From 2945c966b3ccae34a545f7766ca58ccbb2207c97 Mon Sep 17 00:00:00 2001 From: regro-cf-autotick-bot <36490558+regro-cf-autotick-bot@users.noreply.github.com> Date: Tue, 12 Mar 2024 13:28:00 +0000 Subject: [PATCH 1/7] Rebuild for libopenvino_dev 2024 --- .ci_support/migrations/libopenvino_dev2024.yaml | 8 ++++++++ recipe/meta.yaml | 2 +- 2 files changed, 9 insertions(+), 1 deletion(-) create mode 100644 .ci_support/migrations/libopenvino_dev2024.yaml diff --git a/.ci_support/migrations/libopenvino_dev2024.yaml b/.ci_support/migrations/libopenvino_dev2024.yaml new file mode 100644 index 00000000..2a612adf --- /dev/null +++ b/.ci_support/migrations/libopenvino_dev2024.yaml @@ -0,0 +1,8 @@ +__migrator: + build_number: 1 + commit_message: Rebuild for libopenvino_dev 2024 + kind: version + migration_number: 1 +libopenvino_dev: +- '2024.0.0' +migrator_ts: 1709737468.367106 diff --git a/recipe/meta.yaml b/recipe/meta.yaml index 796587df..14f9fe9a 100644 --- a/recipe/meta.yaml +++ b/recipe/meta.yaml @@ -24,7 +24,7 @@ {% set PY_VER_MAJOR = PY_VER.split('.')[0] %} {% set PY_VER_MINOR = PY_VER.split('.')[1] %} -{% set build = 10 %} +{% set build = 11 %} # Allow the qt version to be easily read from the build number 100's value. From 721fc1fee0d86aaec12936bbae2fbe7c4e08d9cc Mon Sep 17 00:00:00 2001 From: Mark Harfouche Date: Sat, 16 Mar 2024 22:01:12 -0400 Subject: [PATCH 2/7] Skip builds, just keep it simple --- recipe/meta.yaml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/recipe/meta.yaml b/recipe/meta.yaml index 14f9fe9a..65603042 100644 --- a/recipe/meta.yaml +++ b/recipe/meta.yaml @@ -63,6 +63,8 @@ source: build: number: {{ build }} + skip: true # [py!=311] + skip: true # [qt_version != "none"] string: headless_py{{ PY_VER_MAJOR }}{{ PY_VER_MINOR }}h{{ PKG_HASH }}_{{ PKG_BUILDNUM }} # [qt_version == "none"] string: qt{{ qt_version }}_py{{ PY_VER_MAJOR }}{{ PY_VER_MINOR }}h{{ PKG_HASH }}_{{ PKG_BUILDNUM }} # [qt_version != "none"] run_exports: From b1789ad8b96bc8eead08513c7cd1e2a1a0a3a0d3 Mon Sep 17 00:00:00 2001 From: Mark Harfouche Date: Sat, 16 Mar 2024 22:05:18 -0400 Subject: [PATCH 3/7] MNT: Re-rendered with conda-build 24.1.2, conda-smithy 3.32.0, and conda-forge-pinning 2024.03.16.19.50.45 --- .azure-pipelines/azure-pipelines-linux.yml | 201 ------- .azure-pipelines/azure-pipelines-osx.yml | 28 - .azure-pipelines/azure-pipelines-win.yml | 86 --- ...1.22python3.10.____cpythonqt_version5.yaml | 75 --- ...1.22python3.10.____cpythonqt_version6.yaml | 75 --- ...2python3.10.____cpythonqt_versionnone.yaml | 75 --- ...y1.22python3.8.____cpythonqt_version5.yaml | 75 --- ...y1.22python3.8.____cpythonqt_version6.yaml | 75 --- ...22python3.8.____cpythonqt_versionnone.yaml | 75 --- ...y1.22python3.9.____73_pypyqt_version5.yaml | 75 --- ...y1.22python3.9.____73_pypyqt_version6.yaml | 75 --- ...22python3.9.____73_pypyqt_versionnone.yaml | 75 --- ...y1.22python3.9.____cpythonqt_version5.yaml | 75 --- ...y1.22python3.9.____cpythonqt_version6.yaml | 75 --- ...22python3.9.____cpythonqt_versionnone.yaml | 75 --- ...1.23python3.11.____cpythonqt_version5.yaml | 75 --- ...1.23python3.11.____cpythonqt_version6.yaml | 75 --- ...3python3.11.____cpythonqt_versionnone.yaml | 6 +- 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...pc64le_numpy1.22python3.9.____cpython.yaml | 69 --- ...c64le_numpy1.26python3.12.____cpython.yaml | 69 --- ...sx_64_numpy1.22python3.10.____cpython.yaml | 73 --- ...osx_64_numpy1.22python3.8.____cpython.yaml | 73 --- ...osx_64_numpy1.22python3.9.____73_pypy.yaml | 73 --- ...osx_64_numpy1.22python3.9.____cpython.yaml | 73 --- ...sx_64_numpy1.23python3.11.____cpython.yaml | 2 +- ...sx_64_numpy1.26python3.12.____cpython.yaml | 73 --- ...arm64_numpy1.22python3.10.____cpython.yaml | 71 --- ..._arm64_numpy1.22python3.8.____cpython.yaml | 71 --- ..._arm64_numpy1.22python3.9.____cpython.yaml | 71 --- ...arm64_numpy1.23python3.11.____cpython.yaml | 2 +- ...arm64_numpy1.26python3.12.____cpython.yaml | 71 --- ...1.22python3.10.____cpythonqt_version5.yaml | 63 --- ...1.22python3.10.____cpythonqt_version6.yaml | 63 --- ...y1.22python3.8.____cpythonqt_version5.yaml | 63 --- ...y1.22python3.8.____cpythonqt_version6.yaml | 63 --- ...y1.22python3.9.____73_pypyqt_version5.yaml | 63 --- ...y1.22python3.9.____73_pypyqt_version6.yaml | 63 --- ...y1.22python3.9.____cpythonqt_version5.yaml | 63 --- ...y1.22python3.9.____cpythonqt_version6.yaml | 63 --- ...1.23python3.11.____cpythonqt_version5.yaml | 63 --- ...1.23python3.11.____cpythonqt_version6.yaml | 63 --- ...1.26python3.12.____cpythonqt_version5.yaml | 63 --- ...1.26python3.12.____cpythonqt_version6.yaml | 63 --- .scripts/run_win_build.bat | 125 ----- README.md | 497 ------------------ azure-pipelines.yml | 3 +- 82 files changed, 6 insertions(+), 6101 deletions(-) delete mode 100755 .azure-pipelines/azure-pipelines-win.yml delete mode 100644 .ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version5.yaml delete mode 100644 .ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version6.yaml delete mode 100644 .ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_versionnone.yaml delete mode 100644 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.ci_support/win_64_numpy1.22python3.9.____73_pypyqt_version5.yaml delete mode 100644 .ci_support/win_64_numpy1.22python3.9.____73_pypyqt_version6.yaml delete mode 100644 .ci_support/win_64_numpy1.22python3.9.____cpythonqt_version5.yaml delete mode 100644 .ci_support/win_64_numpy1.22python3.9.____cpythonqt_version6.yaml delete mode 100644 .ci_support/win_64_numpy1.23python3.11.____cpythonqt_version5.yaml delete mode 100644 .ci_support/win_64_numpy1.23python3.11.____cpythonqt_version6.yaml delete mode 100644 .ci_support/win_64_numpy1.26python3.12.____cpythonqt_version5.yaml delete mode 100644 .ci_support/win_64_numpy1.26python3.12.____cpythonqt_version6.yaml delete mode 100755 .scripts/run_win_build.bat diff --git a/.azure-pipelines/azure-pipelines-linux.yml b/.azure-pipelines/azure-pipelines-linux.yml index 48f9eb57..706a61d6 100755 --- a/.azure-pipelines/azure-pipelines-linux.yml +++ b/.azure-pipelines/azure-pipelines-linux.yml @@ -8,223 +8,22 @@ jobs: vmImage: ubuntu-latest strategy: matrix: - linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version5: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version6: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_versionnone: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone: CONFIG: linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone UPLOAD_PACKAGES: 'True' DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version5: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version6: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_versionnone: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone: CONFIG: linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone UPLOAD_PACKAGES: 'True' DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version5: - CONFIG: linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version6: - CONFIG: linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.22python3.10.____cpythonqt_version6: - CONFIG: linux_aarch64_numpy1.22python3.10.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.22python3.10.____cpythonqt_versionnone: - CONFIG: linux_aarch64_numpy1.22python3.10.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.22python3.8.____cpythonqt_version6: - CONFIG: linux_aarch64_numpy1.22python3.8.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.22python3.8.____cpythonqt_versionnone: - CONFIG: linux_aarch64_numpy1.22python3.8.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.22python3.9.____73_pypyqt_version6: - CONFIG: linux_aarch64_numpy1.22python3.9.____73_pypyqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.22python3.9.____73_pypyqt_versionnone: - CONFIG: linux_aarch64_numpy1.22python3.9.____73_pypyqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.22python3.9.____cpythonqt_version6: - CONFIG: linux_aarch64_numpy1.22python3.9.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.22python3.9.____cpythonqt_versionnone: - CONFIG: linux_aarch64_numpy1.22python3.9.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.23python3.11.____cpythonqt_version6: - CONFIG: linux_aarch64_numpy1.23python3.11.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 linux_aarch64_numpy1.23python3.11.____cpythonqt_versionnone: CONFIG: linux_aarch64_numpy1.23python3.11.____cpythonqt_versionnone UPLOAD_PACKAGES: 'True' DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.26python3.12.____cpythonqt_version6: - CONFIG: linux_aarch64_numpy1.26python3.12.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_aarch64_numpy1.26python3.12.____cpythonqt_versionnone: - CONFIG: linux_aarch64_numpy1.26python3.12.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_ppc64le_numpy1.22python3.10.____cpython: - CONFIG: linux_ppc64le_numpy1.22python3.10.____cpython - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_ppc64le_numpy1.22python3.8.____cpython: - CONFIG: linux_ppc64le_numpy1.22python3.8.____cpython - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_ppc64le_numpy1.22python3.9.____73_pypy: - CONFIG: linux_ppc64le_numpy1.22python3.9.____73_pypy - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_ppc64le_numpy1.22python3.9.____cpython: - CONFIG: linux_ppc64le_numpy1.22python3.9.____cpython - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 linux_ppc64le_numpy1.23python3.11.____cpython: CONFIG: linux_ppc64le_numpy1.23python3.11.____cpython UPLOAD_PACKAGES: 'True' DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_ppc64le_numpy1.26python3.12.____cpython: - CONFIG: linux_ppc64le_numpy1.26python3.12.____cpython - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - maxParallel: 35 timeoutInMinutes: 360 variables: {} diff --git a/.azure-pipelines/azure-pipelines-osx.yml b/.azure-pipelines/azure-pipelines-osx.yml index 76caf949..64877129 100755 --- a/.azure-pipelines/azure-pipelines-osx.yml +++ b/.azure-pipelines/azure-pipelines-osx.yml @@ -8,40 +8,12 @@ jobs: vmImage: macOS-11 strategy: matrix: - osx_64_numpy1.22python3.10.____cpython: - CONFIG: osx_64_numpy1.22python3.10.____cpython - UPLOAD_PACKAGES: 'True' - osx_64_numpy1.22python3.8.____cpython: - CONFIG: osx_64_numpy1.22python3.8.____cpython - UPLOAD_PACKAGES: 'True' - osx_64_numpy1.22python3.9.____73_pypy: - CONFIG: osx_64_numpy1.22python3.9.____73_pypy - UPLOAD_PACKAGES: 'True' - osx_64_numpy1.22python3.9.____cpython: - CONFIG: osx_64_numpy1.22python3.9.____cpython - UPLOAD_PACKAGES: 'True' osx_64_numpy1.23python3.11.____cpython: CONFIG: osx_64_numpy1.23python3.11.____cpython UPLOAD_PACKAGES: 'True' - osx_64_numpy1.26python3.12.____cpython: - CONFIG: osx_64_numpy1.26python3.12.____cpython - UPLOAD_PACKAGES: 'True' - osx_arm64_numpy1.22python3.10.____cpython: - CONFIG: osx_arm64_numpy1.22python3.10.____cpython - UPLOAD_PACKAGES: 'True' - osx_arm64_numpy1.22python3.8.____cpython: - CONFIG: osx_arm64_numpy1.22python3.8.____cpython - UPLOAD_PACKAGES: 'True' - osx_arm64_numpy1.22python3.9.____cpython: - CONFIG: osx_arm64_numpy1.22python3.9.____cpython - UPLOAD_PACKAGES: 'True' osx_arm64_numpy1.23python3.11.____cpython: CONFIG: osx_arm64_numpy1.23python3.11.____cpython UPLOAD_PACKAGES: 'True' - osx_arm64_numpy1.26python3.12.____cpython: - CONFIG: osx_arm64_numpy1.26python3.12.____cpython - UPLOAD_PACKAGES: 'True' - maxParallel: 7 timeoutInMinutes: 360 variables: {} diff --git a/.azure-pipelines/azure-pipelines-win.yml b/.azure-pipelines/azure-pipelines-win.yml deleted file mode 100755 index 2eae2ccc..00000000 --- a/.azure-pipelines/azure-pipelines-win.yml +++ /dev/null @@ -1,86 +0,0 @@ -# This file was generated automatically from conda-smithy. To update this configuration, -# update the conda-forge.yml and/or the recipe/meta.yaml. -# -*- mode: yaml -*- - -jobs: -- job: win - pool: - vmImage: windows-2022 - strategy: - matrix: - win_64_numpy1.22python3.10.____cpythonqt_version5: - CONFIG: win_64_numpy1.22python3.10.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.22python3.10.____cpythonqt_version6: - CONFIG: win_64_numpy1.22python3.10.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.22python3.8.____cpythonqt_version5: - CONFIG: win_64_numpy1.22python3.8.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.22python3.8.____cpythonqt_version6: - CONFIG: win_64_numpy1.22python3.8.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.22python3.9.____73_pypyqt_version5: - CONFIG: win_64_numpy1.22python3.9.____73_pypyqt_version5 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.22python3.9.____73_pypyqt_version6: - CONFIG: win_64_numpy1.22python3.9.____73_pypyqt_version6 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.22python3.9.____cpythonqt_version5: - CONFIG: win_64_numpy1.22python3.9.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.22python3.9.____cpythonqt_version6: - CONFIG: win_64_numpy1.22python3.9.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.23python3.11.____cpythonqt_version5: - CONFIG: win_64_numpy1.23python3.11.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.23python3.11.____cpythonqt_version6: - CONFIG: win_64_numpy1.23python3.11.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.26python3.12.____cpythonqt_version5: - CONFIG: win_64_numpy1.26python3.12.____cpythonqt_version5 - UPLOAD_PACKAGES: 'True' - win_64_numpy1.26python3.12.____cpythonqt_version6: - CONFIG: win_64_numpy1.26python3.12.____cpythonqt_version6 - UPLOAD_PACKAGES: 'True' - maxParallel: 8 - timeoutInMinutes: 360 - variables: - CONDA_BLD_PATH: D:\\bld\\ - UPLOAD_TEMP: D:\\tmp - - steps: - - - task: PythonScript@0 - displayName: 'Download Miniforge' - inputs: - scriptSource: inline - script: | - import urllib.request - url = 'https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-Windows-x86_64.exe' - path = r"$(Build.ArtifactStagingDirectory)/Miniforge.exe" - urllib.request.urlretrieve(url, path) - - - script: | - start /wait "" %BUILD_ARTIFACTSTAGINGDIRECTORY%\Miniforge.exe /InstallationType=JustMe /RegisterPython=0 /S /D=C:\Miniforge - displayName: Install Miniforge - - - powershell: Write-Host "##vso[task.prependpath]C:\Miniforge\Scripts" - displayName: Add conda to PATH - - - script: | - call ".scripts\run_win_build.bat" - displayName: Run Windows build - env: - PYTHONUNBUFFERED: 1 - CONFIG: $(CONFIG) - CI: azure - flow_run_id: azure_$(Build.BuildNumber).$(System.JobAttempt) - remote_url: $(Build.Repository.Uri) - sha: $(Build.SourceVersion) - UPLOAD_PACKAGES: $(UPLOAD_PACKAGES) - UPLOAD_TEMP: $(UPLOAD_TEMP) - BINSTAR_TOKEN: $(BINSTAR_TOKEN) - FEEDSTOCK_TOKEN: $(FEEDSTOCK_TOKEN) - STAGING_BINSTAR_TOKEN: $(STAGING_BINSTAR_TOKEN) \ No newline at end of file diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version5.yaml deleted file mode 100644 index c838ea98..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version6.yaml deleted file mode 100644 index 94d443bc..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_versionnone.yaml deleted file mode 100644 index 6ebcf3dc..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version5.yaml deleted file mode 100644 index 2c96d740..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version6.yaml deleted file mode 100644 index 3ae5fd68..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_versionnone.yaml deleted file mode 100644 index ace042ad..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version5.yaml deleted file mode 100644 index 8ca0ff14..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version6.yaml deleted file mode 100644 index 694068ad..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_versionnone.yaml deleted file mode 100644 index 48c0bb0b..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version5.yaml deleted file mode 100644 index 2e719d89..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version6.yaml deleted file mode 100644 index 3da9ac17..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_versionnone.yaml deleted file mode 100644 index e1a17e09..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version5.yaml deleted file mode 100644 index 0570301e..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.23' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.11.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version6.yaml deleted file mode 100644 index cddad0ae..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.23' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.11.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone.yaml index f2cceba5..42ba37b7 100644 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone.yaml +++ b/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone.yaml @@ -37,7 +37,7 @@ liblapack: liblapacke: - 3.9 *netlib libopenvino_dev: -- 2023.3.0 +- 2024.0.0 libpng: - '1.6' libprotobuf: @@ -58,10 +58,6 @@ python: - 3.11.* *_cpython qt: - '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' qt_version: - none target_platform: diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version5.yaml deleted file mode 100644 index 68aa931a..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version6.yaml deleted file mode 100644 index 74d6d612..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_versionnone.yaml deleted file mode 100644 index 2299b714..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version5.yaml deleted file mode 100644 index c3441195..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version6.yaml deleted file mode 100644 index dea320c0..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_versionnone.yaml deleted file mode 100644 index 70bb1230..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version5.yaml deleted file mode 100644 index 6ccf4ae8..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version6.yaml deleted file mode 100644 index ddcd37fc..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_versionnone.yaml deleted file mode 100644 index d33ad6bd..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version5.yaml deleted file mode 100644 index 7c2db8ac..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version6.yaml deleted file mode 100644 index 61eb9109..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_versionnone.yaml deleted file mode 100644 index 074dc154..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version5.yaml deleted file mode 100644 index 71f3f18c..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version6.yaml deleted file mode 100644 index b59f91a5..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_versionnone.yaml deleted file mode 100644 index dcb1451a..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version5.yaml deleted file mode 100644 index 1c9f056c..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.23' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.11.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version6.yaml deleted file mode 100644 index 2b5fb531..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.23' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.11.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone.yaml index 4ede1641..31669a2b 100644 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone.yaml +++ b/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone.yaml @@ -37,7 +37,7 @@ liblapack: liblapacke: - 3.9 *netlib libopenvino_dev: -- 2023.3.0 +- 2024.0.0 libpng: - '1.6' libprotobuf: @@ -58,10 +58,6 @@ python: - 3.11.* *_cpython qt: - '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' qt_version: - none target_platform: diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version5.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version5.yaml deleted file mode 100644 index 3e25bc65..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version5.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version6.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version6.yaml deleted file mode 100644 index 39e19977..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version6.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_versionnone.yaml deleted file mode 100644 index 3abc400b..00000000 --- a/.ci_support/linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,75 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.22python3.10.____cpythonqt_version6.yaml b/.ci_support/linux_aarch64_numpy1.22python3.10.____cpythonqt_version6.yaml deleted file mode 100644 index f0ce5c89..00000000 --- a/.ci_support/linux_aarch64_numpy1.22python3.10.____cpythonqt_version6.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- '6' -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.22python3.10.____cpythonqt_versionnone.yaml b/.ci_support/linux_aarch64_numpy1.22python3.10.____cpythonqt_versionnone.yaml deleted file mode 100644 index 64b00204..00000000 --- a/.ci_support/linux_aarch64_numpy1.22python3.10.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- none -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.22python3.8.____cpythonqt_version6.yaml b/.ci_support/linux_aarch64_numpy1.22python3.8.____cpythonqt_version6.yaml deleted file mode 100644 index ab70506e..00000000 --- a/.ci_support/linux_aarch64_numpy1.22python3.8.____cpythonqt_version6.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- '6' -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.22python3.8.____cpythonqt_versionnone.yaml b/.ci_support/linux_aarch64_numpy1.22python3.8.____cpythonqt_versionnone.yaml deleted file mode 100644 index 3b384d1e..00000000 --- a/.ci_support/linux_aarch64_numpy1.22python3.8.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- none -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.22python3.9.____73_pypyqt_version6.yaml b/.ci_support/linux_aarch64_numpy1.22python3.9.____73_pypyqt_version6.yaml deleted file mode 100644 index 8d9f5638..00000000 --- a/.ci_support/linux_aarch64_numpy1.22python3.9.____73_pypyqt_version6.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- '6' -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.22python3.9.____73_pypyqt_versionnone.yaml b/.ci_support/linux_aarch64_numpy1.22python3.9.____73_pypyqt_versionnone.yaml deleted file mode 100644 index 12429ab9..00000000 --- a/.ci_support/linux_aarch64_numpy1.22python3.9.____73_pypyqt_versionnone.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- none -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.22python3.9.____cpythonqt_version6.yaml b/.ci_support/linux_aarch64_numpy1.22python3.9.____cpythonqt_version6.yaml deleted file mode 100644 index 12c51131..00000000 --- a/.ci_support/linux_aarch64_numpy1.22python3.9.____cpythonqt_version6.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- '6' -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.22python3.9.____cpythonqt_versionnone.yaml b/.ci_support/linux_aarch64_numpy1.22python3.9.____cpythonqt_versionnone.yaml deleted file mode 100644 index 8ba8a4bc..00000000 --- a/.ci_support/linux_aarch64_numpy1.22python3.9.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- none -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.23python3.11.____cpythonqt_version6.yaml b/.ci_support/linux_aarch64_numpy1.23python3.11.____cpythonqt_version6.yaml deleted file mode 100644 index a0f0f5d2..00000000 --- a/.ci_support/linux_aarch64_numpy1.23python3.11.____cpythonqt_version6.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.23' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.11.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- '6' -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.23python3.11.____cpythonqt_versionnone.yaml b/.ci_support/linux_aarch64_numpy1.23python3.11.____cpythonqt_versionnone.yaml index 4d6398be..353def0c 100644 --- a/.ci_support/linux_aarch64_numpy1.23python3.11.____cpythonqt_versionnone.yaml +++ b/.ci_support/linux_aarch64_numpy1.23python3.11.____cpythonqt_versionnone.yaml @@ -41,7 +41,7 @@ liblapack: liblapacke: - 3.9 *netlib libopenvino_dev: -- 2023.3.0 +- 2024.0.0 libpng: - '1.6' libprotobuf: @@ -62,8 +62,6 @@ python: - 3.11.* *_cpython qt: - '5.15' -qt6_main: -- '6.6' qt_version: - none target_platform: diff --git a/.ci_support/linux_aarch64_numpy1.26python3.12.____cpythonqt_version6.yaml b/.ci_support/linux_aarch64_numpy1.26python3.12.____cpythonqt_version6.yaml deleted file mode 100644 index 73579a49..00000000 --- a/.ci_support/linux_aarch64_numpy1.26python3.12.____cpythonqt_version6.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- '6' -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_aarch64_numpy1.26python3.12.____cpythonqt_versionnone.yaml b/.ci_support/linux_aarch64_numpy1.26python3.12.____cpythonqt_versionnone.yaml deleted file mode 100644 index ea827c3f..00000000 --- a/.ci_support/linux_aarch64_numpy1.26python3.12.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,77 +0,0 @@ -BUILD: -- aarch64-conda_cos7-linux-gnu -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_arch: -- aarch64 -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_version: -- none -target_platform: -- linux-aarch64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_ppc64le_numpy1.22python3.10.____cpython.yaml b/.ci_support/linux_ppc64le_numpy1.22python3.10.____cpython.yaml deleted file mode 100644 index db02facd..00000000 --- a/.ci_support/linux_ppc64le_numpy1.22python3.10.____cpython.yaml +++ /dev/null @@ -1,69 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- linux-ppc64le -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_ppc64le_numpy1.22python3.8.____cpython.yaml b/.ci_support/linux_ppc64le_numpy1.22python3.8.____cpython.yaml deleted file mode 100644 index ea520a18..00000000 --- a/.ci_support/linux_ppc64le_numpy1.22python3.8.____cpython.yaml +++ /dev/null @@ -1,69 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- linux-ppc64le -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_ppc64le_numpy1.22python3.9.____73_pypy.yaml b/.ci_support/linux_ppc64le_numpy1.22python3.9.____73_pypy.yaml deleted file mode 100644 index 9184f6c4..00000000 --- a/.ci_support/linux_ppc64le_numpy1.22python3.9.____73_pypy.yaml +++ /dev/null @@ -1,69 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt_version: -- none -target_platform: -- linux-ppc64le -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_ppc64le_numpy1.22python3.9.____cpython.yaml b/.ci_support/linux_ppc64le_numpy1.22python3.9.____cpython.yaml deleted file mode 100644 index d4876e53..00000000 --- a/.ci_support/linux_ppc64le_numpy1.22python3.9.____cpython.yaml +++ /dev/null @@ -1,69 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- linux-ppc64le -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_ppc64le_numpy1.26python3.12.____cpython.yaml b/.ci_support/linux_ppc64le_numpy1.26python3.12.____cpython.yaml deleted file mode 100644 index d9cb3500..00000000 --- a/.ci_support/linux_ppc64le_numpy1.26python3.12.____cpython.yaml +++ /dev/null @@ -1,69 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- linux-ppc64le -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/osx_64_numpy1.22python3.10.____cpython.yaml b/.ci_support/osx_64_numpy1.22python3.10.____cpython.yaml deleted file mode 100644 index 6a34b837..00000000 --- a/.ci_support/osx_64_numpy1.22python3.10.____cpython.yaml +++ /dev/null @@ -1,73 +0,0 @@ -MACOSX_DEPLOYMENT_TARGET: -- '10.13' -MACOSX_SDK_VERSION: -- '10.13' -c_compiler: -- clang -c_compiler_version: -- '16' -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- clangxx -cxx_compiler_version: -- '16' -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -macos_machine: -- x86_64-apple-darwin13.4.0 -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- osx-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/osx_64_numpy1.22python3.8.____cpython.yaml b/.ci_support/osx_64_numpy1.22python3.8.____cpython.yaml deleted file mode 100644 index 1d223c25..00000000 --- a/.ci_support/osx_64_numpy1.22python3.8.____cpython.yaml +++ /dev/null @@ -1,73 +0,0 @@ -MACOSX_DEPLOYMENT_TARGET: -- '10.13' -MACOSX_SDK_VERSION: -- '10.13' -c_compiler: -- clang -c_compiler_version: -- '16' -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- clangxx -cxx_compiler_version: -- '16' -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -macos_machine: -- x86_64-apple-darwin13.4.0 -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- osx-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/osx_64_numpy1.22python3.9.____73_pypy.yaml b/.ci_support/osx_64_numpy1.22python3.9.____73_pypy.yaml deleted file mode 100644 index 4d1d3f02..00000000 --- a/.ci_support/osx_64_numpy1.22python3.9.____73_pypy.yaml +++ /dev/null @@ -1,73 +0,0 @@ -MACOSX_DEPLOYMENT_TARGET: -- '10.13' -MACOSX_SDK_VERSION: -- '10.13' -c_compiler: -- clang -c_compiler_version: -- '16' -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- clangxx -cxx_compiler_version: -- '16' -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -macos_machine: -- x86_64-apple-darwin13.4.0 -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt_version: -- none -target_platform: -- osx-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/osx_64_numpy1.22python3.9.____cpython.yaml b/.ci_support/osx_64_numpy1.22python3.9.____cpython.yaml deleted file mode 100644 index 3d5edc43..00000000 --- a/.ci_support/osx_64_numpy1.22python3.9.____cpython.yaml +++ /dev/null @@ -1,73 +0,0 @@ -MACOSX_DEPLOYMENT_TARGET: -- '10.13' -MACOSX_SDK_VERSION: -- '10.13' -c_compiler: -- clang -c_compiler_version: -- '16' -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- clangxx -cxx_compiler_version: -- '16' -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -macos_machine: -- x86_64-apple-darwin13.4.0 -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- osx-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/osx_64_numpy1.23python3.11.____cpython.yaml b/.ci_support/osx_64_numpy1.23python3.11.____cpython.yaml index 8bf3ec4a..c1df5b85 100644 --- a/.ci_support/osx_64_numpy1.23python3.11.____cpython.yaml +++ b/.ci_support/osx_64_numpy1.23python3.11.____cpython.yaml @@ -37,7 +37,7 @@ liblapack: liblapacke: - 3.9 *netlib libopenvino_dev: -- 2023.3.0 +- 2024.0.0 libpng: - '1.6' libprotobuf: diff --git a/.ci_support/osx_64_numpy1.26python3.12.____cpython.yaml b/.ci_support/osx_64_numpy1.26python3.12.____cpython.yaml deleted file mode 100644 index 8bc203d9..00000000 --- a/.ci_support/osx_64_numpy1.26python3.12.____cpython.yaml +++ /dev/null @@ -1,73 +0,0 @@ -MACOSX_DEPLOYMENT_TARGET: -- '10.13' -MACOSX_SDK_VERSION: -- '10.13' -c_compiler: -- clang -c_compiler_version: -- '16' -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- clangxx -cxx_compiler_version: -- '16' -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -macos_machine: -- x86_64-apple-darwin13.4.0 -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- osx-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/osx_arm64_numpy1.22python3.10.____cpython.yaml b/.ci_support/osx_arm64_numpy1.22python3.10.____cpython.yaml deleted file mode 100644 index 1a6fb2cf..00000000 --- a/.ci_support/osx_arm64_numpy1.22python3.10.____cpython.yaml +++ /dev/null @@ -1,71 +0,0 @@ -MACOSX_DEPLOYMENT_TARGET: -- '11.0' -c_compiler: -- clang -c_compiler_version: -- '16' -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- clangxx -cxx_compiler_version: -- '16' -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -macos_machine: -- arm64-apple-darwin20.0.0 -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- osx-arm64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/osx_arm64_numpy1.22python3.8.____cpython.yaml b/.ci_support/osx_arm64_numpy1.22python3.8.____cpython.yaml deleted file mode 100644 index 36f80535..00000000 --- a/.ci_support/osx_arm64_numpy1.22python3.8.____cpython.yaml +++ /dev/null @@ -1,71 +0,0 @@ -MACOSX_DEPLOYMENT_TARGET: -- '11.0' -c_compiler: -- clang -c_compiler_version: -- '16' -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- clangxx -cxx_compiler_version: -- '16' -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -macos_machine: -- arm64-apple-darwin20.0.0 -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- osx-arm64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/osx_arm64_numpy1.22python3.9.____cpython.yaml b/.ci_support/osx_arm64_numpy1.22python3.9.____cpython.yaml deleted file mode 100644 index 4a02e20b..00000000 --- a/.ci_support/osx_arm64_numpy1.22python3.9.____cpython.yaml +++ /dev/null @@ -1,71 +0,0 @@ -MACOSX_DEPLOYMENT_TARGET: -- '11.0' -c_compiler: -- clang -c_compiler_version: -- '16' -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- clangxx -cxx_compiler_version: -- '16' -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -macos_machine: -- arm64-apple-darwin20.0.0 -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- osx-arm64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/osx_arm64_numpy1.23python3.11.____cpython.yaml b/.ci_support/osx_arm64_numpy1.23python3.11.____cpython.yaml index 330f96f7..6f0a515c 100644 --- a/.ci_support/osx_arm64_numpy1.23python3.11.____cpython.yaml +++ b/.ci_support/osx_arm64_numpy1.23python3.11.____cpython.yaml @@ -35,7 +35,7 @@ liblapack: liblapacke: - 3.9 *netlib libopenvino_dev: -- 2023.3.0 +- 2024.0.0 libpng: - '1.6' libprotobuf: diff --git a/.ci_support/osx_arm64_numpy1.26python3.12.____cpython.yaml b/.ci_support/osx_arm64_numpy1.26python3.12.____cpython.yaml deleted file mode 100644 index e667323d..00000000 --- a/.ci_support/osx_arm64_numpy1.26python3.12.____cpython.yaml +++ /dev/null @@ -1,71 +0,0 @@ -MACOSX_DEPLOYMENT_TARGET: -- '11.0' -c_compiler: -- clang -c_compiler_version: -- '16' -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- clangxx -cxx_compiler_version: -- '16' -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -macos_machine: -- arm64-apple-darwin20.0.0 -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- osx-arm64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.22python3.10.____cpythonqt_version5.yaml b/.ci_support/win_64_numpy1.22python3.10.____cpythonqt_version5.yaml deleted file mode 100644 index 9541e910..00000000 --- a/.ci_support/win_64_numpy1.22python3.10.____cpythonqt_version5.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.22python3.10.____cpythonqt_version6.yaml b/.ci_support/win_64_numpy1.22python3.10.____cpythonqt_version6.yaml deleted file mode 100644 index ed5f3515..00000000 --- a/.ci_support/win_64_numpy1.22python3.10.____cpythonqt_version6.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.10.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.22python3.8.____cpythonqt_version5.yaml b/.ci_support/win_64_numpy1.22python3.8.____cpythonqt_version5.yaml deleted file mode 100644 index 6d4a9959..00000000 --- a/.ci_support/win_64_numpy1.22python3.8.____cpythonqt_version5.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.22python3.8.____cpythonqt_version6.yaml b/.ci_support/win_64_numpy1.22python3.8.____cpythonqt_version6.yaml deleted file mode 100644 index 783a253a..00000000 --- a/.ci_support/win_64_numpy1.22python3.8.____cpythonqt_version6.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.8.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.22python3.9.____73_pypyqt_version5.yaml b/.ci_support/win_64_numpy1.22python3.9.____73_pypyqt_version5.yaml deleted file mode 100644 index f23b1807..00000000 --- a/.ci_support/win_64_numpy1.22python3.9.____73_pypyqt_version5.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.22python3.9.____73_pypyqt_version6.yaml b/.ci_support/win_64_numpy1.22python3.9.____73_pypyqt_version6.yaml deleted file mode 100644 index 0c3f0364..00000000 --- a/.ci_support/win_64_numpy1.22python3.9.____73_pypyqt_version6.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_73_pypy -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.22python3.9.____cpythonqt_version5.yaml b/.ci_support/win_64_numpy1.22python3.9.____cpythonqt_version5.yaml deleted file mode 100644 index 301d27c4..00000000 --- a/.ci_support/win_64_numpy1.22python3.9.____cpythonqt_version5.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.22python3.9.____cpythonqt_version6.yaml b/.ci_support/win_64_numpy1.22python3.9.____cpythonqt_version6.yaml deleted file mode 100644 index 454c3240..00000000 --- a/.ci_support/win_64_numpy1.22python3.9.____cpythonqt_version6.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.22' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.9.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.23python3.11.____cpythonqt_version5.yaml b/.ci_support/win_64_numpy1.23python3.11.____cpythonqt_version5.yaml deleted file mode 100644 index 2bf6bd8d..00000000 --- a/.ci_support/win_64_numpy1.23python3.11.____cpythonqt_version5.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.23' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.11.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.23python3.11.____cpythonqt_version6.yaml b/.ci_support/win_64_numpy1.23python3.11.____cpythonqt_version6.yaml deleted file mode 100644 index ccb32cbf..00000000 --- a/.ci_support/win_64_numpy1.23python3.11.____cpythonqt_version6.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.23' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.11.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.26python3.12.____cpythonqt_version5.yaml b/.ci_support/win_64_numpy1.26python3.12.____cpythonqt_version5.yaml deleted file mode 100644 index 2692b7e1..00000000 --- a/.ci_support/win_64_numpy1.26python3.12.____cpythonqt_version5.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '5' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/win_64_numpy1.26python3.12.____cpythonqt_version6.yaml b/.ci_support/win_64_numpy1.26python3.12.____cpythonqt_version6.yaml deleted file mode 100644 index dc4a47bd..00000000 --- a/.ci_support/win_64_numpy1.26python3.12.____cpythonqt_version6.yaml +++ /dev/null @@ -1,63 +0,0 @@ -c_compiler: -- vs2019 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- vs2019 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2023.3.0 -libpng: -- '1.6' -libprotobuf: -- 4.25.2 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.26' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.12.* *_cpython -qt: -- '5.15' -qt6_main: -- '6.6' -qt_main: -- '5.15' -qt_version: -- '6' -target_platform: -- win-64 -zip_keys: -- - python - - numpy -zlib: -- '1.2' diff --git a/.scripts/run_win_build.bat b/.scripts/run_win_build.bat deleted file mode 100755 index 6d546976..00000000 --- a/.scripts/run_win_build.bat +++ /dev/null @@ -1,125 +0,0 @@ -:: PLEASE NOTE: This script has been automatically generated by conda-smithy. Any changes here -:: will be lost next time ``conda smithy rerender`` is run. If you would like to make permanent -:: changes to this script, consider a proposal to conda-smithy so that other feedstocks can also -:: benefit from the improvement. - -:: Note: we assume a Miniforge installation is available - -:: INPUTS (required environment variables) -:: CONFIG: name of the .ci_support/*.yaml file for this job -:: CI: azure, github_actions, or unset -:: UPLOAD_PACKAGES: true or false -:: UPLOAD_ON_BRANCH: true or false - -setlocal enableextensions enabledelayedexpansion - -call :start_group "Configuring conda" - -:: Activate the base conda environment -call activate base -:: Configure the solver -set "CONDA_SOLVER=libmamba" -if !errorlevel! neq 0 exit /b !errorlevel! -set "CONDA_LIBMAMBA_SOLVER_NO_CHANNELS_FROM_INSTALLED=1" - -:: Provision the necessary dependencies to build the recipe later -echo Installing dependencies -mamba.exe install "python=3.10" pip mamba conda-build conda-forge-ci-setup=4 "conda-build>=24.1" -c conda-forge --strict-channel-priority --yes -if !errorlevel! neq 0 exit /b !errorlevel! - -:: Set basic configuration -echo Setting up configuration -setup_conda_rc .\ ".\recipe" .\.ci_support\%CONFIG%.yaml -if !errorlevel! neq 0 exit /b !errorlevel! -echo Running build setup -CALL run_conda_forge_build_setup - - -if !errorlevel! neq 0 exit /b !errorlevel! - -if EXIST LICENSE.txt ( - echo Copying feedstock license - copy LICENSE.txt "recipe\\recipe-scripts-license.txt" -) -if NOT [%HOST_PLATFORM%] == [%BUILD_PLATFORM%] ( - if [%CROSSCOMPILING_EMULATOR%] == [] ( - set "EXTRA_CB_OPTIONS=%EXTRA_CB_OPTIONS% --no-test" - ) -) - -if NOT [%flow_run_id%] == [] ( - set "EXTRA_CB_OPTIONS=%EXTRA_CB_OPTIONS% --extra-meta flow_run_id=%flow_run_id% remote_url=%remote_url% sha=%sha%" -) - -call :end_group - -:: Build the recipe -echo Building recipe -conda-build.exe "recipe" -m .ci_support\%CONFIG%.yaml --suppress-variables %EXTRA_CB_OPTIONS% -if !errorlevel! neq 0 exit /b !errorlevel! - -:: Prepare some environment variables for the upload step -if /i "%CI%" == "github_actions" ( - set "FEEDSTOCK_NAME=%GITHUB_REPOSITORY:*/=%" - set "GIT_BRANCH=%GITHUB_REF:refs/heads/=%" - if /i "%GITHUB_EVENT_NAME%" == "pull_request" ( - set "IS_PR_BUILD=True" - ) else ( - set "IS_PR_BUILD=False" - ) - set "TEMP=%RUNNER_TEMP%" -) -if /i "%CI%" == "azure" ( - set "FEEDSTOCK_NAME=%BUILD_REPOSITORY_NAME:*/=%" - set "GIT_BRANCH=%BUILD_SOURCEBRANCHNAME%" - if /i "%BUILD_REASON%" == "PullRequest" ( - set "IS_PR_BUILD=True" - ) else ( - set "IS_PR_BUILD=False" - ) - set "TEMP=%UPLOAD_TEMP%" -) - -:: Validate -call :start_group "Validating outputs" -validate_recipe_outputs "%FEEDSTOCK_NAME%" -if !errorlevel! neq 0 exit /b !errorlevel! -call :end_group - -if /i "%UPLOAD_PACKAGES%" == "true" ( - if /i "%IS_PR_BUILD%" == "false" ( - call :start_group "Uploading packages" - if not exist "%TEMP%\" md "%TEMP%" - set "TMP=%TEMP%" - upload_package --validate --feedstock-name="%FEEDSTOCK_NAME%" .\ ".\recipe" .ci_support\%CONFIG%.yaml - if !errorlevel! neq 0 exit /b !errorlevel! - call :end_group - ) -) - -exit - -:: Logging subroutines - -:start_group -if /i "%CI%" == "github_actions" ( - echo ::group::%~1 - exit /b -) -if /i "%CI%" == "azure" ( - echo ##[group]%~1 - exit /b -) -echo %~1 -exit /b - -:end_group -if /i "%CI%" == "github_actions" ( - echo ::endgroup:: - exit /b -) -if /i "%CI%" == "azure" ( - echo ##[endgroup] - exit /b -) -exit /b \ No newline at end of file diff --git a/README.md b/README.md index 507f1e64..90dae9b1 100644 --- a/README.md +++ b/README.md @@ -31,229 +31,12 @@ Current build status - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
VariantStatus
linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.10.____cpythonqt_versionnone - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.8.____cpythonqt_versionnone - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version5 - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_version6 - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.9.____73_pypyqt_versionnone - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.24.4numpy1.22python3.9.____cpythonqt_versionnone - - variant - -
linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone variant
linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.24.4numpy1.26python3.12.____cpythonqt_versionnone - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.10.____cpythonqt_versionnone - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.8.____cpythonqt_versionnone - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version5 - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_version6 - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.9.____73_pypyqt_versionnone - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.25.2numpy1.22python3.9.____cpythonqt_versionnone - - variant - -
linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone @@ -261,90 +44,6 @@ Current build status variant
linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version5 - - variant - -
linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_version6 - - variant - -
linux_64_libprotobuf4.25.2numpy1.26python3.12.____cpythonqt_versionnone - - variant - -
linux_aarch64_numpy1.22python3.10.____cpythonqt_version6 - - variant - -
linux_aarch64_numpy1.22python3.10.____cpythonqt_versionnone - - variant - -
linux_aarch64_numpy1.22python3.8.____cpythonqt_version6 - - variant - -
linux_aarch64_numpy1.22python3.8.____cpythonqt_versionnone - - variant - -
linux_aarch64_numpy1.22python3.9.____73_pypyqt_version6 - - variant - -
linux_aarch64_numpy1.22python3.9.____73_pypyqt_versionnone - - variant - -
linux_aarch64_numpy1.22python3.9.____cpythonqt_version6 - - variant - -
linux_aarch64_numpy1.22python3.9.____cpythonqt_versionnone - - variant - -
linux_aarch64_numpy1.23python3.11.____cpythonqt_version6 - - variant - -
linux_aarch64_numpy1.23python3.11.____cpythonqt_versionnone @@ -352,48 +51,6 @@ Current build status variant
linux_aarch64_numpy1.26python3.12.____cpythonqt_version6 - - variant - -
linux_aarch64_numpy1.26python3.12.____cpythonqt_versionnone - - variant - -
linux_ppc64le_numpy1.22python3.10.____cpython - - variant - -
linux_ppc64le_numpy1.22python3.8.____cpython - - variant - -
linux_ppc64le_numpy1.22python3.9.____73_pypy - - variant - -
linux_ppc64le_numpy1.22python3.9.____cpython - - variant - -
linux_ppc64le_numpy1.23python3.11.____cpython @@ -401,41 +58,6 @@ Current build status variant
linux_ppc64le_numpy1.26python3.12.____cpython - - variant - -
osx_64_numpy1.22python3.10.____cpython - - variant - -
osx_64_numpy1.22python3.8.____cpython - - variant - -
osx_64_numpy1.22python3.9.____73_pypy - - variant - -
osx_64_numpy1.22python3.9.____cpython - - variant - -
osx_64_numpy1.23python3.11.____cpython @@ -443,34 +65,6 @@ Current build status variant
osx_64_numpy1.26python3.12.____cpython - - variant - -
osx_arm64_numpy1.22python3.10.____cpython - - variant - -
osx_arm64_numpy1.22python3.8.____cpython - - variant - -
osx_arm64_numpy1.22python3.9.____cpython - - variant - -
osx_arm64_numpy1.23python3.11.____cpython @@ -478,97 +72,6 @@ Current build status variant
osx_arm64_numpy1.26python3.12.____cpython - - variant - -
win_64_numpy1.22python3.10.____cpythonqt_version5 - - variant - -
win_64_numpy1.22python3.10.____cpythonqt_version6 - - variant - -
win_64_numpy1.22python3.8.____cpythonqt_version5 - - variant - -
win_64_numpy1.22python3.8.____cpythonqt_version6 - - variant - -
win_64_numpy1.22python3.9.____73_pypyqt_version5 - - variant - -
win_64_numpy1.22python3.9.____73_pypyqt_version6 - - variant - -
win_64_numpy1.22python3.9.____cpythonqt_version5 - - variant - -
win_64_numpy1.22python3.9.____cpythonqt_version6 - - variant - -
win_64_numpy1.23python3.11.____cpythonqt_version5 - - variant - -
win_64_numpy1.23python3.11.____cpythonqt_version6 - - variant - -
win_64_numpy1.26python3.12.____cpythonqt_version5 - - variant - -
win_64_numpy1.26python3.12.____cpythonqt_version6 - - variant - -
diff --git a/azure-pipelines.yml b/azure-pipelines.yml index e5306da9..33a441c1 100644 --- a/azure-pipelines.yml +++ b/azure-pipelines.yml @@ -4,5 +4,4 @@ jobs: - template: ./.azure-pipelines/azure-pipelines-linux.yml - - template: ./.azure-pipelines/azure-pipelines-osx.yml - - template: ./.azure-pipelines/azure-pipelines-win.yml \ No newline at end of file + - template: ./.azure-pipelines/azure-pipelines-osx.yml \ No newline at end of file From b8ad11d96c550c4277aa7aa52c77ac0ffe657253 Mon Sep 17 00:00:00 2001 From: Ilya Lavrenov Date: Tue, 19 Mar 2024 10:08:21 +0400 Subject: [PATCH 4/7] Added patch for OpenVINO 2022.1 and newer --- recipe/meta.yaml | 2 + .../0005-openvino-2022.1.0-and-newer.patch | 4254 +++++++++++++++++ 2 files changed, 4256 insertions(+) create mode 100644 recipe/patches_opencv/0005-openvino-2022.1.0-and-newer.patch diff --git a/recipe/meta.yaml b/recipe/meta.yaml index 65603042..8553d354 100644 --- a/recipe/meta.yaml +++ b/recipe/meta.yaml @@ -50,6 +50,8 @@ source: - patches_opencv/0002-delete-lines-that-download-opencv.patch - patches_opencv/0003-find-pkgconfig-on-windows.patch - patches_opencv/0004-fix-detection-for-protobuf-23.x.patch + # backport of https://github.com/opencv/opencv/pull/25199 + - patches_opencv/0005-openvino-2022.1.0-and-newer.patch - url: https://github.com/opencv/opencv_contrib/archive/{{ version }}.tar.gz fn: opencv_contrib-{{ version }}.tar.gz sha256: 8952c45a73b75676c522dd574229f563e43c271ae1d5bbbd26f8e2b6bc1a4dae diff --git a/recipe/patches_opencv/0005-openvino-2022.1.0-and-newer.patch b/recipe/patches_opencv/0005-openvino-2022.1.0-and-newer.patch new file mode 100644 index 00000000..0c1c2985 --- /dev/null +++ b/recipe/patches_opencv/0005-openvino-2022.1.0-and-newer.patch @@ -0,0 +1,4254 @@ +diff --git a/cmake/OpenCVDetectInferenceEngine.cmake b/cmake/OpenCVDetectInferenceEngine.cmake +index 319fd5bf0a..9a2eb38b03 100644 +--- a/cmake/OpenCVDetectInferenceEngine.cmake ++++ b/cmake/OpenCVDetectInferenceEngine.cmake +@@ -13,67 +13,3 @@ if(WITH_OPENVINO) + return() + endif() + endif() +- +-# ====================== +- +-if(WITH_OPENVINO) +- find_package(OpenVINO QUIET) +- if(OpenVINO_FOUND) +- message(STATUS "OpenVINO FOUND: ${OpenVINO_VERSION}") +- math(EXPR ver "${OpenVINO_VERSION_MAJOR} * 1000000 + ${OpenVINO_VERSION_MINOR} * 10000 + ${OpenVINO_VERSION_PATCH} * 100") +- ocv_add_external_target(openvino "" "openvino::runtime" "INF_ENGINE_RELEASE=${ver};HAVE_NGRAPH;HAVE_DNN_NGRAPH;HAVE_INF_ENGINE") +- set(HAVE_OPENVINO 1) +- return() +- endif() +-endif() +- +-# ====================== +- +-find_package(InferenceEngine QUIET) +-if(InferenceEngine_FOUND) +- set(INF_ENGINE_TARGET ${InferenceEngine_LIBRARIES}) +- set(INF_ENGINE_VERSION "${InferenceEngine_VERSION}") +- message(STATUS "Detected InferenceEngine: cmake package (${InferenceEngine_VERSION})") +-endif() +- +-if(DEFINED InferenceEngine_VERSION) +- message(STATUS "InferenceEngine: ${InferenceEngine_VERSION}") +- if(NOT INF_ENGINE_RELEASE AND NOT (InferenceEngine_VERSION VERSION_LESS "2021.4")) +- math(EXPR INF_ENGINE_RELEASE_INIT "${InferenceEngine_VERSION_MAJOR} * 1000000 + ${InferenceEngine_VERSION_MINOR} * 10000 + ${InferenceEngine_VERSION_PATCH} * 100") +- endif() +-endif() +-if(NOT INF_ENGINE_RELEASE AND NOT INF_ENGINE_RELEASE_INIT) +- message(STATUS "WARNING: InferenceEngine version has not been set, 2021.4.2 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.") +- set(INF_ENGINE_RELEASE_INIT "2021040200") +-elseif(DEFINED INF_ENGINE_RELEASE) +- set(INF_ENGINE_RELEASE_INIT "${INF_ENGINE_RELEASE}") +-endif() +-set(INF_ENGINE_RELEASE "${INF_ENGINE_RELEASE_INIT}" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2020.1.0.2 -> 2020010002)") +- +-set(tgts) +-set(defs) +- +-# Add more features to the target +-if(INF_ENGINE_TARGET) +- set_target_properties(${INF_ENGINE_TARGET} PROPERTIES +- INTERFACE_COMPILE_DEFINITIONS "HAVE_INF_ENGINE=1;INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}" +- ) +- list(APPEND tgts ${INF_ENGINE_TARGET}) +- list(APPEND defs "INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}" "HAVE_INF_ENGINE") +-endif() +- +-if(WITH_NGRAPH OR NOT DEFINED WITH_NGRAPH) +- find_package(ngraph QUIET) +- if(ngraph_FOUND) +- ocv_assert(TARGET ngraph::ngraph) +- if(INF_ENGINE_RELEASE VERSION_LESS "2019039999") +- message(WARNING "nGraph is not tested with current InferenceEngine version: INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}") +- endif() +- message(STATUS "Detected ngraph: cmake package (${ngraph_VERSION})") +- set(HAVE_NGRAPH ON) +- list(APPEND tgts ngraph::ngraph) +- list(APPEND defs "HAVE_NGRAPH" "HAVE_DNN_NGRAPH") +- endif() +-endif() +- +-ocv_add_external_target(openvino "" "${tgts}" "${defs}") +diff --git a/modules/dnn/src/ie_ngraph.cpp b/modules/dnn/src/ie_ngraph.cpp +index 7eeb62bcf6..6e7b9f9be5 100644 +--- a/modules/dnn/src/ie_ngraph.cpp ++++ b/modules/dnn/src/ie_ngraph.cpp +@@ -14,7 +14,7 @@ + #include + + #ifdef HAVE_DNN_NGRAPH +-#include ++#include + #endif // HAVE_DNN_NGRAPH + + #include +@@ -35,36 +35,6 @@ static bool DNN_IE_SERIALIZE = utils::getConfigurationParameterBool("OPENCV_DNN_ + static std::string kDefaultInpLayerName = "opencv_ngraph_empty_inp_layer_name"; + static constexpr const char* kOpenCVLayersType = "opencv_ngraph_layer"; + +-#if INF_ENGINE_VER_MAJOR_LT(INF_ENGINE_RELEASE_2022_1) +-static std::string shapesToStr(const std::vector& mats) +-{ +- std::ostringstream shapes; +- shapes << mats.size() << " "; +- for (const Mat& m : mats) +- { +- shapes << m.dims << " "; +- for (int i = 0; i < m.dims; ++i) +- shapes << m.size[i] << " "; +- } +- return shapes.str(); +-} +- +-static void strToShapes(const std::string& str, std::vector >& shapes) +-{ +- std::istringstream ss(str); +- int num, dims; +- ss >> num; +- shapes.resize(num); +- for (int i = 0; i < num; ++i) +- { +- ss >> dims; +- shapes[i].resize(dims); +- for (int j = 0; j < dims; ++j) +- ss >> shapes[i][j]; +- } +-} +-#endif // OpenVINO < 2022.1 +- + static std::vector > + ngraphWrappers(const std::vector >& ptrs) + { +@@ -78,13 +48,11 @@ ngraphWrappers(const std::vector >& ptrs) + return wrappers; + } + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) +- + class NgraphCustomOp: public ov::op::Op { + public: + OPENVINO_OP(kOpenCVLayersType); + +- NgraphCustomOp(const ngraph::OutputVector& inputs, Ptr& cvLayer, const std::vector& outputs, const std::vector& internals): ++ NgraphCustomOp(const ov::OutputVector& inputs, Ptr& cvLayer, const std::vector& outputs, const std::vector& internals): + Op(inputs), cvLayer(cvLayer), outputs(outputs), internals(internals) + { + constructor_validate_and_infer_types(); +@@ -103,7 +71,7 @@ public: + } + } + +- std::shared_ptr clone_with_new_inputs(const ngraph::OutputVector& new_args) const override ++ std::shared_ptr clone_with_new_inputs(const ov::OutputVector& new_args) const override + { + return std::make_shared(new_args, cvLayer, outputs, internals); + } +@@ -131,265 +99,13 @@ public: + std::vector outputs, internals; + }; + +-#else +- +-class NgraphCustomOp: public ngraph::op::Op { +-public: +- const ngraph::NodeTypeInfo& get_type_info() const override +- { +- static constexpr ngraph::NodeTypeInfo type_info{kOpenCVLayersType, static_cast(0)}; +- return type_info; +- } +- +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_3) +- NgraphCustomOp(const ngraph::OutputVector& inputs, +-#else +- NgraphCustomOp(const ngraph::NodeVector& inputs, +-#endif +- const std::map& params = {}): +- Op(inputs), params(params) +- { +- constructor_validate_and_infer_types(); +- } +- +- ~NgraphCustomOp() +- { +- // nothing +- } +- +- void validate_and_infer_types() override +- { +- std::vector > shapes; +- strToShapes(params["outputs"], shapes); +- set_output_size(shapes.size()); +- for (size_t i = 0; i < shapes.size(); ++i) +- { +- ngraph::Shape output_shape(shapes[i]); +- set_output_type(i, get_input_element_type(0), output_shape); +- } +- } +- +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_4) +- std::shared_ptr clone_with_new_inputs(const ngraph::OutputVector& new_args) const override +- { +- return std::make_shared(new_args, params); +- } +-#else +- std::shared_ptr copy_with_new_args(const ngraph::NodeVector& new_args) const override +- { +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_3) +- return std::make_shared(ngraph::as_output_vector(new_args), params); +-#else +- return std::make_shared(new_args, params); +-#endif +- } +-#endif +- +- bool visit_attributes(ngraph::AttributeVisitor& visitor) override +- { +- for (auto& attr : params) +- { +- if (attr.second.is()) +- visitor.on_attribute(attr.first, attr.second.as()); +- } +- return true; +- } +- +- std::map params; +-}; +- +- +-class InfEngineNgraphCustomLayer : public InferenceEngine::ILayerExecImpl +-{ +-public: +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_2) +- explicit InfEngineNgraphCustomLayer(const std::shared_ptr& _node) +- { +- node = std::dynamic_pointer_cast(_node); +- CV_Assert(node); +- std::string implStr = node->params["impl"]; +- std::istringstream iss(implStr); +-#else +- explicit InfEngineNgraphCustomLayer(const InferenceEngine::CNNLayer& layer) : cnnLayer(layer) +- { +- std::istringstream iss(layer.GetParamAsString("impl")); +-#endif +- size_t ptr; +- iss >> ptr; +- cvLayer = (Layer*)ptr; +- +- std::vector > shapes; +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_2) +- strToShapes(node->params["internals"], shapes); +-#else +- strToShapes(layer.GetParamAsString("internals"), shapes); +-#endif +- internals.resize(shapes.size()); +- for (int i = 0; i < shapes.size(); ++i) +- internals[i].create(std::vector(shapes[i].begin(), shapes[i].end()), CV_32F); +- } +- +- ~InfEngineNgraphCustomLayer() +- { +- // nothing +- } +- +- virtual InferenceEngine::StatusCode execute(std::vector& inputs, +- std::vector& outputs, +- InferenceEngine::ResponseDesc *resp) noexcept +- { +- std::vector inpMats, outMats; +- infEngineBlobsToMats(inputs, inpMats); +- infEngineBlobsToMats(outputs, outMats); +- +- try +- { +- cvLayer->forward(inpMats, outMats, internals); +- return InferenceEngine::StatusCode::OK; +- } +- catch (...) +- { +- return InferenceEngine::StatusCode::GENERAL_ERROR; +- } +- } +- +- virtual InferenceEngine::StatusCode +- getSupportedConfigurations(std::vector& conf, +- InferenceEngine::ResponseDesc* resp) noexcept +- { +- std::vector inDataConfig; +- std::vector outDataConfig; +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_2) +- InferenceEngine::SizeVector order; +- for (int i = 0; i < node->get_input_size(); ++i) +- { +- InferenceEngine::DataConfig conf; +- auto shape = node->input_value(i).get_shape(); +- order.resize(shape.size()); +- std::iota(order.begin(), order.end(), 0); +- conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order}); +- inDataConfig.push_back(conf); +- } +- +- for (int i = 0; i < node->get_output_size(); ++i) +- { +- InferenceEngine::DataConfig conf; +- auto shape = node->output(i).get_shape(); +- order.resize(shape.size()); +- std::iota(order.begin(), order.end(), 0); +- conf.desc = InferenceEngine::TensorDesc(InferenceEngine::Precision::FP32, shape, {shape, order}); +- outDataConfig.push_back(conf); +- } +-#else +- for (auto& it : cnnLayer.insData) +- { +- InferenceEngine::DataConfig conf; +- conf.desc = it.lock()->getTensorDesc(); +- inDataConfig.push_back(conf); +- } +- +- for (auto& it : cnnLayer.outData) +- { +- InferenceEngine::DataConfig conf; +- conf.desc = it->getTensorDesc(); +- outDataConfig.push_back(conf); +- } +-#endif +- +- InferenceEngine::LayerConfig layerConfig; +- layerConfig.inConfs = inDataConfig; +- layerConfig.outConfs = outDataConfig; +- +- conf.push_back(layerConfig); +- return InferenceEngine::StatusCode::OK; +- } +- +- InferenceEngine::StatusCode init(InferenceEngine::LayerConfig& config, +- InferenceEngine::ResponseDesc *resp) noexcept +- { +- return InferenceEngine::StatusCode::OK; +- } +- +-private: +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_2) +- std::shared_ptr node; +-#else +- InferenceEngine::CNNLayer cnnLayer; +-#endif +- dnn::Layer* cvLayer; +- std::vector internals; +-}; +- +-#if INF_ENGINE_VER_MAJOR_LT(INF_ENGINE_RELEASE_2020_2) +-class InfEngineNgraphCustomLayerFactory : public InferenceEngine::ILayerImplFactory { +-public: +- explicit InfEngineNgraphCustomLayerFactory(const InferenceEngine::CNNLayer* layer) : cnnLayer(*layer) +- { +- // nothing +- } +- +- InferenceEngine::StatusCode +- getImplementations(std::vector& impls, +- InferenceEngine::ResponseDesc* resp) noexcept override +- { +- impls.push_back(std::make_shared(cnnLayer)); +- return InferenceEngine::StatusCode::OK; +- } +- +-private: +- InferenceEngine::CNNLayer cnnLayer; +-}; +-#endif +- +- +-class InfEngineNgraphExtension : public InferenceEngine::IExtension +-{ +-public: +- void Unload() noexcept override {} +- void Release() noexcept override { delete this; } +- void GetVersion(const InferenceEngine::Version*&) const noexcept override {} +- +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_2) +- std::vector getImplTypes(const std::shared_ptr& node) override { +- return {"CPU"}; +- } +- +- InferenceEngine::ILayerImpl::Ptr getImplementation(const std::shared_ptr& node, const std::string& implType) override { +- if (std::dynamic_pointer_cast(node) && implType == "CPU") { +- return std::make_shared(node); +- } +- return nullptr; +- } +-#else +- virtual void SetLogCallback(InferenceEngine::IErrorListener&) noexcept {} +- +- virtual InferenceEngine::StatusCode getPrimitiveTypes(char**&, unsigned int&, +- InferenceEngine::ResponseDesc*) noexcept +- { +- return InferenceEngine::StatusCode::OK; +- } +- +- InferenceEngine::StatusCode getFactoryFor(InferenceEngine::ILayerImplFactory*& factory, +- const InferenceEngine::CNNLayer* cnnLayer, +- InferenceEngine::ResponseDesc* resp) noexcept +- { +- if (cnnLayer->type != kOpenCVLayersType) +- return InferenceEngine::StatusCode::NOT_IMPLEMENTED; +- factory = new InfEngineNgraphCustomLayerFactory(cnnLayer); +- return InferenceEngine::StatusCode::OK; +- } +-#endif +-}; +- +-#endif // OpenVINO >= 2022.1 +- +-InfEngineNgraphNode::InfEngineNgraphNode(ngraph::Output&& _node) ++InfEngineNgraphNode::InfEngineNgraphNode(ov::Output&& _node) + : BackendNode(DNN_BACKEND_INFERENCE_ENGINE_NGRAPH), node(std::move(_node)) { + CV_Assert(node.get_node()); + CV_Assert(node.get_node_shared_ptr()); + } + +-InfEngineNgraphNode::InfEngineNgraphNode(const ngraph::Output& _node) ++InfEngineNgraphNode::InfEngineNgraphNode(const ov::Output& _node) + : BackendNode(DNN_BACKEND_INFERENCE_ENGINE_NGRAPH), node(_node) { + CV_Assert(node.get_node()); + CV_Assert(node.get_node_shared_ptr()); +@@ -400,27 +116,11 @@ InfEngineNgraphNode::InfEngineNgraphNode(const std::vector >& n + std::vector& outputs, std::vector& internals) + : BackendNode(DNN_BACKEND_INFERENCE_ENGINE_NGRAPH), cvLayer(cvLayer_) + { +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_3) +- ngraph::OutputVector inp_nodes; +-#else +- ngraph::NodeVector inp_nodes; +-#endif ++ ov::OutputVector inp_nodes; + for (const auto& node : nodes) + inp_nodes.emplace_back(node.dynamicCast()->node); + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + node = std::make_shared(inp_nodes, cvLayer, outputs, internals); +-#else +- std::ostringstream oss; +- oss << (size_t)cvLayer.get(); +- std::map params = { +- {"impl", oss.str()}, +- {"outputs", shapesToStr(outputs)}, +- {"internals", shapesToStr(internals)} +- }; +- node = std::make_shared(inp_nodes, params); +-#endif +- + CV_Assert(!cvLayer->name.empty()); + setName(cvLayer->name); + } +@@ -436,7 +136,7 @@ InfEngineNgraphNet::InfEngineNgraphNet(detail::NetImplBase& netImpl) + device_name = "CPU"; + } + +-InfEngineNgraphNet::InfEngineNgraphNet(detail::NetImplBase& netImpl, InferenceEngine::CNNNetwork& net) ++InfEngineNgraphNet::InfEngineNgraphNet(detail::NetImplBase& netImpl, std::shared_ptr& net) + : netImpl_(netImpl) + , cnn(net) + { +@@ -455,64 +155,31 @@ void InfEngineNgraphNet::createNet(Target targetId) { + if (!hasNetOwner) + { + CV_Assert(!requestedOutputs.empty()); +- ngraph::ResultVector outs; ++ ov::ResultVector outs; + + for (auto output_node_it = requestedOutputs.begin(); output_node_it != requestedOutputs.end(); ++output_node_it) + { + CV_LOG_DEBUG(NULL, "DNN/NGRAPH: Add 'Result' output: " << output_node_it->first); + CV_Assert(output_node_it->second); +- auto out = std::make_shared(output_node_it->second->node); +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) ++ auto out = std::make_shared(output_node_it->second->node); + out->set_friendly_name(output_node_it->first + (output_node_it->second->node.get_node()->get_output_size() == 1 ? "" : ".0")); +-#endif + outs.push_back(out); + } + CV_Assert_N(!inputs_vec.empty(), !outs.empty()); +- ngraph_function = std::make_shared(outs, inputs_vec); ++ ngraph_function = std::make_shared(outs, inputs_vec); + init(targetId); + } + } + +-#if INF_ENGINE_VER_MAJOR_LT(INF_ENGINE_RELEASE_2022_1) +-static inline +-InferenceEngine::Layout estimateLayout(size_t dims); +-#endif +- + void InfEngineNgraphNet::init(Target targetId) + { + if (!hasNetOwner) + { + if (targetId == DNN_TARGET_OPENCL_FP16) + { +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + ov::pass::ConvertFP32ToFP16().run_on_model(ngraph_function); +-#else +- auto nodes = ngraph_function->get_ordered_ops(); +- for (auto& node : nodes) +- { +- auto parameter = std::dynamic_pointer_cast(node); +- if (parameter && parameter->get_element_type() == ngraph::element::f32) +- { +- parameter->set_element_type(ngraph::element::f16); +- } +- auto constant = std::dynamic_pointer_cast(node); +- if (constant && constant->get_element_type() == ngraph::element::f32) +- { +- const float* floatsData = constant->get_data_ptr(); +- size_t total = ngraph::shape_size(constant->get_shape()); +- Mat floats(1, total, CV_32F, (void*)floatsData); +- Mat halfs; +- cv::convertFp16(floats, halfs); +- +- auto new_const = std::make_shared(ngraph::element::f16, constant->get_shape(), halfs.data); +- new_const->set_friendly_name(constant->get_friendly_name()); +- ngraph::replace_node(constant, new_const); +- } +- } +- ngraph_function->validate_nodes_and_infer_types(); +-#endif // OpenVINO >= 2022.1 + } +- cnn = InferenceEngine::CNNNetwork(ngraph_function); ++ cnn = ngraph_function; + + if (DNN_IE_SERIALIZE) + { +@@ -520,7 +187,7 @@ void InfEngineNgraphNet::init(Target targetId) + std::string dumpFileNameBase = netImpl_.getDumpFileNameBase(); + try + { +- cnn.serialize(dumpFileNameBase + "_ngraph.xml", dumpFileNameBase + "_ngraph.bin"); ++ ov::pass::Serialize(dumpFileNameBase + "_ngraph.xml", dumpFileNameBase + "_ngraph.bin").run_on_model(cnn); + } + catch (const std::exception& e) + { +@@ -558,11 +225,9 @@ void InfEngineNgraphNet::init(Target targetId) + CV_Error(Error::StsNotImplemented, "Unknown target"); + }; + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) +- auto model = cnn.getFunction(); +- ov::preprocess::PrePostProcessor ppp(model); ++ ov::preprocess::PrePostProcessor ppp(cnn); + int i = 0; +- for (const auto& inp : model->inputs()) { // TODO: not sure why but ngraph_function->inputs() here causes segfault. ++ for (const auto& inp : cnn->inputs()) { // TODO: not sure why but ngraph_function->inputs() here causes segfault. + const std::string& name = inp.get_node()->get_friendly_name(); + auto blobIt = allBlobs.find(name); + CV_Assert(blobIt != allBlobs.end()); +@@ -574,7 +239,7 @@ void InfEngineNgraphNet::init(Target targetId) + } + + i = 0; +- for (const auto& it : model->outputs()) ++ for (const auto& it : cnn->outputs()) + { + const std::string& name = it.get_node()->get_friendly_name(); + auto blobIt = allBlobs.find(name); +@@ -595,47 +260,21 @@ void InfEngineNgraphNet::init(Target targetId) + + ppp.build(); + +-#else +- +- for (const auto& it : cnn.getInputsInfo()) +- { +- const std::string& name = it.first; +- auto blobIt = allBlobs.find(name); +- CV_Assert(blobIt != allBlobs.end()); +- it.second->setPrecision(blobIt->second->getTensorDesc().getPrecision()); +- } +- +- for (const auto& it : cnn.getOutputsInfo()) +- { +- const std::string& name = it.first; +- auto blobIt = allBlobs.find(name); +- CV_Assert(blobIt != allBlobs.end()); +- InferenceEngine::TensorDesc& desc = blobIt->second->getTensorDesc(); +- +- auto outShape = it.second->getDims(); +- if (outShape != desc.getDims()) { +- desc.reshape(outShape, estimateLayout(outShape.size())); +- } +- +- it.second->setPrecision(blobIt->second->getTensorDesc().getPrecision()); // Should be always FP32 +- } +-#endif // OpenVINO >= 2022.1 +- + initPlugin(cnn); + } + +-ngraph::ParameterVector InfEngineNgraphNet::setInputs(const std::vector& inputs, ++ov::ParameterVector InfEngineNgraphNet::setInputs(const std::vector& inputs, + const std::vector& names) { + CV_Assert_N(inputs.size() == names.size()); +- ngraph::ParameterVector current_inp; ++ ov::ParameterVector current_inp; + for (size_t i = 0; i < inputs.size(); i++) + { + std::vector shape = getShape(inputs[i]); +- auto inp = std::make_shared(ngraph::element::f32, ngraph::Shape(shape)); ++ auto inp = std::make_shared(ov::element::f32, ov::Shape(shape)); + inp->set_friendly_name(names[i]); + + auto it = std::find_if(inputs_vec.begin(), inputs_vec.end(), +- [&inp](const std::shared_ptr& a) { ++ [&inp](const std::shared_ptr& a) { + return a->get_friendly_name() == inp->get_friendly_name(); + }); + if (it == inputs_vec.end()) { +@@ -649,14 +288,14 @@ ngraph::ParameterVector InfEngineNgraphNet::setInputs(const std::vector + } + + +-void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net) ++void InfEngineNgraphNet::initPlugin(std::shared_ptr& net) + { + CV_Assert(!isInitialized()); + + try + { + AutoLock lock(getInitializationMutex()); +- InferenceEngine::Core& ie = getCore(device_name); ++ ov::Core& ie = getCore(device_name); + { + isInit = true; + std::vector candidates; +@@ -671,18 +310,7 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net) + const std::string& libName = candidates[i]; + try + { +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + ie.add_extension(libName); +-#else +- InferenceEngine::IExtensionPtr extension = +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4) +- std::make_shared(libName); +-#else +- InferenceEngine::make_so_pointer(libName); +-#endif +- +- ie.AddExtension(extension, "CPU"); +-#endif + CV_LOG_INFO(NULL, "DNN-IE: Loaded extension plugin: " << libName); + found = true; + break; +@@ -693,30 +321,11 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net) + { + CV_LOG_WARNING(NULL, "DNN-IE: Can't load extension plugin (extra layers for some networks). Specify path via OPENCV_DNN_IE_EXTRA_PLUGIN_PATH parameter"); + } +-#if INF_ENGINE_VER_MAJOR_LT(INF_ENGINE_RELEASE_2022_1) +- // Some of networks can work without a library of extra layers. +- // OpenCV fallbacks as extensions. +- try +- { +- ie.AddExtension(std::make_shared(), "CPU"); +- } +- catch(const std::exception& e) +- { +- CV_LOG_INFO(NULL, "DNN-IE: Can't register OpenCV custom layers nGraph extension: " << e.what()); +- } +-#endif // OpenVINO < 2022.1 + #ifndef _WIN32 + // Limit the number of CPU threads. + if (device_name == "CPU") +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + ie.set_property(device_name, ov::inference_num_threads(getNumThreads())); +-#else +- ie.SetConfig({{ +- InferenceEngine::PluginConfigParams::KEY_CPU_THREADS_NUM, format("%d", getNumThreads()), +- }}, device_name); +-#endif // OpenVINO >= 2022.1 + #endif +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_2) + if (device_name.find("GPU") == 0) + { + #if OPENCV_HAVE_FILESYSTEM_SUPPORT +@@ -727,24 +336,13 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net) + if (!cache_path.empty() && cache_path != "disabled") + { + CV_LOG_INFO(NULL, "OpenCV/nGraph: using GPU kernels cache: " << cache_path); +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + ie.set_property(device_name, ov::cache_dir(cache_path)); +-#else +- ie.SetConfig({{ +- InferenceEngine::PluginConfigParams::KEY_CACHE_DIR, cache_path, +- }}, device_name); +-#endif // OpenVINO >= 2022.1 + } + } +-#endif + } +- std::map config; ++ ov::AnyMap config; + if (device_name == "MYRIAD" || device_name == "HDDL") { +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) + config.emplace("MYRIAD_DETECT_NETWORK_BATCH", "NO"); +-#else +- config.emplace("VPU_DETECT_NETWORK_BATCH", "NO"); +-#endif + } + + bool isHetero = device_name == "FPGA"; +@@ -752,7 +350,7 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net) + // We do not check IR models because they can be with version less than IRv10 + if (!isHetero && device_name != "CPU" && !hasNetOwner) + { +- for (auto& node : net.getFunction()->get_ops()) ++ for (auto& node : net->get_ops()) + { + if (node->description() == kOpenCVLayersType) + { +@@ -764,7 +362,7 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net) + + std::string ieDevice = isHetero ? ("HETERO:" + device_name + ",CPU") : device_name; + CV_LOG_INFO(NULL, "DNN/IE: Calling LoadNetwork(device=" << ieDevice << ")..."); +- netExec = ie.LoadNetwork(net, ieDevice, config); ++ netExec = ie.compile_model(net, ieDevice, config); + } + catch (const std::exception& ex) + { +@@ -782,14 +380,13 @@ bool NgraphBackendLayer::getMemoryShapes(const std::vector &inputs, + std::vector &outputs, + std::vector &internals) const + { +- auto ngraphFunction = t_net.getFunction(); + bool equal_flag = true; +- std::map > inShapes; ++ std::map inShapes; + int i = 0; +- for (const auto& inp : ngraphFunction->get_parameters()) ++ for (const auto& inp : t_net->get_parameters()) + { +- std::vector oldShape = inp->get_shape(); +- std::vector newShape(inputs[i].begin(), inputs[i].end()); ++ ov::Shape oldShape = inp->get_shape(); ++ ov::Shape newShape(inputs[i].begin(), inputs[i].end()); + inShapes.insert({inp->get_friendly_name(), newShape}); + if (oldShape != newShape) + { +@@ -800,21 +397,17 @@ bool NgraphBackendLayer::getMemoryShapes(const std::vector &inputs, + + if (!equal_flag) + { +- InferenceEngine::CNNNetwork curr_t_net(t_net); +- curr_t_net.reshape(inShapes); ++ std::shared_ptr curr_t_net(t_net); ++ curr_t_net->reshape(inShapes); + } +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + std::vector dims; +- for (const auto& it : ngraphFunction->outputs()) { ++ for (const auto& it : t_net->outputs()) { + if (it.get_node()->get_friendly_name() == name) { + dims = it.get_partial_shape().get_max_shape(); + } + } + if (dims.empty()) + CV_Error(Error::StsError, format("Unable find result with name %s", name.c_str())); +-#else +- std::vector dims = t_net.getOutputsInfo()[name]->getDims(); +-#endif + outputs.push_back(MatShape(dims.begin(), dims.end())); + return false; + } +@@ -832,8 +425,6 @@ void NgraphBackendLayer::forward(InputArrayOfArrays inputs, OutputArrayOfArrays + CV_Error(Error::StsInternal, "Choose Inference Engine as a preferable backend."); + } + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) +- + ov::Tensor wrapToNgraphBlob(const Mat& m) { + std::vector shape = getShape(m); + if (m.type() == CV_32F) +@@ -848,60 +439,6 @@ ov::Tensor wrapToNgraphBlob(const Mat& m) { + CV_Error(Error::StsNotImplemented, format("Unsupported data type %s", typeToString(m.type()).c_str())); + } + +-#else +- +-static InferenceEngine::Layout estimateLayout(int dims) +-{ +- if (dims == 4) +- return InferenceEngine::Layout::NCHW; +- else if (dims == 3) +- return InferenceEngine::Layout::CHW; +- else if (dims == 2) +- return InferenceEngine::Layout::NC; +- else if (dims == 1) +- return InferenceEngine::Layout::C; +- else if (dims == 5) +- return InferenceEngine::Layout::NCDHW; +- else +- return InferenceEngine::Layout::ANY; +-} +-static inline +-InferenceEngine::Layout estimateLayout(size_t dims) +-{ +- return estimateLayout((int)dims); +-} +- +-static inline +-InferenceEngine::Layout estimateLayout(const Mat& m) +-{ +- return estimateLayout(m.dims); +-} +- +-InferenceEngine::Blob::Ptr wrapToNgraphBlob(const Mat& m, const std::vector& shape, +- InferenceEngine::Layout layout) +-{ +- if (m.type() == CV_32F) +- return InferenceEngine::make_shared_blob( +- {InferenceEngine::Precision::FP32, shape, layout}, (float*)m.data); +- else if (m.type() == CV_8U) +- return InferenceEngine::make_shared_blob( +- {InferenceEngine::Precision::U8, shape, layout}, (uint8_t*)m.data); +- else if (m.type() == CV_32SC1) +- return InferenceEngine::make_shared_blob( +- {InferenceEngine::Precision::I32, shape, layout}, (int32_t*)m.data); +- else +- CV_Error(Error::StsNotImplemented, format("Unsupported data type %s", typeToString(m.type()).c_str())); +-} +- +-InferenceEngine::Blob::Ptr wrapToNgraphBlob(const Mat& m, InferenceEngine::Layout layout) +-{ +- std::vector shape = getShape(m); +- return wrapToNgraphBlob(m, shape, layout); +-} +- +-InferenceEngine::Blob::Ptr wrapToNgraphBlob(const Mat& m) { return wrapToNgraphBlob(m, estimateLayout(m)); } +- +-#endif // OpenVINO >= 2022.1 + + NgraphBackendWrapper::NgraphBackendWrapper(int targetId, const cv::Mat& m) + : BackendWrapper(DNN_BACKEND_INFERENCE_ENGINE_NGRAPH, targetId) +@@ -941,36 +478,10 @@ void NgraphBackendWrapper::setHostDirty() + //CV_Error(Error::StsNotImplemented, ""); + } + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + ov::Tensor copyBlob(const ov::Tensor& blob) + { + return ov::Tensor(blob.get_element_type(), blob.get_shape()); + } +-#else +-InferenceEngine::Blob::Ptr copyBlob(const InferenceEngine::Blob::Ptr& blob) +-{ +- InferenceEngine::Blob::Ptr copy; +- auto description = blob->getTensorDesc(); +- InferenceEngine::Precision precision = description.getPrecision(); +- if (precision == InferenceEngine::Precision::FP32) +- { +- copy = InferenceEngine::make_shared_blob(description); +- } +- else if (precision == InferenceEngine::Precision::U8) +- { +- copy = InferenceEngine::make_shared_blob(description); +- } +- else +- { +- std::ostringstream msg; +- msg << precision; +- CV_Error_(Error::StsNotImplemented, ("Unsupported blob precision: %s", msg.str().c_str())); +- } +- copy->allocate(); +- return copy; +-} +- +-#endif // OpenVINO < 2022.1 + + void InfEngineNgraphNet::reset() + { +@@ -1022,7 +533,7 @@ void InfEngineNgraphNet::forward(const std::vector >& outBlo + reqWrapper = Ptr(new NgraphReqWrapper()); + try + { +- reqWrapper->req = netExec.CreateInferRequest(); ++ reqWrapper->req = netExec.create_infer_request(); + } + catch (const std::exception& ex) + { +@@ -1030,7 +541,6 @@ void InfEngineNgraphNet::forward(const std::vector >& outBlo + } + infRequests.push_back(reqWrapper); + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + int i = 0; + for (const auto& it : netExec.inputs()) + { +@@ -1048,27 +558,7 @@ void InfEngineNgraphNet::forward(const std::vector >& outBlo + CV_Assert(blobIt != allBlobs.end()); + reqWrapper->req.set_output_tensor(i++, isAsync ? copyBlob(blobIt->second) : blobIt->second); + } +-#else +- InferenceEngine::BlobMap inpBlobs, outBlobs; +- for (const auto& it : cnn.getInputsInfo()) +- { +- const std::string& name = it.first; +- auto blobIt = allBlobs.find(name); +- CV_Assert(blobIt != allBlobs.end()); +- inpBlobs[name] = isAsync ? copyBlob(blobIt->second) : blobIt->second; +- } +- for (const auto& it : cnn.getOutputsInfo()) +- { +- const std::string& name = it.first; +- auto blobIt = allBlobs.find(name); +- CV_Assert(blobIt != allBlobs.end()); +- outBlobs[name] = isAsync ? copyBlob(blobIt->second) : blobIt->second; +- } +- reqWrapper->req.SetInput(inpBlobs); +- reqWrapper->req.SetOutput(outBlobs); +-#endif + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + if (isAsync) { + bool* isReady = &reqWrapper->isReady; + auto* promises = &reqWrapper->outProms; +@@ -1112,86 +602,13 @@ void InfEngineNgraphNet::forward(const std::vector >& outBlo + *isReady = true; + }); + } +-#else // OpenVINO >= 2022.1 +- +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4) +- InferenceEngine::InferRequest infRequest = reqWrapper->req; +- NgraphReqWrapper* wrapperPtr = reqWrapper.get(); +- CV_Assert(wrapperPtr && "Internal error"); +-#else +- InferenceEngine::IInferRequest::Ptr infRequestPtr = reqWrapper->req; +- CV_Assert(infRequestPtr); +- InferenceEngine::IInferRequest& infRequest = *infRequestPtr.get(); +- infRequest.SetUserData(reqWrapper.get(), 0); +-#endif +- +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4) +- // do NOT capture 'reqWrapper' (smart ptr) in the lambda callback +- infRequest.SetCompletionCallback>( +- [wrapperPtr](InferenceEngine::InferRequest /*request*/, InferenceEngine::StatusCode status) +-#else +- infRequest.SetCompletionCallback( +- [](InferenceEngine::IInferRequest::Ptr requestPtr, InferenceEngine::StatusCode status) +-#endif +- { +- CV_LOG_DEBUG(NULL, "DNN(nGraph): completionCallback(" << (int)status << ")"); +-#if !INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_4) +- CV_Assert(requestPtr); +- InferenceEngine::IInferRequest& request = *requestPtr.get(); +- +- NgraphReqWrapper* wrapperPtr; +- request.GetUserData((void**)&wrapperPtr, 0); +- CV_Assert(wrapperPtr && "Internal error"); +-#endif +- NgraphReqWrapper& wrapper = *wrapperPtr; +- +- size_t processedOutputs = 0; +- try +- { +- for (; processedOutputs < wrapper.outProms.size(); ++processedOutputs) +- { +- const std::string& name = wrapper.outsNames[processedOutputs]; +- Mat m = infEngineBlobToMat(wrapper.req.GetBlob(name)); +- +- try +- { +- CV_Assert(status == InferenceEngine::StatusCode::OK); +- wrapper.outProms[processedOutputs].setValue(m.clone()); +- } +- catch (...) +- { +- try { +- wrapper.outProms[processedOutputs].setException(std::current_exception()); +- } catch(...) { +- CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation"); +- } +- } +- } +- } +- catch (...) +- { +- std::exception_ptr e = std::current_exception(); +- for (; processedOutputs < wrapper.outProms.size(); ++processedOutputs) +- { +- try { +- wrapper.outProms[processedOutputs].setException(e); +- } catch(...) { +- CV_LOG_ERROR(NULL, "DNN: Exception occurred during async inference exception propagation"); +- } +- } +- } +- wrapper.isReady = true; +- } +- ); +-#endif // OpenVINO >= 2022.1 + } + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + if (isAsync) + { + // Copy actual data to infer request's input blobs. + int i = 0; +- for (const auto& it : cnn.getFunction()->get_parameters()) ++ for (const auto& it : cnn->get_parameters()) + { + const std::string& name = it->get_friendly_name(); + auto blobIt = allBlobs.find(name); +@@ -1210,54 +627,30 @@ void InfEngineNgraphNet::forward(const std::vector >& outBlo + { + reqWrapper->req.infer(); + } +-#else +- if (isAsync) +- { +- // Copy actual data to infer request's input blobs. +- for (const auto& it : cnn.getInputsInfo()) +- { +- const std::string& name = it.first; +- auto blobIt = allBlobs.find(name); +- Mat srcMat = infEngineBlobToMat(blobIt->second); +- Mat dstMat = infEngineBlobToMat(reqWrapper->req.GetBlob(name)); +- srcMat.copyTo(dstMat); +- } +- +- // Set promises to output blobs wrappers. +- reqWrapper->makePromises(outBlobsWrappers); +- +- reqWrapper->isReady = false; +- reqWrapper->req.StartAsync(); +- } +- else +- { +- reqWrapper->req.Infer(); +- } +-#endif // OpenVINO >= 2022.1 + } + +-ngraph::Output ngraphQuantize(ngraph::Output input, float output_sc, float output_zp) { ++ov::Output ngraphQuantize(ov::Output input, float output_sc, float output_zp) { + float outLow = -128, outHigh = 127; + float inpLow = output_sc * (outLow - output_zp); + float inpHigh = output_sc * (outHigh - output_zp); +- return std::make_shared(input, +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &inpLow), +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &inpHigh), +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &outLow), +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &outHigh), ++ return std::make_shared(input, ++ std::make_shared(ov::element::f32, ov::Shape{1}, &inpLow), ++ std::make_shared(ov::element::f32, ov::Shape{1}, &inpHigh), ++ std::make_shared(ov::element::f32, ov::Shape{1}, &outLow), ++ std::make_shared(ov::element::f32, ov::Shape{1}, &outHigh), + 256 // levels + ); + } + +-ngraph::Output ngraphDequantize(ngraph::Output input, float input_sc, float input_zp) { ++ov::Output ngraphDequantize(ov::Output input, float input_sc, float input_zp) { + float inpLow = -128, inpHigh = 127; + float outLow = input_sc * (inpLow - input_zp); + float outHigh = input_sc * (inpHigh - input_zp); +- return std::make_shared(input, +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &inpLow), +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &inpHigh), +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &outLow), +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &outHigh), ++ return std::make_shared(input, ++ std::make_shared(ov::element::f32, ov::Shape{1}, &inpLow), ++ std::make_shared(ov::element::f32, ov::Shape{1}, &inpHigh), ++ std::make_shared(ov::element::f32, ov::Shape{1}, &outLow), ++ std::make_shared(ov::element::f32, ov::Shape{1}, &outHigh), + 256 // levels + ); + } +diff --git a/modules/dnn/src/ie_ngraph.hpp b/modules/dnn/src/ie_ngraph.hpp +index 8672f1a3c2..19e07d62ac 100644 +--- a/modules/dnn/src/ie_ngraph.hpp ++++ b/modules/dnn/src/ie_ngraph.hpp +@@ -17,7 +17,8 @@ + #pragma warning(disable : 4245) + #pragma warning(disable : 4268) + #endif +-#include ++#include ++#include + #ifdef _MSC_VER + #pragma warning(pop) + #endif +@@ -30,12 +31,11 @@ namespace cv { namespace dnn { + + class InfEngineNgraphNode; + +- + class InfEngineNgraphNet + { + public: + InfEngineNgraphNet(detail::NetImplBase& netImpl); +- InfEngineNgraphNet(detail::NetImplBase& netImpl, InferenceEngine::CNNNetwork& net); ++ InfEngineNgraphNet(detail::NetImplBase& netImpl, std::shared_ptr& net); + + void addOutput(const Ptr& node); + +@@ -44,8 +44,8 @@ public: + + void forward(const std::vector >& outBlobsWrappers, bool isAsync); + +- void initPlugin(InferenceEngine::CNNNetwork& net); +- ngraph::ParameterVector setInputs(const std::vector& inputs, const std::vector& names); ++ void initPlugin(std::shared_ptr& net); ++ ov::ParameterVector setInputs(const std::vector& inputs, const std::vector& names); + + void addBlobs(const std::vector >& ptrs); + +@@ -56,15 +56,11 @@ public: + //private: + detail::NetImplBase& netImpl_; + +- ngraph::ParameterVector inputs_vec; +- std::shared_ptr ngraph_function; ++ ov::ParameterVector inputs_vec; ++ std::shared_ptr ngraph_function; + +- InferenceEngine::ExecutableNetwork netExec; +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) ++ ov::CompiledModel netExec; + std::map allBlobs; +-#else +- InferenceEngine::BlobMap allBlobs; +-#endif + std::string device_name; + bool isInit = false; + +@@ -74,14 +70,14 @@ public: + + void makePromises(const std::vector >& outs); + +- InferenceEngine::InferRequest req; ++ ov::InferRequest req; + std::vector outProms; + std::vector outsNames; + bool isReady; + }; + std::vector > infRequests; + +- InferenceEngine::CNNNetwork cnn; ++ std::shared_ptr cnn; + bool hasNetOwner; + std::unordered_map requestedOutputs; + }; +@@ -93,13 +89,13 @@ public: + std::vector& inputs, std::vector& outputs, + std::vector& internals); + +- InfEngineNgraphNode(ngraph::Output&& _node); +- InfEngineNgraphNode(const ngraph::Output& _node); ++ InfEngineNgraphNode(ov::Output&& _node); ++ InfEngineNgraphNode(const ov::Output& _node); + + void setName(const std::string& name); + + // Inference Engine network object that allows to obtain the outputs of this layer. +- ngraph::Output node; ++ ov::Output node; + Ptr net; + Ptr cvLayer; + }; +@@ -118,11 +114,7 @@ public: + + Mat* host; + std::string name; +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + ov::Tensor blob; +-#else +- InferenceEngine::Blob::Ptr blob; +-#endif + AsyncArray futureMat; + }; + +@@ -132,7 +124,7 @@ public: + class NgraphBackendLayer : public Layer + { + public: +- NgraphBackendLayer(const InferenceEngine::CNNNetwork &t_net_) : t_net(t_net_) {}; ++ NgraphBackendLayer(const std::shared_ptr &t_net_) : t_net(t_net_) {}; + + virtual bool getMemoryShapes(const std::vector &inputs, + const int requiredOutputs, +@@ -145,11 +137,11 @@ public: + virtual bool supportBackend(int backendId) CV_OVERRIDE; + + private: +- InferenceEngine::CNNNetwork t_net; ++ std::shared_ptr t_net; + }; + +-ngraph::Output ngraphQuantize(ngraph::Output input, float output_sc, float output_zp); +-ngraph::Output ngraphDequantize(ngraph::Output input, float input_sc, float input_zp); ++ov::Output ngraphQuantize(ov::Output input, float output_sc, float output_zp); ++ov::Output ngraphDequantize(ov::Output input, float input_sc, float input_zp); + + #endif // HAVE_DNN_NGRAPH + +diff --git a/modules/dnn/src/int8layers/batch_norm_layer.cpp b/modules/dnn/src/int8layers/batch_norm_layer.cpp +index 7ef169deea..3fbf8cd191 100644 +--- a/modules/dnn/src/int8layers/batch_norm_layer.cpp ++++ b/modules/dnn/src/int8layers/batch_norm_layer.cpp +@@ -7,8 +7,6 @@ + #include "../op_timvx.hpp" + #include "../ie_ngraph.hpp" + +-#include +- + namespace cv + { + namespace dnn +@@ -250,11 +248,11 @@ public: + std::vector shape(input.get_shape().size(), 1); + shape[1] = origin_weights.total(); + +- ngraph::Output res; +- auto ieWeights = std::make_shared(ngraph::element::f32, shape, origin_weights.data); +- auto ieBias = std::make_shared(ngraph::element::f32, shape, origin_bias.data); +- res = std::make_shared(input, ieWeights); +- res = std::make_shared(res, ieBias); ++ ov::Output res; ++ auto ieWeights = std::make_shared(ov::element::f32, shape, origin_weights.data); ++ auto ieBias = std::make_shared(ov::element::f32, shape, origin_bias.data); ++ res = std::make_shared(input, ieWeights); ++ res = std::make_shared(res, ieBias); + + res = ngraphQuantize(res, output_sc, output_zp); + return new InfEngineNgraphNode(res); +diff --git a/modules/dnn/src/int8layers/convolution_layer.cpp b/modules/dnn/src/int8layers/convolution_layer.cpp +index ba9b31fe35..2695cb6d56 100644 +--- a/modules/dnn/src/int8layers/convolution_layer.cpp ++++ b/modules/dnn/src/int8layers/convolution_layer.cpp +@@ -573,8 +573,8 @@ public: + auto ieInpNode = nodes[0].dynamicCast()->node; + std::vector dims = ieInpNode.get_shape(); + CV_Check(dims.size(), dims.size() >= 3 && dims.size() <= 5, ""); +- CV_Assert(ieInpNode.get_element_type() == ngraph::element::f32); +- ngraph::Output ieWeights; ++ CV_Assert(ieInpNode.get_element_type() == ov::element::f32); ++ ov::Output ieWeights; + if (nodes.size() > 1) + ieWeights = nodes[1].dynamicCast()->node; + const int inpCn = dims[1]; +@@ -592,18 +592,18 @@ public: + + if (nodes.size() == 1) + { +- ieWeights = std::make_shared(ngraph::element::i8, kernel_shape, blobs[0].data); ++ ieWeights = std::make_shared(ov::element::i8, kernel_shape, blobs[0].data); + } + else + { +- auto shape = std::make_shared(ngraph::element::i64, +- ngraph::Shape{kernel_shape.size()}, std::vector(kernel_shape.begin(), kernel_shape.end())); +- ieWeights = std::make_shared(ieWeights, shape, true); ++ auto shape = std::make_shared(ov::element::i64, ++ ov::Shape{kernel_shape.size()}, std::vector(kernel_shape.begin(), kernel_shape.end())); ++ ieWeights = std::make_shared(ieWeights, shape, true); + } + +- ngraph::op::PadType pad_type = ngraph::op::PadType::EXPLICIT; ++ ov::op::PadType pad_type = ov::op::PadType::EXPLICIT; + if (!padMode.empty()) +- pad_type = padMode == "VALID" ? ngraph::op::PadType::VALID : ngraph::op::PadType::SAME_UPPER; ++ pad_type = padMode == "VALID" ? ov::op::PadType::VALID : ov::op::PadType::SAME_UPPER; + + ieInpNode = ngraphDequantize(ieInpNode, input_sc, input_zp); + +@@ -627,31 +627,31 @@ public: + outLows[i] = low * outputMultiplier[i] * output_sc / input_sc; + outHighs[i] = high * outputMultiplier[i] * output_sc / input_sc; + } +- ieWeights = std::make_shared(ieWeights, ngraph::element::f32); +- ieWeights = std::make_shared(ieWeights, +- std::make_shared(ngraph::element::f32, quantShape, inpLows.data()), +- std::make_shared(ngraph::element::f32, quantShape, inpHighs.data()), +- std::make_shared(ngraph::element::f32, quantShape, outLows.data()), +- std::make_shared(ngraph::element::f32, quantShape, outHighs.data()), ++ ieWeights = std::make_shared(ieWeights, ov::element::f32); ++ ieWeights = std::make_shared(ieWeights, ++ std::make_shared(ov::element::f32, quantShape, inpLows.data()), ++ std::make_shared(ov::element::f32, quantShape, inpHighs.data()), ++ std::make_shared(ov::element::f32, quantShape, outLows.data()), ++ std::make_shared(ov::element::f32, quantShape, outHighs.data()), + 256 // levels + ); + +- ngraph::Output conv_node; ++ ov::Output conv_node; + if (group != 1) { +- conv_node = std::make_shared( ++ conv_node = std::make_shared( + ieInpNode, ieWeights, +- ngraph::Strides(strides), +- ngraph::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), +- ngraph::CoordinateDiff(std::vector(pads_end.begin(), pads_end.end())), +- ngraph::Strides(dilations), ++ ov::Strides(strides), ++ ov::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), ++ ov::CoordinateDiff(std::vector(pads_end.begin(), pads_end.end())), ++ ov::Strides(dilations), + pad_type); + } else { +- conv_node = std::make_shared( ++ conv_node = std::make_shared( + ieInpNode, ieWeights, +- ngraph::Strides(strides), +- ngraph::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), +- ngraph::CoordinateDiff(std::vector(pads_end.begin(), pads_end.end())), +- ngraph::Strides(dilations), ++ ov::Strides(strides), ++ ov::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), ++ ov::CoordinateDiff(std::vector(pads_end.begin(), pads_end.end())), ++ ov::Strides(dilations), + pad_type); + } + +@@ -659,12 +659,12 @@ public: + shape[1] = conv_node.get_shape()[1]; + if (biasvec.size() || nodes.size() == 3) + { +- std::shared_ptr bias; ++ std::shared_ptr bias; + if (nodes.size() == 3) + { +- auto bias_shape = std::make_shared(ngraph::element::i64, +- ngraph::Shape{shape.size()}, std::vector(shape.begin(), shape.end())); +- bias = std::make_shared(nodes[2].dynamicCast()->node, bias_shape, true); ++ auto bias_shape = std::make_shared(ov::element::i64, ++ ov::Shape{shape.size()}, std::vector(shape.begin(), shape.end())); ++ bias = std::make_shared(nodes[2].dynamicCast()->node, bias_shape, true); + } + else + { +@@ -672,9 +672,9 @@ public: + for (int i = 0; i < numOutput; ++i) { + ovBias[i] = (biasvec[i] + input_zp * cv::sum(blobs[0].row(i))[0]) * outputMultiplier[i] * output_sc; + } +- bias = std::make_shared(ngraph::element::f32, ngraph::Shape(shape), ovBias.data()); ++ bias = std::make_shared(ov::element::f32, ov::Shape(shape), ovBias.data()); + } +- conv_node = std::make_shared(conv_node, bias, ngraph::op::AutoBroadcastType::NUMPY); ++ conv_node = std::make_shared(conv_node, bias, ov::op::AutoBroadcastType::NUMPY); + } + + conv_node = ngraphQuantize(conv_node, output_sc, output_zp); +diff --git a/modules/dnn/src/int8layers/elementwise_layers.cpp b/modules/dnn/src/int8layers/elementwise_layers.cpp +index 2f40a4039f..f522efa0c1 100644 +--- a/modules/dnn/src/int8layers/elementwise_layers.cpp ++++ b/modules/dnn/src/int8layers/elementwise_layers.cpp +@@ -253,24 +253,26 @@ public: + + input = ngraphDequantize(input, input_sc, input_zp); + +- ngraph::Output res; ++ ov::Output res; + if (type == "ReLU6Int8") { +- res = std::make_shared(input, 0.0f, 6.0f); ++ res = std::make_shared(input, 0.0f, 6.0f); + } else if (type == "ReLUInt8") { + if (slope) { +- auto param = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &slope); +- res = std::make_shared(input, param); ++ auto param = std::make_shared(ov::element::f32, ov::Shape{1}, &slope); ++ res = std::make_shared(input, param); + } else { +- res = std::make_shared(input); ++ res = std::make_shared(input); + } + } else if (type == "ELUInt8") { +- res = std::make_shared(input, 1.0f); ++ res = std::make_shared(input, 1.0f); + } else if (type == "MishInt8") { +- res = std::make_shared(input); ++ res = std::make_shared(input); ++ } else if (type == "HardSwishInt8") { ++ res = std::make_shared(input); + } else if (type == "AbsValInt8") { +- res = std::make_shared(input); ++ res = std::make_shared(input); + } else if (type == "SigmoidInt8") { +- res = std::make_shared(input); ++ res = std::make_shared(input); + } else { + CV_Error(Error::StsNotImplemented, type + " activation with OpenVINO"); + } +diff --git a/modules/dnn/src/int8layers/eltwise_layer.cpp b/modules/dnn/src/int8layers/eltwise_layer.cpp +index a3bb6ec2d6..214d11525a 100644 +--- a/modules/dnn/src/int8layers/eltwise_layer.cpp ++++ b/modules/dnn/src/int8layers/eltwise_layer.cpp +@@ -375,7 +375,7 @@ public: + const std::vector >& nodes) CV_OVERRIDE + { + CV_Assert(nodes.size() >= 2); +- std::vector> ieInpNodes(nodes.size()); ++ std::vector> ieInpNodes(nodes.size()); + for (size_t i = 0; i < nodes.size(); i++) + { + ieInpNodes[i] = nodes[i].dynamicCast()->node; +@@ -389,9 +389,9 @@ public: + for (size_t i = 1; i < ieInpNodes.size(); i++) + { + switch (op) { +- case SUM: res = std::make_shared(res, ieInpNodes[i]); break; +- case PROD: res = std::make_shared(res, ieInpNodes[i]); break; +- case MAX: res = std::make_shared(res, ieInpNodes[i]); break; ++ case SUM: res = std::make_shared(res, ieInpNodes[i]); break; ++ case PROD: res = std::make_shared(res, ieInpNodes[i]); break; ++ case MAX: res = std::make_shared(res, ieInpNodes[i]); break; + default: CV_Error(Error::StsNotImplemented, "Unsupported eltwise operation"); + } + } +diff --git a/modules/dnn/src/int8layers/fully_connected_layer.cpp b/modules/dnn/src/int8layers/fully_connected_layer.cpp +index ba5b0d79c1..5d13ba8f29 100644 +--- a/modules/dnn/src/int8layers/fully_connected_layer.cpp ++++ b/modules/dnn/src/int8layers/fully_connected_layer.cpp +@@ -405,8 +405,8 @@ public: + CV_CheckTypeEQ(blobs[1].type(), CV_32S, ""); // bias + CV_CheckTypeEQ(outputMultiplier.type(), CV_32F, ""); + +- ngraph::Output input = nodes[0].dynamicCast()->node; +- ngraph::Output ieWeights, ieBias, matmul; ++ ov::Output input = nodes[0].dynamicCast()->node; ++ ov::Output ieWeights, ieBias, matmul; + bool transA = false, transB = true; + size_t numOutput = blobs[0].size[0]; + +@@ -414,15 +414,15 @@ public: + { + CV_Error(Error::StsNotImplemented, ""); + // auto inp2 = nodes[1].dynamicCast()->node; +- // matmul = std::make_shared(ieInpNode, inp2, transA, transB); ++ // matmul = std::make_shared(ieInpNode, inp2, transA, transB); + } + else + { + std::vector shape(1 + normalize_axis(axis, input.get_shape().size()), 0); + shape[shape.size() - 1] = -1; +- input = std::make_shared( ++ input = std::make_shared( + input, +- std::make_shared(ngraph::element::i32, ngraph::Shape{shape.size()}, shape.data()), ++ std::make_shared(ov::element::i32, ov::Shape{shape.size()}, shape.data()), + true + ); + +@@ -439,16 +439,16 @@ public: + } + + std::vector weight_shape{(size_t)blobs[0].size[0], (size_t)blobs[0].size[1]}; +- ieWeights = std::make_shared(ngraph::element::i8, weight_shape, blobs[0].data); +- ieWeights = std::make_shared(ieWeights, ngraph::element::f32); +- ieWeights = std::make_shared(ieWeights, +- std::make_shared(ngraph::element::f32, ngraph::Shape{numOutput, 1}, inpLows.data()), +- std::make_shared(ngraph::element::f32, ngraph::Shape{numOutput, 1}, inpHighs.data()), +- std::make_shared(ngraph::element::f32, ngraph::Shape{numOutput, 1}, outLows.data()), +- std::make_shared(ngraph::element::f32, ngraph::Shape{numOutput, 1}, outHighs.data()), ++ ieWeights = std::make_shared(ov::element::i8, weight_shape, blobs[0].data); ++ ieWeights = std::make_shared(ieWeights, ov::element::f32); ++ ieWeights = std::make_shared(ieWeights, ++ std::make_shared(ov::element::f32, ov::Shape{numOutput, 1}, inpLows.data()), ++ std::make_shared(ov::element::f32, ov::Shape{numOutput, 1}, inpHighs.data()), ++ std::make_shared(ov::element::f32, ov::Shape{numOutput, 1}, outLows.data()), ++ std::make_shared(ov::element::f32, ov::Shape{numOutput, 1}, outHighs.data()), + 256 // levels + ); +- matmul = std::make_shared(input, ieWeights, transA, transB); ++ matmul = std::make_shared(input, ieWeights, transA, transB); + } + + if (blobs.size() > 1) { +@@ -457,9 +457,9 @@ public: + for (int i = 0; i < ovBias.size(); ++i) { + ovBias[i] = (bias[i] + input_zp * cv::sum(blobs[0].row(i))[0]) * outputMultiplier.ptr()[i] * output_sc; + } +- auto bias_node = std::make_shared(ngraph::element::f32, +- ngraph::Shape{blobs[1].total()}, ovBias.data()); +- matmul = std::make_shared(matmul, bias_node); ++ auto bias_node = std::make_shared(ov::element::f32, ++ ov::Shape{blobs[1].total()}, ovBias.data()); ++ matmul = std::make_shared(matmul, bias_node); + } + + matmul = ngraphQuantize(matmul, output_sc, output_zp); +diff --git a/modules/dnn/src/int8layers/pooling_layer.cpp b/modules/dnn/src/int8layers/pooling_layer.cpp +index b321d730f7..cfd04bd2f4 100644 +--- a/modules/dnn/src/int8layers/pooling_layer.cpp ++++ b/modules/dnn/src/int8layers/pooling_layer.cpp +@@ -11,6 +11,7 @@ + #include + #include + #include ++ + using std::max; + using std::min; + +@@ -284,22 +285,22 @@ public: + + input = ngraphDequantize(input, input_sc, input_zp); + +- ngraph::op::PadType pad_type = ngraph::op::PadType::EXPLICIT; ++ ov::op::PadType pad_type = ov::op::PadType::EXPLICIT; + if (!padMode.empty()) +- pad_type = padMode == "VALID" ? ngraph::op::PadType::VALID : ngraph::op::PadType::SAME_UPPER; ++ pad_type = padMode == "VALID" ? ov::op::PadType::VALID : ov::op::PadType::SAME_UPPER; + +- auto rounding_type = ceilMode ? ngraph::op::RoundingType::CEIL : ngraph::op::RoundingType::FLOOR; +- ngraph::Output pool; ++ auto rounding_type = ceilMode ? ov::op::RoundingType::CEIL : ov::op::RoundingType::FLOOR; ++ ov::Output pool; + if (type == MAX) { +- pool = std::make_shared(input, ngraph::Strides(strides), +- ngraph::Shape(pads_begin), ngraph::Shape(pads_end), ngraph::Shape(kernel_size), ++ pool = std::make_shared(input, ov::Strides(strides), ++ ov::Shape(pads_begin), ov::Shape(pads_end), ov::Shape(kernel_size), + rounding_type, pad_type); + } else if (type == AVE) { +- pool = std::make_shared(input, ngraph::Strides(strides), +- ngraph::Shape(pads_begin), ngraph::Shape(pads_end), ngraph::Shape(kernel_size), ++ pool = std::make_shared(input, ov::Strides(strides), ++ ov::Shape(pads_begin), ov::Shape(pads_end), ov::Shape(kernel_size), + !avePoolPaddedArea, rounding_type, pad_type); + } else if (type == SUM) { +- ngraph::Shape inpShape = input.get_shape(); ++ ov::Shape inpShape = input.get_shape(); + CV_Assert(inpShape.size() == 2 + kernel_size.size()); + std::vector axes; + for (size_t i = 0; i < kernel_size.size(); i++) +@@ -307,8 +308,8 @@ public: + if (inpShape[2 + i] == kernel_size[i]) + axes.push_back(2 + i); + } +- auto reduction_axes = std::make_shared(ngraph::element::i64, ngraph::Shape{axes.size()}, axes); +- pool = std::make_shared(input, reduction_axes, true); ++ auto reduction_axes = std::make_shared(ov::element::i64, ov::Shape{axes.size()}, axes); ++ pool = std::make_shared(input, reduction_axes, true); + } else { + CV_Error(Error::StsNotImplemented, format("INT8 Pooling type: %d", type)); + } +diff --git a/modules/dnn/src/int8layers/scale_layer.cpp b/modules/dnn/src/int8layers/scale_layer.cpp +index e50c4cea0e..25d48e3d17 100644 +--- a/modules/dnn/src/int8layers/scale_layer.cpp ++++ b/modules/dnn/src/int8layers/scale_layer.cpp +@@ -191,7 +191,7 @@ public: + #ifdef HAVE_DNN_NGRAPH + virtual Ptr initNgraph(const std::vector >& inputs, const std::vector >& nodes) CV_OVERRIDE + { +- std::vector> ieInpNodes(nodes.size()); ++ std::vector> ieInpNodes(nodes.size()); + for (int i = 0; i < nodes.size(); ++i) { + ieInpNodes[i] = nodes[i].dynamicCast()->node; + } +@@ -200,7 +200,7 @@ public: + + CV_Assert(!blobs.empty() || ieInpNodes.size() == 1 + (int)hasWeights + (int)hasBias); + +- ngraph::Output weights, bias; ++ ov::Output weights, bias; + if (blobs.empty()) { + if (hasWeights) + weights = ieInpNodes[1]; +@@ -222,17 +222,17 @@ public: + } + + if (hasWeights) +- weights = std::make_shared(ngraph::element::f32, shape, blobs[0].data); ++ weights = std::make_shared(ov::element::f32, shape, blobs[0].data); + if (hasBias) +- bias = std::make_shared(ngraph::element::f32, shape, blobs[(int)hasWeights].data); ++ bias = std::make_shared(ov::element::f32, shape, blobs[(int)hasWeights].data); + } + +- ngraph::Output res = ieInpNodes[0]; ++ ov::Output res = ieInpNodes[0]; + if (hasWeights) { +- res = std::make_shared(res, weights); ++ res = std::make_shared(res, weights); + } + if (hasBias) { +- res = std::make_shared(res, bias); ++ res = std::make_shared(res, bias); + } + + res = ngraphQuantize(res, output_sc, output_zp); +diff --git a/modules/dnn/src/int8layers/softmax_layer.cpp b/modules/dnn/src/int8layers/softmax_layer.cpp +index 28c6837cca..e81b82b99f 100644 +--- a/modules/dnn/src/int8layers/softmax_layer.cpp ++++ b/modules/dnn/src/int8layers/softmax_layer.cpp +@@ -204,11 +204,11 @@ public: + + input = ngraphDequantize(input, input_sc, input_zp); + +- ngraph::Output res; ++ ov::Output res; + if (logSoftMax) { +- res = std::make_shared(input, axis); ++ res = std::make_shared(input, axis); + } else { +- res = std::make_shared(input, axis); ++ res = std::make_shared(input, axis); + } + + res = ngraphQuantize(res, output_sc, output_zp); +diff --git a/modules/dnn/src/layers/batch_norm_layer.cpp b/modules/dnn/src/layers/batch_norm_layer.cpp +index 1d95096e60..ccf5608317 100644 +--- a/modules/dnn/src/layers/batch_norm_layer.cpp ++++ b/modules/dnn/src/layers/batch_norm_layer.cpp +@@ -18,8 +18,6 @@ Implementation of Batch Normalization layer. + #include "../op_webnn.hpp" + #include "../op_cann.hpp" + +-#include +- + #ifdef HAVE_OPENCL + #include "opencl_kernels_dnn.hpp" + #endif +@@ -459,14 +457,10 @@ public: + auto ieInpNode = nodes[0].dynamicCast()->node; + std::vector shape(ieInpNode.get_shape().size(), 1); + shape[1] = weights_.total(); +- auto weight = std::make_shared(ngraph::element::f32, ngraph::Shape(shape), weights_.data); +- auto bias = std::make_shared(ngraph::element::f32, ngraph::Shape(shape), bias_.data); +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2021_2) +- auto scale_node = std::make_shared(ieInpNode, weight, ngraph::op::AutoBroadcastType::NUMPY); +-#else +- auto scale_node = std::make_shared(ieInpNode, weight, ngraph::op::AutoBroadcastType::NUMPY); +-#endif +- auto scale_shift = std::make_shared(scale_node, bias, ngraph::op::AutoBroadcastType::NUMPY); ++ auto weight = std::make_shared(ov::element::f32, ov::Shape(shape), weights_.data); ++ auto bias = std::make_shared(ov::element::f32, ov::Shape(shape), bias_.data); ++ auto scale_node = std::make_shared(ieInpNode, weight, ov::op::AutoBroadcastType::NUMPY); ++ auto scale_shift = std::make_shared(scale_node, bias, ov::op::AutoBroadcastType::NUMPY); + return Ptr(new InfEngineNgraphNode(scale_shift)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/blank_layer.cpp b/modules/dnn/src/layers/blank_layer.cpp +index 16de23b15e..9723975723 100644 +--- a/modules/dnn/src/layers/blank_layer.cpp ++++ b/modules/dnn/src/layers/blank_layer.cpp +@@ -149,8 +149,8 @@ public: + const std::vector >& nodes) CV_OVERRIDE + { + auto ieInpNode = nodes[0].dynamicCast()->node; +- ngraph::OutputVector inp{ieInpNode}; +- auto blank = std::make_shared(inp, 0); ++ ov::OutputVector inp{ieInpNode}; ++ auto blank = std::make_shared(inp, 0); + return Ptr(new InfEngineNgraphNode(blank)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/concat_layer.cpp b/modules/dnn/src/layers/concat_layer.cpp +index a5af16f32e..14834d2cd3 100644 +--- a/modules/dnn/src/layers/concat_layer.cpp ++++ b/modules/dnn/src/layers/concat_layer.cpp +@@ -59,7 +59,6 @@ + #include "../cuda4dnn/primitives/concat.hpp" + using namespace cv::dnn::cuda4dnn; + #endif +- + namespace cv + { + namespace dnn +@@ -397,7 +396,7 @@ public: + std::vector maxDims(numDims, 0); + + CV_Assert(inputs.size() == nodes.size()); +- ngraph::OutputVector inp_nodes; ++ ov::OutputVector inp_nodes; + for (int i = 0; i < nodes.size(); ++i) + { + auto inp = nodes[i].dynamicCast()->node; +@@ -423,14 +422,14 @@ public: + } + if (needPadding) + { +- inp_nodes[i] = std::make_shared( ++ inp_nodes[i] = std::make_shared( + inp_nodes[i], +- std::make_shared(ngraph::element::i64, ngraph::Shape{begins.size()}, begins.data()), +- std::make_shared(ngraph::element::i64, ngraph::Shape{ends.size()}, ends.data()), +- ngraph::op::PadMode::CONSTANT); ++ std::make_shared(ov::element::i64, ov::Shape{begins.size()}, begins.data()), ++ std::make_shared(ov::element::i64, ov::Shape{ends.size()}, ends.data()), ++ ov::op::PadMode::CONSTANT); + } + } +- auto concat = std::make_shared(inp_nodes, cAxis); ++ auto concat = std::make_shared(inp_nodes, cAxis); + return Ptr(new InfEngineNgraphNode(concat)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/const_layer.cpp b/modules/dnn/src/layers/const_layer.cpp +index 2a1e27db56..0fe7c22782 100644 +--- a/modules/dnn/src/layers/const_layer.cpp ++++ b/modules/dnn/src/layers/const_layer.cpp +@@ -128,22 +128,22 @@ public: + virtual Ptr initNgraph(const std::vector >& inputs, + const std::vector >& nodes) CV_OVERRIDE + { +- ngraph::element::Type dType; ++ ov::element::Type dType; + if (blobs[0].depth() == CV_32F) { +- dType = ngraph::element::f32; ++ dType = ov::element::f32; + } else if (blobs[0].depth() == CV_32S) { +- dType = ngraph::element::i32; ++ dType = ov::element::i32; + } else if (blobs[0].depth() == CV_8S) { +- dType = ngraph::element::i8; ++ dType = ov::element::i8; + } else { + CV_Error(Error::StsNotImplemented, format("Unexpected Const data depth: %d", blobs[0].depth())); + } +- std::shared_ptr node = +- std::make_shared(dType, ++ std::shared_ptr node = ++ std::make_shared(dType, + getShape(blobs[0]), + blobs[0].data); +- if (node->get_element_type() != ngraph::element::f32) { +- node = std::make_shared(node, ngraph::element::f32); ++ if (node->get_element_type() != ov::element::f32) { ++ node = std::make_shared(node, ov::element::f32); + } + return Ptr(new InfEngineNgraphNode(node)); + } +diff --git a/modules/dnn/src/layers/convolution_layer.cpp b/modules/dnn/src/layers/convolution_layer.cpp +index dd6fa7bc1d..85c9f1d8d6 100644 +--- a/modules/dnn/src/layers/convolution_layer.cpp ++++ b/modules/dnn/src/layers/convolution_layer.cpp +@@ -822,7 +822,7 @@ public: + auto& ieInpNode = nodes[0].dynamicCast()->node; + std::vector dims = ieInpNode.get_shape(); + CV_Check(dims.size(), dims.size() >= 3 && dims.size() <= 5, ""); +- ngraph::Output ieWeights; ++ ov::Output ieWeights; + if (nodes.size() > 1) + ieWeights = nodes[1].dynamicCast()->node; + const int inpCn = dims[1]; +@@ -840,49 +840,49 @@ public: + + if (nodes.size() == 1) + { +- ieWeights = std::make_shared(ngraph::element::f32, kernel_shape, blobs[0].data); ++ ieWeights = std::make_shared(ov::element::f32, kernel_shape, blobs[0].data); + if (fusedWeights) + { + if (weightsMat.isContinuous()) + { +- ieWeights = std::make_shared(ngraph::element::f32, kernel_shape, weightsMat.data); ++ ieWeights = std::make_shared(ov::element::f32, kernel_shape, weightsMat.data); + } + else + { + Mat newWeights; + Mat cvWeights = weightsMat.colRange(0, blobs[0].total() / numOutput); + cvWeights.copyTo(newWeights); +- ieWeights = std::make_shared(ngraph::element::f32, kernel_shape, newWeights.data); ++ ieWeights = std::make_shared(ov::element::f32, kernel_shape, newWeights.data); + } + } + } + else + { +- auto shape = std::make_shared(ngraph::element::i64, +- ngraph::Shape{kernel_shape.size()}, std::vector(kernel_shape.begin(), kernel_shape.end())); +- ieWeights = std::make_shared(ieWeights, shape, true); ++ auto shape = std::make_shared(ov::element::i64, ++ ov::Shape{kernel_shape.size()}, std::vector(kernel_shape.begin(), kernel_shape.end())); ++ ieWeights = std::make_shared(ieWeights, shape, true); + } + +- ngraph::op::PadType pad_type = ngraph::op::PadType::EXPLICIT; ++ ov::op::PadType pad_type = ov::op::PadType::EXPLICIT; + if (!padMode.empty()) +- pad_type = padMode == "VALID" ? ngraph::op::PadType::VALID : ngraph::op::PadType::SAME_UPPER; ++ pad_type = padMode == "VALID" ? ov::op::PadType::VALID : ov::op::PadType::SAME_UPPER; + +- std::shared_ptr conv_node; ++ std::shared_ptr conv_node; + if (group != 1) { +- conv_node = std::make_shared( ++ conv_node = std::make_shared( + ieInpNode, ieWeights, +- ngraph::Strides(strides), +- ngraph::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), +- ngraph::CoordinateDiff(std::vector(pads_end.begin(), pads_end.end())), +- ngraph::Strides(dilations), ++ ov::Strides(strides), ++ ov::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), ++ ov::CoordinateDiff(std::vector(pads_end.begin(), pads_end.end())), ++ ov::Strides(dilations), + pad_type); + } else { +- conv_node = std::make_shared( ++ conv_node = std::make_shared( + ieInpNode, ieWeights, +- ngraph::Strides(strides), +- ngraph::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), +- ngraph::CoordinateDiff(std::vector(pads_end.begin(), pads_end.end())), +- ngraph::Strides(dilations), ++ ov::Strides(strides), ++ ov::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), ++ ov::CoordinateDiff(std::vector(pads_end.begin(), pads_end.end())), ++ ov::Strides(dilations), + pad_type); + } + +@@ -890,18 +890,18 @@ public: + { + std::vector shape(conv_node->get_shape().size(), 1); + shape[1] = conv_node->get_shape()[1]; +- std::shared_ptr bias; ++ std::shared_ptr bias; + if (nodes.size() == 3) + { +- auto bias_shape = std::make_shared(ngraph::element::i64, +- ngraph::Shape{shape.size()}, std::vector(shape.begin(), shape.end())); +- bias = std::make_shared(nodes[2].dynamicCast()->node, bias_shape, true); ++ auto bias_shape = std::make_shared(ov::element::i64, ++ ov::Shape{shape.size()}, std::vector(shape.begin(), shape.end())); ++ bias = std::make_shared(nodes[2].dynamicCast()->node, bias_shape, true); + } + else + { +- bias = std::make_shared(ngraph::element::f32, ngraph::Shape(shape), biasvec.data()); ++ bias = std::make_shared(ov::element::f32, ov::Shape(shape), biasvec.data()); + } +- auto conv_bias = std::make_shared(conv_node, bias, ngraph::op::AutoBroadcastType::NUMPY); ++ auto conv_bias = std::make_shared(conv_node, bias, ov::op::AutoBroadcastType::NUMPY); + return Ptr(new InfEngineNgraphNode(conv_bias)); + } + return Ptr(new InfEngineNgraphNode(conv_node)); +@@ -2251,13 +2251,13 @@ public: + + auto& ieInpNode = nodes[0].dynamicCast()->node; + std::vector kernel_shape = getShape(blobs[0]); +- auto ieWeights = std::make_shared(ngraph::element::f32, kernel_shape, blobs[0].data); ++ auto ieWeights = std::make_shared(ov::element::f32, kernel_shape, blobs[0].data); + + if (fusedWeights) + { + Mat newWeights; + transpose(weightsMat, newWeights); +- ieWeights = std::make_shared(ngraph::element::f32, kernel_shape, newWeights.data); ++ ieWeights = std::make_shared(ov::element::f32, kernel_shape, newWeights.data); + } + std::vector paddings_end; + if (padMode == "SAME") +@@ -2269,24 +2269,24 @@ public: + } else { + paddings_end = pads_end; + } +- ngraph::op::PadType pad_type = padMode == "VALID" ? ngraph::op::PadType::VALID : ngraph::op::PadType::EXPLICIT; ++ ov::op::PadType pad_type = padMode == "VALID" ? ov::op::PadType::VALID : ov::op::PadType::EXPLICIT; + +- auto deconv = std::make_shared( ++ auto deconv = std::make_shared( + ieInpNode, + ieWeights, +- ngraph::Strides(strides), +- ngraph::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), +- ngraph::CoordinateDiff(std::vector(paddings_end.begin(), paddings_end.end())), +- ngraph::Strides(dilations), ++ ov::Strides(strides), ++ ov::CoordinateDiff(std::vector(pads_begin.begin(), pads_begin.end())), ++ ov::CoordinateDiff(std::vector(paddings_end.begin(), paddings_end.end())), ++ ov::Strides(dilations), + pad_type, +- ngraph::CoordinateDiff(std::vector(adjust_pads.begin(), adjust_pads.end()))); ++ ov::CoordinateDiff(std::vector(adjust_pads.begin(), adjust_pads.end()))); + + if (hasBias() || fusedBias) + { + std::vector shape(deconv->get_shape().size(), 1); + shape[1] = numOutput; +- auto bias = std::make_shared(ngraph::element::f32, ngraph::Shape(shape), blobs[1].data); +- auto deconv_bias = std::make_shared(deconv, bias, ngraph::op::AutoBroadcastType::NUMPY); ++ auto bias = std::make_shared(ov::element::f32, ov::Shape(shape), blobs[1].data); ++ auto deconv_bias = std::make_shared(deconv, bias, ov::op::AutoBroadcastType::NUMPY); + return Ptr(new InfEngineNgraphNode(deconv_bias)); + } + +diff --git a/modules/dnn/src/layers/crop_and_resize_layer.cpp b/modules/dnn/src/layers/crop_and_resize_layer.cpp +index a6f58f8983..e735242929 100644 +--- a/modules/dnn/src/layers/crop_and_resize_layer.cpp ++++ b/modules/dnn/src/layers/crop_and_resize_layer.cpp +@@ -138,23 +138,23 @@ public: + offsets[3] = 2; + dims[3] = 7; + +- auto lower_bounds = std::make_shared(ngraph::element::i64, +- ngraph::Shape{offsets.size()}, offsets.data()); +- auto upper_bounds = std::make_shared(ngraph::element::i64, +- ngraph::Shape{dims.size()}, dims.data()); +- auto strides = std::make_shared(ngraph::element::i64, +- ngraph::Shape{dims.size()}, std::vector((int64_t)dims.size(), 1)); +- auto slice = std::make_shared(rois, ++ auto lower_bounds = std::make_shared(ov::element::i64, ++ ov::Shape{offsets.size()}, offsets.data()); ++ auto upper_bounds = std::make_shared(ov::element::i64, ++ ov::Shape{dims.size()}, dims.data()); ++ auto strides = std::make_shared(ov::element::i64, ++ ov::Shape{dims.size()}, std::vector((int64_t)dims.size(), 1)); ++ auto slice = std::make_shared(rois, + lower_bounds, upper_bounds, strides, std::vector{}, std::vector{}); + + // Reshape rois from 4D to 2D + std::vector shapeData = {dims[2], 5}; +- auto shape = std::make_shared(ngraph::element::i64, ngraph::Shape{2}, shapeData.data()); +- auto reshape = std::make_shared(slice, shape, true); ++ auto shape = std::make_shared(ov::element::i64, ov::Shape{2}, shapeData.data()); ++ auto reshape = std::make_shared(slice, shape, true); + + auto roiPooling = +- std::make_shared(input, reshape, +- ngraph::Shape{(size_t)outHeight, (size_t)outWidth}, ++ std::make_shared(input, reshape, ++ ov::Shape{(size_t)outHeight, (size_t)outWidth}, + 1.0f, "bilinear"); + + return Ptr(new InfEngineNgraphNode(roiPooling)); +diff --git a/modules/dnn/src/layers/detection_output_layer.cpp b/modules/dnn/src/layers/detection_output_layer.cpp +index 26f483a770..07f96e2a08 100644 +--- a/modules/dnn/src/layers/detection_output_layer.cpp ++++ b/modules/dnn/src/layers/detection_output_layer.cpp +@@ -55,11 +55,7 @@ + + #ifdef HAVE_DNN_NGRAPH + #include "../ie_ngraph.hpp" +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) +-#include +-#else +-#include +-#endif ++#include + #endif + + #ifdef HAVE_CUDA +@@ -1012,26 +1008,26 @@ public: + + if (_locPredTransposed) { + // Convert box predictions from yxYX to xyXY +- box_logits = std::make_shared(box_logits, +- std::make_shared(ngraph::element::i32, ngraph::Shape{3}, std::vector{0, -1, 2}), ++ box_logits = std::make_shared(box_logits, ++ std::make_shared(ov::element::i32, ov::Shape{3}, std::vector{0, -1, 2}), + true + ); + int axis = 2; +- box_logits = std::make_shared(box_logits, +- std::make_shared(ngraph::element::i32, ngraph::Shape{1}, &axis), +- ngraph::op::v1::Reverse::Mode::INDEX ++ box_logits = std::make_shared(box_logits, ++ std::make_shared(ov::element::i32, ov::Shape{1}, &axis), ++ ov::op::v1::Reverse::Mode::INDEX + ); + } + +- auto shape = std::make_shared(ngraph::element::i32, ngraph::Shape{2}, std::vector{0, -1}); +- box_logits = std::make_shared(box_logits, shape, true); +- class_preds = std::make_shared(class_preds, shape, true); +- proposals = std::make_shared(proposals, +- std::make_shared(ngraph::element::i32, ngraph::Shape{3}, std::vector{0, _varianceEncodedInTarget ? 1 : 2, -1}), ++ auto shape = std::make_shared(ov::element::i32, ov::Shape{2}, std::vector{0, -1}); ++ box_logits = std::make_shared(box_logits, shape, true); ++ class_preds = std::make_shared(class_preds, shape, true); ++ proposals = std::make_shared(proposals, ++ std::make_shared(ov::element::i32, ov::Shape{3}, std::vector{0, _varianceEncodedInTarget ? 1 : 2, -1}), + true + ); + +- ngraph::op::DetectionOutputAttrs attrs; ++ ov::op::v0::DetectionOutput::Attributes attrs; + attrs.num_classes = _numClasses; + attrs.background_label_id = _backgroundLabelId; + attrs.top_k = _topK > 0 ? _topK : _keepTopK; +@@ -1044,7 +1040,7 @@ public: + attrs.code_type = std::string{"caffe.PriorBoxParameter." + _codeType}; + attrs.normalized = true; + +- auto det_out = std::make_shared(box_logits, class_preds, ++ auto det_out = std::make_shared(box_logits, class_preds, + proposals, attrs); + return Ptr(new InfEngineNgraphNode(det_out)); + } +diff --git a/modules/dnn/src/layers/elementwise_layers.cpp b/modules/dnn/src/layers/elementwise_layers.cpp +index 746db69603..f96a7f2f08 100644 +--- a/modules/dnn/src/layers/elementwise_layers.cpp ++++ b/modules/dnn/src/layers/elementwise_layers.cpp +@@ -490,13 +490,13 @@ struct ReLUFunctor : public BaseFunctor + #endif + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { + if (slope) { +- auto param = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &slope); +- return std::make_shared(node, param); ++ auto param = std::make_shared(ov::element::f32, ov::Shape{1}, &slope); ++ return std::make_shared(node, param); + } +- return std::make_shared(node); ++ return std::make_shared(node); + } + #endif // HAVE_DNN_NGRAPH + +@@ -674,9 +674,9 @@ struct ReLU6Functor : public BaseFunctor + + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- return std::make_shared(node, minValue, maxValue); ++ return std::make_shared(node, minValue, maxValue); + } + #endif // HAVE_DNN_NGRAPH + +@@ -796,7 +796,7 @@ struct BaseDefaultFunctor : public BaseFunctor + #endif // HAVE_CANN + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { + CV_Error(Error::StsNotImplemented, ""); + } +@@ -929,9 +929,9 @@ struct TanHFunctor : public BaseDefaultFunctor + #endif // HAVE_CANN + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- return std::make_shared(node); ++ return std::make_shared(node); + } + #endif // HAVE_DNN_NGRAPH + +@@ -998,10 +998,10 @@ struct SwishFunctor : public BaseDefaultFunctor + #endif // HAVE_CANN + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- auto sigmoid = std::make_shared(node); +- return std::make_shared(node, sigmoid); ++ auto sigmoid = std::make_shared(node); ++ return std::make_shared(node, sigmoid); + } + #endif // HAVE_DNN_NGRAPH + +@@ -1074,9 +1074,9 @@ struct MishFunctor : public BaseDefaultFunctor + #endif // HAVE_CANN + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- return std::make_shared(node); ++ return std::make_shared(node); + } + #endif // HAVE_DNN_NGRAPH + +@@ -1151,9 +1151,9 @@ struct SigmoidFunctor : public BaseDefaultFunctor + #endif // HAVE_CANN + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- return std::make_shared(node); ++ return std::make_shared(node); + } + #endif // HAVE_DNN_NGRAPH + +@@ -1231,9 +1231,9 @@ struct ELUFunctor : public BaseDefaultFunctor + #endif // HAVE_CANN + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- return std::make_shared(node, alpha); ++ return std::make_shared(node, alpha); + } + #endif // HAVE_DNN_NGRAPH + +@@ -1301,9 +1301,9 @@ struct AbsValFunctor : public BaseDefaultFunctor + #endif // HAVE_CANN + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- return std::make_shared(node); ++ return std::make_shared(node); + } + #endif // HAVE_DNN_NGRAPH + +@@ -1594,9 +1594,9 @@ struct SqrtFunctor : public BaseDefaultFunctor + #endif // HAVE_HALIDE + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- return std::make_shared(node); ++ return std::make_shared(node); + } + #endif // HAVE_DNN_NGRAPH + +@@ -2343,22 +2343,22 @@ struct PowerFunctor : public BaseFunctor + #endif // HAVE_CANN + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- auto scale_node = std::make_shared(ngraph::element::f32, +- ngraph::Shape{1}, &scale); +- auto shift_node = std::make_shared(ngraph::element::f32, +- ngraph::Shape{1}, &shift); ++ auto scale_node = std::make_shared(ov::element::f32, ++ ov::Shape{1}, &scale); ++ auto shift_node = std::make_shared(ov::element::f32, ++ ov::Shape{1}, &shift); + +- auto mul = std::make_shared(scale_node, node, ngraph::op::AutoBroadcastType::NUMPY); +- auto scale_shift = std::make_shared(mul, shift_node, ngraph::op::AutoBroadcastType::NUMPY); ++ auto mul = std::make_shared(scale_node, node, ov::op::AutoBroadcastType::NUMPY); ++ auto scale_shift = std::make_shared(mul, shift_node, ov::op::AutoBroadcastType::NUMPY); + + if (power == 1) + return scale_shift; + +- auto power_node = std::make_shared(ngraph::element::f32, +- ngraph::Shape{1}, &power); +- return std::make_shared(scale_shift, power_node, ngraph::op::AutoBroadcastType::NUMPY); ++ auto power_node = std::make_shared(ov::element::f32, ++ ov::Shape{1}, &power); ++ return std::make_shared(scale_shift, power_node, ov::op::AutoBroadcastType::NUMPY); + } + #endif // HAVE_DNN_NGRAPH + +@@ -2453,15 +2453,15 @@ struct ExpFunctor : public BaseDefaultFunctor + #endif // HAVE_HALIDE + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { +- auto scale_node = std::make_shared(ngraph::element::f32, +- ngraph::Shape{1}, &normScale); +- auto shift_node = std::make_shared(ngraph::element::f32, +- ngraph::Shape{1}, &normShift); +- auto mul = std::make_shared(scale_node, node, ngraph::op::AutoBroadcastType::NUMPY); +- auto scale_shift = std::make_shared(mul, shift_node, ngraph::op::AutoBroadcastType::NUMPY); +- return std::make_shared(scale_shift); ++ auto scale_node = std::make_shared(ov::element::f32, ++ ov::Shape{1}, &normScale); ++ auto shift_node = std::make_shared(ov::element::f32, ++ ov::Shape{1}, &normShift); ++ auto mul = std::make_shared(scale_node, node, ov::op::AutoBroadcastType::NUMPY); ++ auto scale_shift = std::make_shared(mul, shift_node, ov::op::AutoBroadcastType::NUMPY); ++ return std::make_shared(scale_shift); + } + #endif // HAVE_DNN_NGRAPH + +@@ -2612,11 +2612,11 @@ struct ChannelsPReLUFunctor : public BaseFunctor + #endif // HAVE_CANN + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { + const size_t numChannels = scale.total(); +- auto slope = std::make_shared(ngraph::element::f32, ngraph::Shape{numChannels}, scale.data); +- return std::make_shared(node, slope); ++ auto slope = std::make_shared(ov::element::f32, ov::Shape{numChannels}, scale.data); ++ return std::make_shared(node, slope); + } + #endif // HAVE_DNN_NGRAPH + +@@ -2692,11 +2692,11 @@ struct PReLUFunctor : public ChannelsPReLUFunctor + } + + #ifdef HAVE_DNN_NGRAPH +- std::shared_ptr initNgraphAPI(const ngraph::Output& node) ++ std::shared_ptr initNgraphAPI(const ov::Output& node) + { + auto shape = getShape(scale); +- auto slope = std::make_shared(ngraph::element::f32, shape, scale.ptr()); +- return std::make_shared(node, slope); ++ auto slope = std::make_shared(ov::element::f32, shape, scale.ptr()); ++ return std::make_shared(node, slope); + } + #endif // HAVE_DNN_NGRAPH + }; +diff --git a/modules/dnn/src/layers/eltwise_layer.cpp b/modules/dnn/src/layers/eltwise_layer.cpp +index 49b3c02de3..37b8b1ba66 100644 +--- a/modules/dnn/src/layers/eltwise_layer.cpp ++++ b/modules/dnn/src/layers/eltwise_layer.cpp +@@ -899,24 +899,24 @@ public: + CV_Assert(nodes.size() >= 2); + auto curr_node = nodes[0].dynamicCast()->node; + if (!coeffs.empty()) { +- auto coeff = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &coeffs[0]); +- curr_node = std::make_shared(curr_node, coeff, ngraph::op::AutoBroadcastType::NUMPY); ++ auto coeff = std::make_shared(ov::element::f32, ov::Shape{1}, &coeffs[0]); ++ curr_node = std::make_shared(curr_node, coeff, ov::op::AutoBroadcastType::NUMPY); + } + +- std::shared_ptr res; ++ std::shared_ptr res; + for (size_t i = 1; i < nodes.size(); i++) + { + auto next_node = nodes[i].dynamicCast()->node; + if (!coeffs.empty()) { +- auto coeff = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &coeffs[i]); +- next_node = std::make_shared(next_node, coeff, ngraph::op::AutoBroadcastType::NUMPY); ++ auto coeff = std::make_shared(ov::element::f32, ov::Shape{1}, &coeffs[i]); ++ next_node = std::make_shared(next_node, coeff, ov::op::AutoBroadcastType::NUMPY); + } + switch (op) { +- case SUM: res = std::make_shared(curr_node, next_node); break; +- case PROD: res = std::make_shared(curr_node, next_node); break; +- case DIV: res = std::make_shared(curr_node, next_node); break; +- case MAX: res = std::make_shared(curr_node, next_node); break; +- case MIN: res = std::make_shared(curr_node, next_node); break; ++ case SUM: res = std::make_shared(curr_node, next_node); break; ++ case PROD: res = std::make_shared(curr_node, next_node); break; ++ case DIV: res = std::make_shared(curr_node, next_node); break; ++ case MAX: res = std::make_shared(curr_node, next_node); break; ++ case MIN: res = std::make_shared(curr_node, next_node); break; + default: CV_Error(Error::StsNotImplemented, "Unsupported eltwise operation"); + } + curr_node = res; +diff --git a/modules/dnn/src/layers/flatten_layer.cpp b/modules/dnn/src/layers/flatten_layer.cpp +index 9ff3bec38b..48950601f2 100644 +--- a/modules/dnn/src/layers/flatten_layer.cpp ++++ b/modules/dnn/src/layers/flatten_layer.cpp +@@ -56,6 +56,7 @@ + using namespace cv::dnn::cuda4dnn; + #endif + ++ + namespace cv + { + namespace dnn +@@ -224,9 +225,9 @@ public: + outputShapeVec.push_back(flattenedDimensionSize); + outputShapeVec.insert(outputShapeVec.end(), dims.begin() + endAxis + 1, dims.end()); + +- auto shape = std::make_shared(ngraph::element::i64, +- ngraph::Shape({outputShapeVec.size()}), outputShapeVec.data()); +- auto reshape = std::make_shared(ieInpNode, shape, true); ++ auto shape = std::make_shared(ov::element::i64, ++ ov::Shape({outputShapeVec.size()}), outputShapeVec.data()); ++ auto reshape = std::make_shared(ieInpNode, shape, true); + return Ptr(new InfEngineNgraphNode(reshape)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/fully_connected_layer.cpp b/modules/dnn/src/layers/fully_connected_layer.cpp +index 1c27043f1a..0694c4bc69 100644 +--- a/modules/dnn/src/layers/fully_connected_layer.cpp ++++ b/modules/dnn/src/layers/fully_connected_layer.cpp +@@ -794,20 +794,20 @@ public: + const std::vector >& nodes) CV_OVERRIDE + { + auto& ieInpNode = nodes[0].dynamicCast()->node; +- std::shared_ptr matmul; ++ std::shared_ptr matmul; + + if (nodes.size() == 2) + { + auto& inp2 = nodes[1].dynamicCast()->node; +- matmul = std::make_shared(ieInpNode, inp2, transA, transB); ++ matmul = std::make_shared(ieInpNode, inp2, transA, transB); + } + else + { + std::vector shape(1 + normalize_axis(axis, ieInpNode.get_shape().size()), 0); + shape[shape.size() - 1] = -1; +- auto inp = std::make_shared( ++ auto inp = std::make_shared( + ieInpNode, +- std::make_shared(ngraph::element::i32, ngraph::Shape{shape.size()}, shape.data()), ++ std::make_shared(ov::element::i32, ov::Shape{shape.size()}, shape.data()), + true + ); + +@@ -817,14 +817,14 @@ public: + } else { + weight_shape = {(size_t)blobs[0].size[0], (size_t)blobs[0].size[1]}; + } +- auto ieWeights = std::make_shared(ngraph::element::f32, weight_shape, blobs[0].data); +- matmul = std::make_shared(inp, ieWeights, transA, transB); ++ auto ieWeights = std::make_shared(ov::element::f32, weight_shape, blobs[0].data); ++ matmul = std::make_shared(inp, ieWeights, transA, transB); + } + + if (bias) { +- auto bias_node = std::make_shared(ngraph::element::f32, +- ngraph::Shape{(size_t)blobs[1].size[1]}, blobs[1].data); +- matmul = std::make_shared(matmul, bias_node, ngraph::op::AutoBroadcastType::NUMPY); ++ auto bias_node = std::make_shared(ov::element::f32, ++ ov::Shape{(size_t)blobs[1].size[1]}, blobs[1].data); ++ matmul = std::make_shared(matmul, bias_node, ov::op::AutoBroadcastType::NUMPY); + } + return Ptr(new InfEngineNgraphNode(matmul)); + } +diff --git a/modules/dnn/src/layers/gemm_layer.cpp b/modules/dnn/src/layers/gemm_layer.cpp +index 821700c83e..8c7000a8e6 100644 +--- a/modules/dnn/src/layers/gemm_layer.cpp ++++ b/modules/dnn/src/layers/gemm_layer.cpp +@@ -285,45 +285,45 @@ public: + const std::vector >& nodes) CV_OVERRIDE + { + auto ieInpNode = nodes[0].dynamicCast()->node; +- std::shared_ptr matmul; ++ std::shared_ptr matmul; + + if (nodes.size() == 2) + { + auto& inp2 = nodes[1].dynamicCast()->node; +- matmul = std::make_shared(ieInpNode, inp2, trans_a, trans_b); ++ matmul = std::make_shared(ieInpNode, inp2, trans_a, trans_b); + } + else + { +- std::shared_ptr ieWeights = std::make_shared(ngraph::element::f32, getShape(blobs[0]), blobs[0].data); ++ std::shared_ptr ieWeights = std::make_shared(ov::element::f32, getShape(blobs[0]), blobs[0].data); + + int flatten_axis = ieInpNode.get_shape().size() - ieWeights->get_shape().size(); + if (flatten_axis > 0) { + std::vector shape(1 + flatten_axis, 0); + shape[shape.size() - 1] = -1; +- ieInpNode = std::make_shared( ++ ieInpNode = std::make_shared( + ieInpNode, +- std::make_shared(ngraph::element::i32, ngraph::Shape{shape.size()}, shape.data()), ++ std::make_shared(ov::element::i32, ov::Shape{shape.size()}, shape.data()), + true + ); + } +- matmul = std::make_shared(ieInpNode, ieWeights, trans_a, trans_b); ++ matmul = std::make_shared(ieInpNode, ieWeights, trans_a, trans_b); + } + if (alpha != 1.0f) { +- matmul = std::make_shared(matmul, +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &alpha) ++ matmul = std::make_shared(matmul, ++ std::make_shared(ov::element::f32, ov::Shape{1}, &alpha) + ); + } + + if (have_bias && const_C) { + Mat bias = blobs.back(); +- auto shape = bias.total() == bias.size[0] ? ngraph::Shape{bias.total()} : getShape(bias); +- std::shared_ptr bias_node = std::make_shared(ngraph::element::f32, shape, bias.data); ++ auto shape = bias.total() == bias.size[0] ? ov::Shape{bias.total()} : getShape(bias); ++ std::shared_ptr bias_node = std::make_shared(ov::element::f32, shape, bias.data); + if (beta != 1.0f) { +- bias_node = std::make_shared(bias_node, +- std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &beta) ++ bias_node = std::make_shared(bias_node, ++ std::make_shared(ov::element::f32, ov::Shape{1}, &beta) + ); + } +- matmul = std::make_shared(matmul, bias_node, ngraph::op::AutoBroadcastType::NUMPY); ++ matmul = std::make_shared(matmul, bias_node, ov::op::AutoBroadcastType::NUMPY); + } + return Ptr(new InfEngineNgraphNode(matmul)); + } +diff --git a/modules/dnn/src/layers/instance_norm_layer.cpp b/modules/dnn/src/layers/instance_norm_layer.cpp +index b43e9bbb7a..29f3732dc2 100644 +--- a/modules/dnn/src/layers/instance_norm_layer.cpp ++++ b/modules/dnn/src/layers/instance_norm_layer.cpp +@@ -225,33 +225,26 @@ public: + + auto ieInpNode = nodes[0].dynamicCast()->node; + const auto &input_shape = ieInpNode.get_shape(); +- std::shared_ptr mvn, result; ++ std::shared_ptr mvn, result; + + // mvn +-#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2021_2) +- // https://docs.openvino.ai/2021.4/api/ngraph_python_api/_autosummary/ngraph.opset3.mvn.html?highlight=mvn#ngraph.opset3.mvn +- bool across_channels = false; +- bool normalize_variance = true; +- mvn = std::make_shared(ieInpNode, across_channels, normalize_variance, epsilon); +-#else + // https://docs.openvino.ai/2023.1/openvino_docs_ops_normalization_MVN_6.html + std::vector axes_v(input_shape.size() - 2); + std::iota(axes_v.begin(), axes_v.end(), 2); // {2, 3, ...} for nd input tensor, n>=3 +- auto axes = std::make_shared(ngraph::element::i64, ngraph::Shape{axes_v.size()}, axes_v.data()); ++ auto axes = std::make_shared(ov::element::i64, ov::Shape{axes_v.size()}, axes_v.data()); + bool normalize_variance = true; +- mvn = std::make_shared(ieInpNode, axes, normalize_variance, epsilon, ngraph::op::MVNEpsMode::INSIDE_SQRT); +-#endif ++ mvn = std::make_shared(ieInpNode, axes, normalize_variance, epsilon, ov::op::MVNEpsMode::INSIDE_SQRT); + + // instance norm = scale * mvn + bias + auto scale = nodes[1].dynamicCast()->node; + std::vector shared_shape_v(input_shape.size(), 1); + shared_shape_v[1] = -1; +- auto shared_shape = std::make_shared(ngraph::element::i64, ngraph::Shape{shared_shape_v.size()}, shared_shape_v.data()); +- scale = std::make_shared(scale, shared_shape, true); +- result = std::make_shared(mvn, scale); ++ auto shared_shape = std::make_shared(ov::element::i64, ov::Shape{shared_shape_v.size()}, shared_shape_v.data()); ++ scale = std::make_shared(scale, shared_shape, true); ++ result = std::make_shared(mvn, scale); + auto bias = nodes[2].dynamicCast()->node; +- bias = std::make_shared(bias, shared_shape, true); +- result = std::make_shared(result, bias); ++ bias = std::make_shared(bias, shared_shape, true); ++ result = std::make_shared(result, bias); + + return Ptr(new InfEngineNgraphNode(result)); + } +diff --git a/modules/dnn/src/layers/layer_norm.cpp b/modules/dnn/src/layers/layer_norm.cpp +index f3d2667a0a..aae5ff9f41 100644 +--- a/modules/dnn/src/layers/layer_norm.cpp ++++ b/modules/dnn/src/layers/layer_norm.cpp +@@ -263,42 +263,35 @@ public: + const std::vector >& nodes) CV_OVERRIDE { + auto ieInpNode = nodes[0].dynamicCast()->node; + const auto &input_shape = ieInpNode.get_shape(); +- std::shared_ptr mvn, result; ++ std::shared_ptr mvn, result; + + // mvn +-#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2021_2) +- // https://docs.openvino.ai/2021.4/api/ngraph_python_api/_autosummary/ngraph.opset3.mvn.html?highlight=mvn#ngraph.opset3.mvn +- bool across_channels = false; +- bool normalize_variance = true; +- mvn = std::make_shared(ieInpNode, across_channels, normalize_variance, epsilon); +-#else + // https://docs.openvino.ai/2023.1/openvino_docs_ops_normalization_MVN_6.html + std::vector axes_v(input_shape.size() - axis); + std::iota(axes_v.begin(), axes_v.end(), axis); +- auto axes = std::make_shared(ngraph::element::i64, ngraph::Shape{axes_v.size()}, axes_v.data()); ++ auto axes = std::make_shared(ov::element::i64, ov::Shape{axes_v.size()}, axes_v.data()); + bool normalize_variance = true; +- mvn = std::make_shared(ieInpNode, axes, normalize_variance, epsilon, ngraph::op::MVNEpsMode::INSIDE_SQRT); +-#endif ++ mvn = std::make_shared(ieInpNode, axes, normalize_variance, epsilon, ov::op::MVNEpsMode::INSIDE_SQRT); + + // layer norm = scale * mvn + bias + auto scale = nodes[1].dynamicCast()->node; +- ngraph::Output bias; ++ ov::Output bias; + if (nodes.size() == 3) { + bias = nodes[2].dynamicCast()->node; + } + if (axis == -1 || axis == input_shape.size() - 1) { // special case for 1D tensor (2D mat) + std::vector shared_shape_v(input_shape.size(), 1); + shared_shape_v.back() = -1; +- auto shared_shape = std::make_shared(ngraph::element::i64, ngraph::Shape{shared_shape_v.size()}, shared_shape_v.data()); +- scale = std::make_shared(scale, shared_shape, true); ++ auto shared_shape = std::make_shared(ov::element::i64, ov::Shape{shared_shape_v.size()}, shared_shape_v.data()); ++ scale = std::make_shared(scale, shared_shape, true); + if (nodes.size() == 3) { +- bias = std::make_shared(bias, shared_shape, true); ++ bias = std::make_shared(bias, shared_shape, true); + } + } + +- result = std::make_shared(mvn, scale); ++ result = std::make_shared(mvn, scale); + if (nodes.size() == 3) { +- result = std::make_shared(result, bias); ++ result = std::make_shared(result, bias); + } + + return Ptr(new InfEngineNgraphNode(result)); +diff --git a/modules/dnn/src/layers/lrn_layer.cpp b/modules/dnn/src/layers/lrn_layer.cpp +index f8de64cb32..a86004ac18 100644 +--- a/modules/dnn/src/layers/lrn_layer.cpp ++++ b/modules/dnn/src/layers/lrn_layer.cpp +@@ -483,8 +483,8 @@ public: + axes.resize(ieInpNode.get_shape().size() - 2); + std::iota(axes.begin(), axes.end(), 2); + } +- auto ngraph_axes = std::make_shared(ngraph::element::i64, ngraph::Shape{axes.size()}, axes.data()); +- auto lrn = std::make_shared(ieInpNode, ngraph_axes, alphaSize, beta, bias, size); ++ auto ngraph_axes = std::make_shared(ov::element::i64, ov::Shape{axes.size()}, axes.data()); ++ auto lrn = std::make_shared(ieInpNode, ngraph_axes, alphaSize, beta, bias, size); + return Ptr(new InfEngineNgraphNode(lrn)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/matmul_layer.cpp b/modules/dnn/src/layers/matmul_layer.cpp +index c6cea65d87..2fccbde4ac 100644 +--- a/modules/dnn/src/layers/matmul_layer.cpp ++++ b/modules/dnn/src/layers/matmul_layer.cpp +@@ -216,15 +216,15 @@ class MatMulLayerImpl CV_FINAL : public MatMulLayer { + virtual Ptr initNgraph(const std::vector >& inputs, + const std::vector >& nodes) CV_OVERRIDE { + auto& input_A_node = nodes[0].dynamicCast()->node; +- std::shared_ptr matmul; ++ std::shared_ptr matmul; + + if (nodes.size() == 2) { + auto &input_B_node = nodes[1].dynamicCast()->node; +- matmul = std::make_shared(input_A_node, input_B_node, trans_a, trans_b); ++ matmul = std::make_shared(input_A_node, input_B_node, trans_a, trans_b); + } else { + auto input_B_shape = getShape(blobs[0]); +- auto input_B_node = std::make_shared(ngraph::element::f32, input_B_shape, blobs[0].data); +- matmul = std::make_shared(input_A_node, input_B_node, trans_a, trans_b); ++ auto input_B_node = std::make_shared(ov::element::f32, input_B_shape, blobs[0].data); ++ matmul = std::make_shared(input_A_node, input_B_node, trans_a, trans_b); + } + + return Ptr(new InfEngineNgraphNode(matmul)); +diff --git a/modules/dnn/src/layers/max_unpooling_layer.cpp b/modules/dnn/src/layers/max_unpooling_layer.cpp +index 7ed6c64ae8..d81d585d4e 100644 +--- a/modules/dnn/src/layers/max_unpooling_layer.cpp ++++ b/modules/dnn/src/layers/max_unpooling_layer.cpp +@@ -200,29 +200,29 @@ public: + getMemoryShapes(inpShapes, 1, outShapes, internals); + + Mat zeros = Mat::zeros(1, total(outShapes[0]), CV_32F); +- auto zeroInp = std::make_shared(ngraph::element::f32, ngraph::Shape{zeros.total()}, zeros.data); ++ auto zeroInp = std::make_shared(ov::element::f32, ov::Shape{zeros.total()}, zeros.data); + + int newShape = -1; +- features = std::make_shared( ++ features = std::make_shared( + features, +- std::make_shared(ngraph::element::i32, ngraph::Shape{1}, &newShape), ++ std::make_shared(ov::element::i32, ov::Shape{1}, &newShape), + true + ); +- indices = std::make_shared( ++ indices = std::make_shared( + indices, +- std::make_shared(ngraph::element::i32, ngraph::Shape{1}, &newShape), ++ std::make_shared(ov::element::i32, ov::Shape{1}, &newShape), + true + ); +- if (indices.get_element_type() != ngraph::element::i32 && indices.get_element_type() != ngraph::element::i64) { +- indices = std::make_shared(indices, ngraph::element::i64); ++ if (indices.get_element_type() != ov::element::i32 && indices.get_element_type() != ov::element::i64) { ++ indices = std::make_shared(indices, ov::element::i64); + } + + int axis = 0; +- std::shared_ptr unpool = std::make_shared(zeroInp, indices, features, +- std::make_shared(ngraph::element::i32, ngraph::Shape{1}, &axis)); ++ std::shared_ptr unpool = std::make_shared(zeroInp, indices, features, ++ std::make_shared(ov::element::i32, ov::Shape{1}, &axis)); + +- auto shape = std::make_shared(ngraph::element::i32, ngraph::Shape{outShapes[0].size()}, outShapes[0].data()); +- unpool = std::make_shared(unpool, shape, true); ++ auto shape = std::make_shared(ov::element::i32, ov::Shape{outShapes[0].size()}, outShapes[0].data()); ++ unpool = std::make_shared(unpool, shape, true); + + return Ptr(new InfEngineNgraphNode(unpool)); + } +diff --git a/modules/dnn/src/layers/mvn_layer.cpp b/modules/dnn/src/layers/mvn_layer.cpp +index 43c33d82af..69a5bc8b1a 100644 +--- a/modules/dnn/src/layers/mvn_layer.cpp ++++ b/modules/dnn/src/layers/mvn_layer.cpp +@@ -336,15 +336,11 @@ public: + const std::vector >& nodes) CV_OVERRIDE + { + auto& ieInpNode = nodes[0].dynamicCast()->node; +-#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2021_2) +- auto mvn = std::make_shared(ieInpNode, acrossChannels, normVariance, eps); +-#else + int64_t start_axis = acrossChannels ? 1 : 2; + std::vector axes_v(ieInpNode.get_shape().size() - start_axis); + std::iota(axes_v.begin(), axes_v.end(), start_axis); +- auto axes = std::make_shared(ngraph::element::i64, ngraph::Shape{axes_v.size()}, axes_v.data()); +- auto mvn = std::make_shared(ieInpNode, axes, normVariance, eps, ngraph::op::MVNEpsMode::INSIDE_SQRT); +-#endif ++ auto axes = std::make_shared(ov::element::i64, ov::Shape{axes_v.size()}, axes_v.data()); ++ auto mvn = std::make_shared(ieInpNode, axes, normVariance, eps, ov::op::MVNEpsMode::INSIDE_SQRT); + return Ptr(new InfEngineNgraphNode(mvn)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/nary_eltwise_layers.cpp b/modules/dnn/src/layers/nary_eltwise_layers.cpp +index c988ec69f2..b20148ac31 100644 +--- a/modules/dnn/src/layers/nary_eltwise_layers.cpp ++++ b/modules/dnn/src/layers/nary_eltwise_layers.cpp +@@ -897,7 +897,6 @@ public: + CV_Assert(inputs.size()); + return inputs.size() * total(outputs[0]); + } +- + #ifdef HAVE_DNN_NGRAPH + virtual Ptr initNgraph(const std::vector >& inputs, const std::vector >& nodes) CV_OVERRIDE + { +@@ -907,22 +906,30 @@ public: + + if (inp0.get_element_type() != inp1.get_element_type()) { + auto dtype = preferableTarget == DNN_TARGET_OPENCL_FP16 || preferableTarget == DNN_TARGET_MYRIAD ? +- ngraph::element::f16 : ngraph::element::f32; ++ ov::element::f16 : ov::element::f32; + if (inp0.get_element_type() != dtype) +- inp0 = std::make_shared(inp0, dtype); ++ inp0 = std::make_shared(inp0, dtype); + if (inp1.get_element_type() != dtype) +- inp1 = std::make_shared(inp1, dtype); ++ inp1 = std::make_shared(inp1, dtype); + } + +- std::shared_ptr node; ++ std::shared_ptr node; + if (op == OPERATION::ADD) +- node = std::make_shared(inp0, inp1); ++ node = std::make_shared(inp0, inp1); + else if (op == OPERATION::PROD) +- node = std::make_shared(inp0, inp1); ++ node = std::make_shared(inp0, inp1); + else if (op == OPERATION::GREATER_EQUAL) +- node = std::make_shared(inp0, inp1); ++ node = std::make_shared(inp0, inp1); + else if (op == OPERATION::LESS_EQUAL) +- node = std::make_shared(inp0, inp1); ++ node = std::make_shared(inp0, inp1); ++ // Ideally we should do this but int32 internal blobs are converted to float32 data type in inference. ++ // TODO: Remove data type convertion when we have type inference. ++ else if (op == OPERATION::MOD) { ++ auto inp0_i64 = std::make_shared(inp0, ov::element::i64); ++ auto inp1_i64 = std::make_shared(inp1, ov::element::i64); ++ auto mod = std::make_shared(inp0_i64, inp1_i64); ++ node = std::make_shared(mod, ov::element::f32); ++ } + else + CV_Error(Error::StsNotImplemented, "Operation is not implemented for nGraph backend"); + return Ptr(new InfEngineNgraphNode(node)); +diff --git a/modules/dnn/src/layers/normalize_bbox_layer.cpp b/modules/dnn/src/layers/normalize_bbox_layer.cpp +index 431eeab82d..5dfb5d128b 100644 +--- a/modules/dnn/src/layers/normalize_bbox_layer.cpp ++++ b/modules/dnn/src/layers/normalize_bbox_layer.cpp +@@ -283,8 +283,8 @@ public: + axes_data.resize(ieInpNode.get_shape().size() - 1); + std::iota(axes_data.begin(), axes_data.end(), 1); + } +- auto axes = std::make_shared(ngraph::element::i64, ngraph::Shape{axes_data.size()}, axes_data); +- auto norm = std::make_shared(ieInpNode, axes, epsilon, ngraph::op::EpsMode::ADD); ++ auto axes = std::make_shared(ov::element::i64, ov::Shape{axes_data.size()}, axes_data); ++ auto norm = std::make_shared(ieInpNode, axes, epsilon, ov::op::EpsMode::ADD); + + CV_Assert(blobs.empty() || numChannels == blobs[0].total()); + std::vector shape(ieInpNode.get_shape().size(), 1); +@@ -292,13 +292,9 @@ public: + shape[1] = numChannels; + if (!blobs.empty()) + { +- auto weight = std::make_shared( +- ngraph::element::f32, ngraph::Shape(shape), blobs[0].data); +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2021_2) +- auto mul = std::make_shared(norm, weight, ngraph::op::AutoBroadcastType::NUMPY); +-#else +- auto mul = std::make_shared(norm, weight, ngraph::op::AutoBroadcastType::NUMPY); +-#endif ++ auto weight = std::make_shared( ++ ov::element::f32, ov::Shape(shape), blobs[0].data); ++ auto mul = std::make_shared(norm, weight, ov::op::AutoBroadcastType::NUMPY); + return Ptr(new InfEngineNgraphNode(mul)); + } + return Ptr(new InfEngineNgraphNode(norm)); +diff --git a/modules/dnn/src/layers/padding_layer.cpp b/modules/dnn/src/layers/padding_layer.cpp +index f66d44b222..8bb8ab663d 100644 +--- a/modules/dnn/src/layers/padding_layer.cpp ++++ b/modules/dnn/src/layers/padding_layer.cpp +@@ -278,14 +278,14 @@ public: + begins[i] = static_cast(paddings[i].first); + ends[i] = static_cast(paddings[i].second); + } +- auto padding_below = std::make_shared(ngraph::element::i64, ngraph::Shape{begins.size()}, begins.data()); +- auto padding_above = std::make_shared(ngraph::element::i64, ngraph::Shape{ends.size()}, ends.data()); +- auto pad_mode = paddingType == "constant" ? ngraph::op::PadMode::CONSTANT : ngraph::op::PadMode::REFLECT; // SYMMETRIC +- auto arg_pad_value = std::make_shared(ngraph::element::f32, ngraph::Shape{}, &paddingValue);; ++ auto padding_below = std::make_shared(ov::element::i64, ov::Shape{begins.size()}, begins.data()); ++ auto padding_above = std::make_shared(ov::element::i64, ov::Shape{ends.size()}, ends.data()); ++ auto pad_mode = paddingType == "constant" ? ov::op::PadMode::CONSTANT : ov::op::PadMode::REFLECT; // SYMMETRIC ++ auto arg_pad_value = std::make_shared(ov::element::f32, ov::Shape{}, &paddingValue);; + + auto pad = paddingType == "constant" ? +- std::make_shared(ieInpNode, padding_below, padding_above, arg_pad_value, pad_mode) : +- std::make_shared(ieInpNode, padding_below, padding_above, pad_mode); ++ std::make_shared(ieInpNode, padding_below, padding_above, arg_pad_value, pad_mode) : ++ std::make_shared(ieInpNode, padding_below, padding_above, pad_mode); + return Ptr(new InfEngineNgraphNode(pad)); + } + #endif +diff --git a/modules/dnn/src/layers/permute_layer.cpp b/modules/dnn/src/layers/permute_layer.cpp +index 4e6ca2543d..a4f9181d45 100644 +--- a/modules/dnn/src/layers/permute_layer.cpp ++++ b/modules/dnn/src/layers/permute_layer.cpp +@@ -475,9 +475,9 @@ public: + { + auto& ieInpNode = nodes[0].dynamicCast()->node; + std::vector order(_order.begin(), _order.end()); +- auto tr_axes = std::make_shared(ngraph::element::i64, +- ngraph::Shape({order.size()}), order.data()); +- auto transpose = std::make_shared(ieInpNode, tr_axes); ++ auto tr_axes = std::make_shared(ov::element::i64, ++ ov::Shape({order.size()}), order.data()); ++ auto transpose = std::make_shared(ieInpNode, tr_axes); + return Ptr(new InfEngineNgraphNode(transpose)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/pooling_layer.cpp b/modules/dnn/src/layers/pooling_layer.cpp +index fb980c4152..92c7a7f72c 100644 +--- a/modules/dnn/src/layers/pooling_layer.cpp ++++ b/modules/dnn/src/layers/pooling_layer.cpp +@@ -51,13 +51,8 @@ + + #ifdef HAVE_DNN_NGRAPH + #include "../ie_ngraph.hpp" +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) +-#include +-#include +-#else +-#include +-#include +-#endif ++#include ++#include + #endif + + #include "../op_vkcom.hpp" +@@ -588,20 +583,20 @@ public: + CV_Assert_N((inputs.size() == 1 && (type == MAX || type == AVE || type == SUM)) || inputs.size() == 2, nodes.size() == inputs.size()); + auto& ieInpNode = nodes[0].dynamicCast()->node; + +- ngraph::op::PadType pad_type = ngraph::op::PadType::EXPLICIT; ++ ov::op::PadType pad_type = ov::op::PadType::EXPLICIT; + if (!padMode.empty()) +- pad_type = padMode == "VALID" ? ngraph::op::PadType::VALID : ngraph::op::PadType::SAME_UPPER; ++ pad_type = padMode == "VALID" ? ov::op::PadType::VALID : ov::op::PadType::SAME_UPPER; + +- auto rounding_type = ceilMode ? ngraph::op::RoundingType::CEIL : ngraph::op::RoundingType::FLOOR; ++ auto rounding_type = ceilMode ? ov::op::RoundingType::CEIL : ov::op::RoundingType::FLOOR; + if (type == AVE) { + auto exclude_pad = !avePoolPaddedArea; +- auto ave_pool = std::make_shared(ieInpNode, ngraph::Strides(strides), +- ngraph::Shape(pads_begin), ngraph::Shape(pads_end), ngraph::Shape(kernel_size), ++ auto ave_pool = std::make_shared(ieInpNode, ov::Strides(strides), ++ ov::Shape(pads_begin), ov::Shape(pads_end), ov::Shape(kernel_size), + exclude_pad, rounding_type, pad_type); + return Ptr(new InfEngineNgraphNode(ave_pool)); + } + else if (type == SUM) { +- ngraph::Shape inpShape = ieInpNode.get_shape(); ++ ov::Shape inpShape = ieInpNode.get_shape(); + CV_Assert(inpShape.size() == 2 + kernel_size.size()); + std::vector axes; + for (size_t i = 0; i < kernel_size.size(); i++) +@@ -609,37 +604,33 @@ public: + if (inpShape[2 + i] == kernel_size[i]) + axes.push_back(2 + i); + } +- auto reduction_axes = std::make_shared(ngraph::element::i64, ngraph::Shape{axes.size()}, axes); +- auto reduce_sum = std::make_shared(ieInpNode, reduction_axes, true); ++ auto reduction_axes = std::make_shared(ov::element::i64, ov::Shape{axes.size()}, axes); ++ auto reduce_sum = std::make_shared(ieInpNode, reduction_axes, true); + return Ptr(new InfEngineNgraphNode(reduce_sum)); + } + else if (type == MAX) { +- std::shared_ptr max_pool; ++ std::shared_ptr max_pool; + if (computeMaxIdx) { +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + std::vector dilations(kernel_size.size(), 1); +- max_pool = std::make_shared(ieInpNode, ngraph::Strides(strides), ngraph::Strides(dilations), +- ngraph::Shape(pads_begin), ngraph::Shape(pads_end), ngraph::Shape(kernel_size), ++ max_pool = std::make_shared(ieInpNode, ov::Strides(strides), ov::Strides(dilations), ++ ov::Shape(pads_begin), ov::Shape(pads_end), ov::Shape(kernel_size), + rounding_type, pad_type); +-#else +- CV_Error(Error::StsNotImplemented, "OpenVINO MaxPool with indices"); +-#endif + } else { +- max_pool = std::make_shared(ieInpNode, ngraph::Strides(strides), +- ngraph::Shape(pads_begin), ngraph::Shape(pads_end), ngraph::Shape(kernel_size), ++ max_pool = std::make_shared(ieInpNode, ov::Strides(strides), ++ ov::Shape(pads_begin), ov::Shape(pads_end), ov::Shape(kernel_size), + rounding_type, pad_type); + } + return Ptr(new InfEngineNgraphNode(max_pool)); + } + else if (type == ROI) { + auto& coords = nodes[1].dynamicCast()->node; +- auto roi = std::make_shared(ieInpNode, coords, +- ngraph::Shape{(size_t)pooledSize.height, (size_t)pooledSize.width}, spatialScale, "max"); ++ auto roi = std::make_shared(ieInpNode, coords, ++ ov::Shape{(size_t)pooledSize.height, (size_t)pooledSize.width}, spatialScale, "max"); + return Ptr(new InfEngineNgraphNode(roi)); + } + else if (type == PSROI) { + auto& coords = nodes[1].dynamicCast()->node; +- auto psroi = std::make_shared(ieInpNode, coords, ++ auto psroi = std::make_shared(ieInpNode, coords, + (size_t)psRoiOutChannels, (size_t)pooledSize.width, spatialScale, 1, 1, "average"); + return Ptr(new InfEngineNgraphNode(psroi)); + } +diff --git a/modules/dnn/src/layers/prior_box_layer.cpp b/modules/dnn/src/layers/prior_box_layer.cpp +index bf25927480..4cfffb6095 100644 +--- a/modules/dnn/src/layers/prior_box_layer.cpp ++++ b/modules/dnn/src/layers/prior_box_layer.cpp +@@ -47,13 +47,8 @@ + + #ifdef HAVE_DNN_NGRAPH + #include "../ie_ngraph.hpp" +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) +-#include +-#include +-#else +-#include +-#include +-#endif ++#include ++#include + #endif + + #include "../op_vkcom.hpp" +@@ -513,23 +508,23 @@ public: + CV_Assert(nodes.size() == 2); + auto layer = nodes[0].dynamicCast()->node; + auto image = nodes[1].dynamicCast()->node; +- auto layer_shape = std::make_shared(layer); +- auto image_shape = std::make_shared(image); ++ auto layer_shape = std::make_shared(layer); ++ auto image_shape = std::make_shared(image); + +- auto lower_bounds = std::make_shared(ngraph::element::i64, ngraph::Shape{1}, std::vector{2}); +- auto upper_bounds = std::make_shared(ngraph::element::i64, ngraph::Shape{1}, std::vector{4}); +- auto strides = std::make_shared(ngraph::element::i64, ngraph::Shape{1}, std::vector{1}); ++ auto lower_bounds = std::make_shared(ov::element::i64, ov::Shape{1}, std::vector{2}); ++ auto upper_bounds = std::make_shared(ov::element::i64, ov::Shape{1}, std::vector{4}); ++ auto strides = std::make_shared(ov::element::i64, ov::Shape{1}, std::vector{1}); + +- auto slice_layer = std::make_shared(layer_shape, ++ auto slice_layer = std::make_shared(layer_shape, + lower_bounds, upper_bounds, strides, std::vector{}, std::vector{}); +- auto slice_image = std::make_shared(image_shape, ++ auto slice_image = std::make_shared(image_shape, + lower_bounds, upper_bounds, strides, std::vector{}, std::vector{}); + + if (_explicitSizes) + { + CV_Assert_N(!_boxWidths.empty(), !_boxHeights.empty(), !_variance.empty()); + CV_Assert(_boxWidths.size() == _boxHeights.size()); +- ngraph::op::PriorBoxClusteredAttrs attrs; ++ ov::op::v0::PriorBoxClustered::Attributes attrs; + attrs.widths = _boxWidths; + attrs.heights = _boxHeights; + attrs.clip = _clip; +@@ -539,14 +534,14 @@ public: + attrs.step_widths = _stepX; + attrs.variances = _variance; + +- auto priorBox = std::make_shared(slice_layer, slice_image, attrs); +- auto axis = std::make_shared(ngraph::element::i64, ngraph::Shape{1}, std::vector{0}); +- auto unsqueeze = std::make_shared(priorBox, axis); ++ auto priorBox = std::make_shared(slice_layer, slice_image, attrs); ++ auto axis = std::make_shared(ov::element::i64, ov::Shape{1}, std::vector{0}); ++ auto unsqueeze = std::make_shared(priorBox, axis); + return Ptr(new InfEngineNgraphNode(unsqueeze)); + } + else + { +- ngraph::op::PriorBoxAttrs attrs; ++ ov::op::v0::PriorBox::Attributes attrs; + attrs.min_size = _minSize; + attrs.max_size = _maxSize; + // doesn't work with empty aspectRatio +@@ -560,9 +555,9 @@ public: + attrs.step = _stepX; + attrs.scale_all_sizes = !_aspectRatios.empty(); + +- auto priorBox = std::make_shared(slice_layer, slice_image, attrs); +- auto axis = std::make_shared(ngraph::element::i64, ngraph::Shape{1}, std::vector{0}); +- auto unsqueeze = std::make_shared(priorBox, axis); ++ auto priorBox = std::make_shared(slice_layer, slice_image, attrs); ++ auto axis = std::make_shared(ov::element::i64, ov::Shape{1}, std::vector{0}); ++ auto unsqueeze = std::make_shared(priorBox, axis); + return Ptr(new InfEngineNgraphNode(unsqueeze)); + } + } +diff --git a/modules/dnn/src/layers/proposal_layer.cpp b/modules/dnn/src/layers/proposal_layer.cpp +index 2f2a33cc6f..c7baf7870c 100644 +--- a/modules/dnn/src/layers/proposal_layer.cpp ++++ b/modules/dnn/src/layers/proposal_layer.cpp +@@ -10,11 +10,7 @@ + + #ifdef HAVE_DNN_NGRAPH + #include "../ie_ngraph.hpp" +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) +-#include +-#else +-#include +-#endif ++#include + #endif + + namespace cv { namespace dnn { +@@ -344,7 +340,7 @@ public: + const std::vector >& nodes) CV_OVERRIDE + { + CV_Assert(nodes.size() == 3); +- ngraph::op::ProposalAttrs attr; ++ ov::op::v0::Proposal::Attributes attr; + attr.base_size = baseSize; + attr.nms_thresh = nmsThreshold; + attr.feat_stride = featStride; +@@ -367,12 +363,12 @@ public: + auto& image_shape = nodes[2].dynamicCast()->node; + + CV_Assert_N(image_shape.get_shape().size() == 2, image_shape.get_shape().front() == 1); +- auto shape = std::make_shared(ngraph::element::i64, +- ngraph::Shape{1}, ++ auto shape = std::make_shared(ov::element::i64, ++ ov::Shape{1}, + std::vector{(int64_t)image_shape.get_shape().back()}); +- auto reshape = std::make_shared(image_shape, shape, true); ++ auto reshape = std::make_shared(image_shape, shape, true); + +- auto proposal = std::make_shared(class_probs, class_logits, reshape, attr); ++ auto proposal = std::make_shared(class_probs, class_logits, reshape, attr); + return Ptr(new InfEngineNgraphNode(proposal)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/region_layer.cpp b/modules/dnn/src/layers/region_layer.cpp +index 38b809e0f9..5eecc9139d 100644 +--- a/modules/dnn/src/layers/region_layer.cpp ++++ b/modules/dnn/src/layers/region_layer.cpp +@@ -60,7 +60,6 @@ + using namespace cv::dnn::cuda4dnn; + #endif + +- + namespace cv + { + namespace dnn +@@ -122,7 +121,7 @@ public: + { + #ifdef HAVE_DNN_NGRAPH + if (backendId == DNN_BACKEND_INFERENCE_ENGINE_NGRAPH) +- return INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2020_2) && preferableTarget != DNN_TARGET_MYRIAD && new_coords == 0; ++ return preferableTarget != DNN_TARGET_MYRIAD && new_coords == 0; + #endif + #ifdef HAVE_CUDA + if (backendId == DNN_BACKEND_CUDA) +@@ -473,55 +472,55 @@ public: + + int64_t cols = b * h * w * anchors; + int64_t rows = c / anchors; +- auto shape_node = std::make_shared(ngraph::element::i64, ngraph::Shape{2}, std::vector{cols, rows}); +- auto tr_axes = std::make_shared(ngraph::element::i64, ngraph::Shape{2}, std::vector{1, 0}); ++ auto shape_node = std::make_shared(ov::element::i64, ov::Shape{2}, std::vector{cols, rows}); ++ auto tr_axes = std::make_shared(ov::element::i64, ov::Shape{2}, std::vector{1, 0}); + +- std::shared_ptr input2d; ++ std::shared_ptr input2d; + { +- input2d = std::make_shared(input, shape_node, true); +- input2d = std::make_shared(input2d, tr_axes); ++ input2d = std::make_shared(input, shape_node, true); ++ input2d = std::make_shared(input2d, tr_axes); + } + +- std::shared_ptr region; ++ std::shared_ptr region; + { +- auto new_axes = std::make_shared(ngraph::element::i64, ngraph::Shape{4}, std::vector{0, 3, 1, 2}); +- auto tr_input = std::make_shared(input, new_axes); ++ auto new_axes = std::make_shared(ov::element::i64, ov::Shape{4}, std::vector{0, 3, 1, 2}); ++ auto tr_input = std::make_shared(input, new_axes); + + std::vector anchors_vec(blobs[0].ptr(), blobs[0].ptr() + blobs[0].total()); + std::vector mask(anchors, 1); +- region = std::make_shared(tr_input, coords, classes, anchors, useSoftmax, mask, 1, 3, anchors_vec); ++ region = std::make_shared(tr_input, coords, classes, anchors, useSoftmax, mask, 1, 3, anchors_vec); + + auto tr_shape = tr_input->get_shape(); +- auto shape_as_inp = std::make_shared(ngraph::element::i64, +- ngraph::Shape{tr_shape.size()}, ++ auto shape_as_inp = std::make_shared(ov::element::i64, ++ ov::Shape{tr_shape.size()}, + std::vector(tr_shape.begin(), tr_shape.end())); + +- region = std::make_shared(region, shape_as_inp, true); +- new_axes = std::make_shared(ngraph::element::i64, ngraph::Shape{4}, std::vector{0, 2, 3, 1}); +- region = std::make_shared(region, new_axes); ++ region = std::make_shared(region, shape_as_inp, true); ++ new_axes = std::make_shared(ov::element::i64, ov::Shape{4}, std::vector{0, 2, 3, 1}); ++ region = std::make_shared(region, new_axes); + +- region = std::make_shared(region, shape_node, true); +- region = std::make_shared(region, tr_axes); ++ region = std::make_shared(region, shape_node, true); ++ region = std::make_shared(region, tr_axes); + } + +- auto strides = std::make_shared(ngraph::element::i64, ngraph::Shape{2}, std::vector{1, 1}); ++ auto strides = std::make_shared(ov::element::i64, ov::Shape{2}, std::vector{1, 1}); + std::vector boxes_shape{b, anchors, h, w}; +- auto shape_3d = std::make_shared(ngraph::element::i64, ngraph::Shape{boxes_shape.size()}, boxes_shape.data()); ++ auto shape_3d = std::make_shared(ov::element::i64, ov::Shape{boxes_shape.size()}, boxes_shape.data()); + +- ngraph::Shape box_broad_shape{1, (size_t)anchors, (size_t)h, (size_t)w}; +- auto scale_x_y_node = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &scale_x_y); +- auto shift_node = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, std::vector{0.5}); ++ ov::Shape box_broad_shape{1, (size_t)anchors, (size_t)h, (size_t)w}; ++ auto scale_x_y_node = std::make_shared(ov::element::f32, ov::Shape{1}, &scale_x_y); ++ auto shift_node = std::make_shared(ov::element::f32, ov::Shape{1}, std::vector{0.5}); + +- auto axis = ngraph::op::Constant::create(ngraph::element::i64, ngraph::Shape{}, {0}); +- auto splits = ngraph::op::Constant::create(ngraph::element::i64, ngraph::Shape{5}, {1, 1, 1, 1, rows - 4}); +- auto split = std::make_shared(input2d, axis, splits); +- std::shared_ptr box_x; ++ auto axis = ov::op::v0::Constant::create(ov::element::i64, ov::Shape{}, {0}); ++ auto splits = ov::op::v0::Constant::create(ov::element::i64, ov::Shape{5}, {1, 1, 1, 1, rows - 4}); ++ auto split = std::make_shared(input2d, axis, splits); ++ std::shared_ptr box_x; + { +- box_x = std::make_shared(split->output(0)); +- box_x = std::make_shared(box_x, shift_node, ngraph::op::AutoBroadcastType::NUMPY); +- box_x = std::make_shared(box_x, scale_x_y_node, ngraph::op::AutoBroadcastType::NUMPY); +- box_x = std::make_shared(box_x, shift_node, ngraph::op::AutoBroadcastType::NUMPY); +- box_x = std::make_shared(box_x, shape_3d, true); ++ box_x = std::make_shared(split->output(0)); ++ box_x = std::make_shared(box_x, shift_node, ov::op::AutoBroadcastType::NUMPY); ++ box_x = std::make_shared(box_x, scale_x_y_node, ov::op::AutoBroadcastType::NUMPY); ++ box_x = std::make_shared(box_x, shift_node, ov::op::AutoBroadcastType::NUMPY); ++ box_x = std::make_shared(box_x, shape_3d, true); + + std::vector x_indices(w * h * anchors); + auto begin = x_indices.begin(); +@@ -534,20 +533,20 @@ public: + { + std::copy(begin, begin + w * anchors, begin + j * w * anchors); + } +- auto horiz = std::make_shared(ngraph::element::f32, box_broad_shape, x_indices.data()); +- box_x = std::make_shared(box_x, horiz, ngraph::op::AutoBroadcastType::NUMPY); ++ auto horiz = std::make_shared(ov::element::f32, box_broad_shape, x_indices.data()); ++ box_x = std::make_shared(box_x, horiz, ov::op::AutoBroadcastType::NUMPY); + +- auto cols_node = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, std::vector{float(w)}); +- box_x = std::make_shared(box_x, cols_node, ngraph::op::AutoBroadcastType::NUMPY); ++ auto cols_node = std::make_shared(ov::element::f32, ov::Shape{1}, std::vector{float(w)}); ++ box_x = std::make_shared(box_x, cols_node, ov::op::AutoBroadcastType::NUMPY); + } + +- std::shared_ptr box_y; ++ std::shared_ptr box_y; + { +- box_y = std::make_shared(split->output(1)); +- box_y = std::make_shared(box_y, shift_node, ngraph::op::AutoBroadcastType::NUMPY); +- box_y = std::make_shared(box_y, scale_x_y_node, ngraph::op::AutoBroadcastType::NUMPY); +- box_y = std::make_shared(box_y, shift_node, ngraph::op::AutoBroadcastType::NUMPY); +- box_y = std::make_shared(box_y, shape_3d, true); ++ box_y = std::make_shared(split->output(1)); ++ box_y = std::make_shared(box_y, shift_node, ov::op::AutoBroadcastType::NUMPY); ++ box_y = std::make_shared(box_y, scale_x_y_node, ov::op::AutoBroadcastType::NUMPY); ++ box_y = std::make_shared(box_y, shift_node, ov::op::AutoBroadcastType::NUMPY); ++ box_y = std::make_shared(box_y, shape_3d, true); + + std::vector y_indices(h * anchors); + for (int i = 0; i < h; i++) +@@ -555,13 +554,13 @@ public: + std::fill(y_indices.begin() + i * anchors, y_indices.begin() + (i + 1) * anchors, i); + } + +- auto vert = std::make_shared(ngraph::element::f32, ngraph::Shape{1, (size_t)anchors, (size_t)h, 1}, y_indices.data()); +- box_y = std::make_shared(box_y, vert, ngraph::op::AutoBroadcastType::NUMPY); +- auto rows_node = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, std::vector{float(h)}); +- box_y = std::make_shared(box_y, rows_node, ngraph::op::AutoBroadcastType::NUMPY); ++ auto vert = std::make_shared(ov::element::f32, ov::Shape{1, (size_t)anchors, (size_t)h, 1}, y_indices.data()); ++ box_y = std::make_shared(box_y, vert, ov::op::AutoBroadcastType::NUMPY); ++ auto rows_node = std::make_shared(ov::element::f32, ov::Shape{1}, std::vector{float(h)}); ++ box_y = std::make_shared(box_y, rows_node, ov::op::AutoBroadcastType::NUMPY); + } + +- std::shared_ptr box_w, box_h; ++ std::shared_ptr box_w, box_h; + { + int hNorm, wNorm; + if (nodes.size() > 1) +@@ -596,53 +595,53 @@ public: + std::copy(bias_h.begin(), bias_h.begin() + h * anchors, bias_h.begin() + i * h * anchors); + } + +- box_w = std::make_shared(split->output(2)); +- box_w = std::make_shared(box_w, shape_3d, true); +- auto anchor_w_node = std::make_shared(ngraph::element::f32, box_broad_shape, bias_w.data()); +- box_w = std::make_shared(box_w, anchor_w_node, ngraph::op::AutoBroadcastType::NUMPY); ++ box_w = std::make_shared(split->output(2)); ++ box_w = std::make_shared(box_w, shape_3d, true); ++ auto anchor_w_node = std::make_shared(ov::element::f32, box_broad_shape, bias_w.data()); ++ box_w = std::make_shared(box_w, anchor_w_node, ov::op::AutoBroadcastType::NUMPY); + +- box_h = std::make_shared(split->output(3)); +- box_h = std::make_shared(box_h, shape_3d, true); +- auto anchor_h_node = std::make_shared(ngraph::element::f32, box_broad_shape, bias_h.data()); +- box_h = std::make_shared(box_h, anchor_h_node, ngraph::op::AutoBroadcastType::NUMPY); ++ box_h = std::make_shared(split->output(3)); ++ box_h = std::make_shared(box_h, shape_3d, true); ++ auto anchor_h_node = std::make_shared(ov::element::f32, box_broad_shape, bias_h.data()); ++ box_h = std::make_shared(box_h, anchor_h_node, ov::op::AutoBroadcastType::NUMPY); + } + +- auto region_splits = ngraph::op::Constant::create(ngraph::element::i64, ngraph::Shape{3}, {4, 1, rows - 5}); +- auto region_split = std::make_shared(region, axis, region_splits); ++ auto region_splits = ov::op::v0::Constant::create(ov::element::i64, ov::Shape{3}, {4, 1, rows - 5}); ++ auto region_split = std::make_shared(region, axis, region_splits); + +- std::shared_ptr scale; ++ std::shared_ptr scale; + { + float thr = classfix == -1 ? 0.5 : 0; +- auto thresh_node = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, std::vector{thr}); +- auto mask = std::make_shared(region_split->output(1), thresh_node); +- auto zero_node = std::make_shared(ngraph::element::f32, mask->get_shape(), std::vector(cols, 0)); +- scale = std::make_shared(mask, zero_node, region_split->output(1)); ++ auto thresh_node = std::make_shared(ov::element::f32, ov::Shape{1}, std::vector{thr}); ++ auto mask = std::make_shared(region_split->output(1), thresh_node); ++ auto zero_node = std::make_shared(ov::element::f32, mask->get_shape(), std::vector(cols, 0)); ++ scale = std::make_shared(mask, zero_node, region_split->output(1)); + } + +- std::shared_ptr probs; ++ std::shared_ptr probs; + { +- probs = std::make_shared(region_split->output(2), scale, ngraph::op::AutoBroadcastType::NUMPY); +- auto thresh_node = std::make_shared(ngraph::element::f32, ngraph::Shape{1}, &thresh); +- auto mask = std::make_shared(probs, thresh_node); +- auto zero_node = std::make_shared(ngraph::element::f32, mask->get_shape(), std::vector((rows - 5) * cols, 0)); +- probs = std::make_shared(mask, probs, zero_node); ++ probs = std::make_shared(region_split->output(2), scale, ov::op::AutoBroadcastType::NUMPY); ++ auto thresh_node = std::make_shared(ov::element::f32, ov::Shape{1}, &thresh); ++ auto mask = std::make_shared(probs, thresh_node); ++ auto zero_node = std::make_shared(ov::element::f32, mask->get_shape(), std::vector((rows - 5) * cols, 0)); ++ probs = std::make_shared(mask, probs, zero_node); + } + + +- auto concat_shape = std::make_shared(ngraph::element::i64, ngraph::Shape{2}, std::vector{1, cols}); +- box_x = std::make_shared(box_x, concat_shape, true); +- box_y = std::make_shared(box_y, concat_shape, true); +- box_w = std::make_shared(box_w, concat_shape, true); +- box_h = std::make_shared(box_h, concat_shape, true); ++ auto concat_shape = std::make_shared(ov::element::i64, ov::Shape{2}, std::vector{1, cols}); ++ box_x = std::make_shared(box_x, concat_shape, true); ++ box_y = std::make_shared(box_y, concat_shape, true); ++ box_w = std::make_shared(box_w, concat_shape, true); ++ box_h = std::make_shared(box_h, concat_shape, true); + +- ngraph::NodeVector inp_nodes{box_x, box_y, box_w, box_h, scale, probs}; +- std::shared_ptr result = std::make_shared(inp_nodes, 0); +- result = std::make_shared(result, tr_axes); ++ ov::NodeVector inp_nodes{box_x, box_y, box_w, box_h, scale, probs}; ++ std::shared_ptr result = std::make_shared(inp_nodes, 0); ++ result = std::make_shared(result, tr_axes); + if (b > 1) + { + std::vector sizes{b, static_cast(result->get_shape()[0]) / b, static_cast(result->get_shape()[1])}; +- auto shape_node = std::make_shared(ngraph::element::i64, ngraph::Shape{sizes.size()}, sizes.data()); +- result = std::make_shared(result, shape_node, true); ++ auto shape_node = std::make_shared(ov::element::i64, ov::Shape{sizes.size()}, sizes.data()); ++ result = std::make_shared(result, shape_node, true); + } + + return Ptr(new InfEngineNgraphNode(result)); +diff --git a/modules/dnn/src/layers/reorg_layer.cpp b/modules/dnn/src/layers/reorg_layer.cpp +index ac7d1abfb1..4a8686bae1 100644 +--- a/modules/dnn/src/layers/reorg_layer.cpp ++++ b/modules/dnn/src/layers/reorg_layer.cpp +@@ -52,11 +52,7 @@ + #include "../op_inf_engine.hpp" + #ifdef HAVE_DNN_NGRAPH + #include "../ie_ngraph.hpp" +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) +-#include +-#else +-#include +-#endif ++#include + #endif + + #include "../op_cuda.hpp" +@@ -205,7 +201,7 @@ public: + const std::vector >& nodes) CV_OVERRIDE + { + auto& ieInpNode = nodes[0].dynamicCast()->node; +- auto reorg = std::make_shared(ieInpNode, ngraph::Strides{(size_t)reorgStride}); ++ auto reorg = std::make_shared(ieInpNode, ov::Strides{(size_t)reorgStride}); + return Ptr(new InfEngineNgraphNode(reorg)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/reshape_layer.cpp b/modules/dnn/src/layers/reshape_layer.cpp +index a72236c472..f259629e96 100644 +--- a/modules/dnn/src/layers/reshape_layer.cpp ++++ b/modules/dnn/src/layers/reshape_layer.cpp +@@ -369,9 +369,9 @@ public: + auto& ieInpNode = nodes[0].dynamicCast()->node; + + std::vector out(outShapes[0].begin(), outShapes[0].end()); +- auto shape = std::make_shared(ngraph::element::i64, +- ngraph::Shape{out.size()}, out.data()); +- auto reshape = std::make_shared(ieInpNode, shape, true); ++ auto shape = std::make_shared(ov::element::i64, ++ ov::Shape{out.size()}, out.data()); ++ auto reshape = std::make_shared(ieInpNode, shape, true); + return Ptr(new InfEngineNgraphNode(reshape)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/resize_layer.cpp b/modules/dnn/src/layers/resize_layer.cpp +index fe27748319..12a3b613e1 100644 +--- a/modules/dnn/src/layers/resize_layer.cpp ++++ b/modules/dnn/src/layers/resize_layer.cpp +@@ -13,11 +13,7 @@ + + #ifdef HAVE_DNN_NGRAPH + #include "../ie_ngraph.hpp" +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) +-#include +-#else +-#include +-#endif ++#include + #endif + + #ifdef HAVE_CUDA +@@ -376,81 +372,39 @@ public: + { + auto& ieInpNode = nodes[0].dynamicCast()->node; + +-#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2021_2) +- ngraph::op::InterpolateAttrs attrs; +- attrs.pads_begin.push_back(0); +- attrs.pads_end.push_back(0); +- attrs.axes = ngraph::AxisSet{2, 3}; +- attrs.align_corners = alignCorners; +- +- if (interpolation == "nearest") { +- attrs.mode = "nearest"; +- attrs.antialias = false; +- } else if (interpolation == "bilinear") { +- attrs.mode = "linear"; +- } else { +- CV_Error(Error::StsNotImplemented, "Unsupported interpolation: " + interpolation); +- } +- +- std::vector shape = {outHeight, outWidth}; +- auto out_shape = std::make_shared(ngraph::element::i64, ngraph::Shape{2}, shape.data()); +- auto interp = std::make_shared(ieInpNode, out_shape, attrs); +-#else +- ngraph::op::v4::Interpolate::InterpolateAttrs attrs; ++ ov::op::v4::Interpolate::InterpolateAttrs attrs; + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + if (interpolation == "nearest") { +- attrs.mode = ngraph::op::v4::Interpolate::InterpolateMode::NEAREST; +- attrs.coordinate_transformation_mode = ngraph::op::v4::Interpolate::CoordinateTransformMode::HALF_PIXEL; ++ attrs.mode = ov::op::v4::Interpolate::InterpolateMode::NEAREST; ++ attrs.coordinate_transformation_mode = ov::op::v4::Interpolate::CoordinateTransformMode::HALF_PIXEL; + } else if (interpolation == "bilinear") { +- attrs.mode = ngraph::op::v4::Interpolate::InterpolateMode::LINEAR_ONNX; +- attrs.coordinate_transformation_mode = ngraph::op::v4::Interpolate::CoordinateTransformMode::ASYMMETRIC; ++ attrs.mode = ov::op::v4::Interpolate::InterpolateMode::LINEAR_ONNX; ++ attrs.coordinate_transformation_mode = ov::op::v4::Interpolate::CoordinateTransformMode::ASYMMETRIC; + } else { + CV_Error(Error::StsNotImplemented, format("Unsupported interpolation: %s", interpolation.c_str())); + } +- attrs.shape_calculation_mode = ngraph::op::v4::Interpolate::ShapeCalcMode::SIZES; ++ attrs.shape_calculation_mode = ov::op::v4::Interpolate::ShapeCalcMode::SIZES; + + CV_Assert(!halfPixelCenters || !alignCorners); + if (halfPixelCenters) { +- attrs.coordinate_transformation_mode = ngraph::op::v4::Interpolate::CoordinateTransformMode::HALF_PIXEL; ++ attrs.coordinate_transformation_mode = ov::op::v4::Interpolate::CoordinateTransformMode::HALF_PIXEL; + } else if (alignCorners) { +- attrs.coordinate_transformation_mode = ngraph::op::v4::Interpolate::CoordinateTransformMode::ALIGN_CORNERS; ++ attrs.coordinate_transformation_mode = ov::op::v4::Interpolate::CoordinateTransformMode::ALIGN_CORNERS; + } + +- attrs.nearest_mode = ngraph::op::v4::Interpolate::NearestMode::ROUND_PREFER_FLOOR; +-#else +- if (interpolation == "nearest") { +- attrs.mode = ngraph::op::v4::Interpolate::InterpolateMode::nearest; +- attrs.coordinate_transformation_mode = ngraph::op::v4::Interpolate::CoordinateTransformMode::half_pixel; +- } else if (interpolation == "bilinear") { +- attrs.mode = ngraph::op::v4::Interpolate::InterpolateMode::linear_onnx; +- attrs.coordinate_transformation_mode = ngraph::op::v4::Interpolate::CoordinateTransformMode::asymmetric; +- } else { +- CV_Error(Error::StsNotImplemented, format("Unsupported interpolation: %s", interpolation.c_str())); +- } +- attrs.shape_calculation_mode = ngraph::op::v4::Interpolate::ShapeCalcMode::sizes; ++ attrs.nearest_mode = ov::op::v4::Interpolate::NearestMode::ROUND_PREFER_FLOOR; + +- CV_Assert(!halfPixelCenters || !alignCorners); +- if (halfPixelCenters) { +- attrs.coordinate_transformation_mode = ngraph::op::v4::Interpolate::CoordinateTransformMode::half_pixel; +- } else if (alignCorners) { +- attrs.coordinate_transformation_mode = ngraph::op::v4::Interpolate::CoordinateTransformMode::align_corners; +- } +- +- attrs.nearest_mode = ngraph::op::v4::Interpolate::NearestMode::round_prefer_floor; +-#endif // OpenVINO >= 2022.1 + + std::vector shape = {outHeight, outWidth}; +- auto out_shape = std::make_shared(ngraph::element::i64, ngraph::Shape{2}, shape.data()); ++ auto out_shape = std::make_shared(ov::element::i64, ov::Shape{2}, shape.data()); + + auto& input_shape = ieInpNode.get_shape(); + CV_Assert_N(input_shape[2] != 0, input_shape[3] != 0); + std::vector scales = {static_cast(outHeight) / input_shape[2], static_cast(outWidth) / input_shape[3]}; +- auto scales_shape = std::make_shared(ngraph::element::f32, ngraph::Shape{2}, scales.data()); ++ auto scales_shape = std::make_shared(ov::element::f32, ov::Shape{2}, scales.data()); + +- auto axes = std::make_shared(ngraph::element::i64, ngraph::Shape{2}, std::vector{2, 3}); +- auto interp = std::make_shared(ieInpNode, out_shape, scales_shape, axes, attrs); +-#endif ++ auto axes = std::make_shared(ov::element::i64, ov::Shape{2}, std::vector{2, 3}); ++ auto interp = std::make_shared(ieInpNode, out_shape, scales_shape, axes, attrs); + return Ptr(new InfEngineNgraphNode(interp)); + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/layers/scale_layer.cpp b/modules/dnn/src/layers/scale_layer.cpp +index 2a4e1a05d5..00ca4322f8 100644 +--- a/modules/dnn/src/layers/scale_layer.cpp ++++ b/modules/dnn/src/layers/scale_layer.cpp +@@ -331,7 +331,7 @@ public: + virtual Ptr initNgraph(const std::vector >& inputs, const std::vector >& nodes) CV_OVERRIDE + { + auto ieInpNode0 = nodes[0].dynamicCast()->node; +- ngraph::Output ieInpNode1; ++ ov::Output ieInpNode1; + if (nodes.size() > 1) + ieInpNode1 = nodes[1].dynamicCast()->node; + +@@ -346,31 +346,26 @@ public: + int cAxis = normalize_axis(axis, shape.size()); + shape[cAxis] = numChannels; + +- std::shared_ptr node; ++ std::shared_ptr node; + if (hasWeights) + { +- ngraph::Output weight = blobs.empty() ? ieInpNode1 : +- std::make_shared(ngraph::element::f32, ngraph::Shape(shape), blobs[0].data); +- +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2021_2) +- node = std::make_shared(ieInpNode0, weight, ngraph::op::AutoBroadcastType::NUMPY); +-#else +- node = std::make_shared(ieInpNode0, weight, ngraph::op::AutoBroadcastType::NUMPY); +-#endif ++ ov::Output weight = blobs.empty() ? ieInpNode1 : ++ std::make_shared(ov::element::f32, ov::Shape(shape), blobs[0].data); ++ node = std::make_shared(ieInpNode0, weight, ov::op::AutoBroadcastType::NUMPY); + } + if (hasBias || !hasWeights) + { +- ngraph::Output bias; ++ ov::Output bias; + if (hasBias) + { + bias = blobs.empty() ? ieInpNode1 : +- std::make_shared(ngraph::element::f32, +- ngraph::Shape(shape), blobs.back().data); ++ std::make_shared(ov::element::f32, ++ ov::Shape(shape), blobs.back().data); + } + else +- bias = std::make_shared(ngraph::element::f32, +- ngraph::Shape(shape), std::vector(numChannels, 0).data()); +- node = std::make_shared(node, bias, ngraph::op::AutoBroadcastType::NUMPY); ++ bias = std::make_shared(ov::element::f32, ++ ov::Shape(shape), std::vector(numChannels, 0).data()); ++ node = std::make_shared(node, bias, ov::op::AutoBroadcastType::NUMPY); + } + return Ptr(new InfEngineNgraphNode(node)); + } +diff --git a/modules/dnn/src/layers/slice_layer.cpp b/modules/dnn/src/layers/slice_layer.cpp +index c44d18182e..1947635214 100644 +--- a/modules/dnn/src/layers/slice_layer.cpp ++++ b/modules/dnn/src/layers/slice_layer.cpp +@@ -768,14 +768,14 @@ public: + dims.push_back(finalSliceRanges[0][i].end); + } + +- auto lower_bounds = std::make_shared(ngraph::element::i64, +- ngraph::Shape{offsets.size()}, offsets.data()); +- auto upper_bounds = std::make_shared(ngraph::element::i64, +- ngraph::Shape{dims.size()}, dims.data()); +- auto strides = std::make_shared(ngraph::element::i64, +- ngraph::Shape{dims.size()}, std::vector((int64_t)dims.size(), 1)); +- +- auto slice = std::make_shared(ieInpNode, ++ auto lower_bounds = std::make_shared(ov::element::i64, ++ ov::Shape{offsets.size()}, offsets.data()); ++ auto upper_bounds = std::make_shared(ov::element::i64, ++ ov::Shape{dims.size()}, dims.data()); ++ auto strides = std::make_shared(ov::element::i64, ++ ov::Shape{dims.size()}, std::vector((int64_t)dims.size(), 1)); ++ ++ auto slice = std::make_shared(ieInpNode, + lower_bounds, upper_bounds, strides, std::vector{}, std::vector{}); + + return Ptr(new InfEngineNgraphNode(slice)); +diff --git a/modules/dnn/src/layers/softmax_layer.cpp b/modules/dnn/src/layers/softmax_layer.cpp +index ff559e980a..56abc888e3 100644 +--- a/modules/dnn/src/layers/softmax_layer.cpp ++++ b/modules/dnn/src/layers/softmax_layer.cpp +@@ -314,9 +314,9 @@ public: + auto& ieInpNode = nodes[0].dynamicCast()->node; + int axis = normalize_axis(axisRaw, ieInpNode.get_shape().size()); + if (logSoftMax) { +- return new InfEngineNgraphNode(std::make_shared(ieInpNode, axis)); ++ return new InfEngineNgraphNode(std::make_shared(ieInpNode, axis)); + } else { +- return new InfEngineNgraphNode(std::make_shared(ieInpNode, axis)); ++ return new InfEngineNgraphNode(std::make_shared(ieInpNode, axis)); + } + } + #endif // HAVE_DNN_NGRAPH +diff --git a/modules/dnn/src/net_openvino.cpp b/modules/dnn/src/net_openvino.cpp +index adcfea60f0..501a596e5d 100644 +--- a/modules/dnn/src/net_openvino.cpp ++++ b/modules/dnn/src/net_openvino.cpp +@@ -9,6 +9,12 @@ + #include + #include + ++#include "op_inf_engine.hpp" ++ ++#ifdef HAVE_INF_ENGINE ++#include ++#endif ++ + #include "net_impl.hpp" + + #include "backend.hpp" +@@ -146,7 +152,7 @@ public: + //string dump(bool forceAllocation = false) const override; + + static +- Net createNetworkFromModelOptimizer(InferenceEngine::CNNNetwork& ieNet); ++ Net createNetworkFromModelOptimizer(std::shared_ptr& ieNet); + + }; // NetImplOpenVINO + +@@ -320,11 +326,6 @@ void NetImplOpenVINO::initBackend(const std::vector& blobsToKeep_) + return; + } + +-#if INF_ENGINE_VER_MAJOR_LT(INF_ENGINE_RELEASE_2022_1) +- bool supportsCPUFallback = !isArmComputePlugin() && (preferableTarget == DNN_TARGET_CPU || +- openvino::checkTarget(DNN_TARGET_CPU)); +-#endif +- + // Build Inference Engine networks from sets of layers that support this + // backend. Split a whole model on several Inference Engine networks if + // some of layers are not implemented. +@@ -342,49 +343,8 @@ void NetImplOpenVINO::initBackend(const std::vector& blobsToKeep_) + + bool fused = ld.skip; + Ptr layer = ld.layerInstance; +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + if (ld.id == 0) + continue; +-#else +- if (!fused && !layer->supportBackend(preferableBackend)) +- { +- CV_LOG_DEBUG(NULL, "DNN/IE: NOT supported!"); +- bool customizable = ld.id != 0 && supportsCPUFallback; +- +- // TODO: there is a bug in Myriad plugin with custom layers shape infer. +- if (preferableTarget == DNN_TARGET_MYRIAD || preferableTarget == DNN_TARGET_HDDL) +- { +- for (int i = 0; customizable && i < ld.inputBlobs.size(); ++i) +- { +- customizable = ld.inputBlobs[i]->size[0] == 1; +- } +- } +- +- if (preferableTarget == DNN_TARGET_OPENCL) +- customizable &= ld.type != "Eltwise"; +- +- if (!customizable) +- { +- CV_LOG_DEBUG(NULL, "DNN/IE: NOT customizable!"); +- addNgraphOutputs(ld); +- net = Ptr(); +- layer->preferableTarget = DNN_TARGET_CPU; +- +- for (int i = 0; i < ld.inputBlobsId.size(); ++i) +- { +- LayerData& inpLd = layers[ld.inputBlobsId[i].lid]; +- Ptr inpNode = inpLd.backendNodes[preferableBackend]; +- if (!inpNode.empty()) +- { +- Ptr ieNode = inpNode.dynamicCast(); +- CV_Assert(!ieNode.empty()); +- ieNode->net->addOutput(ieNode); +- } +- } +- continue; +- } +- } +-#endif + ld.skip = true; // Initially skip all Inference Engine supported layers. + + // Create a new network if one of inputs from different Inference Engine graph. +@@ -480,25 +440,14 @@ void NetImplOpenVINO::initBackend(const std::vector& blobsToKeep_) + continue; + + // Handle parameters from other subnets. Output port is not used in this case +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) +- if ((ngraph::op::is_parameter(ngraph_input_node) || ngraph::op::is_constant(ngraph_input_node)) && +-#else +- if ((ngraph_input_node->is_parameter() || ngraph_input_node->is_constant()) && +-#endif +- +- ngraph_input_node->get_output_size() == 1) ++ if ((ov::op::util::is_parameter(ngraph_input_node) || ov::op::util::is_constant(ngraph_input_node)) && ++ ngraph_input_node->get_output_size() == 1) + { + inputNodes[i] = Ptr(new InfEngineNgraphNode(ngraph_input_node)); + continue; + } + CV_CheckLT((size_t)oid, ngraph_input_node->get_output_size(), ""); +-#if INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_4) + inputNodes[i] = new InfEngineNgraphNode(ngraph_input_node->output(oid)); +-#elif INF_ENGINE_VER_MAJOR_GT(INF_ENGINE_RELEASE_2020_3) +- inputNodes[i] = Ptr(new InfEngineNgraphNode(ieInpNode->node->get_output_as_single_output_node(oid))); +-#else +- inputNodes[i] = Ptr(new InfEngineNgraphNode(ieInpNode->node->get_output_as_single_output_node(oid, false))); +-#endif + } + + if (layer->supportBackend(preferableBackend)) +@@ -606,9 +555,7 @@ void NetImplOpenVINO::initBackend(const std::vector& blobsToKeep_) + } + } + } +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + CV_Assert(uniqueNets.size() == 1); +-#endif + } + + +@@ -708,18 +655,15 @@ void switchToOpenVINOBackend(Net& net) + + + /*static*/ +-Net NetImplOpenVINO::createNetworkFromModelOptimizer(InferenceEngine::CNNNetwork& ieNet) ++Net NetImplOpenVINO::createNetworkFromModelOptimizer(std::shared_ptr& ieNet) + { + CV_TRACE_FUNCTION(); + + CV_TRACE_REGION("register_inputs"); + +- auto ngraphFunction = ieNet.getFunction(); +- CV_Assert(ngraphFunction); +- + std::vector inputsNames; + std::vector inp_shapes; +- for (auto& it : ngraphFunction->get_parameters()) ++ for (auto& it : ieNet->get_parameters()) + { + inputsNames.push_back(it->get_friendly_name()); + std::vector dims = it->get_shape(); +@@ -728,16 +672,9 @@ Net NetImplOpenVINO::createNetworkFromModelOptimizer(InferenceEngine::CNNNetwork + // nGraph models produce output "Result" layers which have "/sink_port" suffix in their names. + // Their inputs are actual model outputs and we change friendly name to it. + // By this workaround, we produce similar outputs names comparing to ieNet.getOutputsInfo() +- for (int i = 0; i < ngraphFunction->get_output_size(); ++i) { +- auto res = ngraphFunction->output(i); +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) ++ for (int i = 0; i < ieNet->get_output_size(); ++i) { ++ auto res = ieNet->output(i); + const std::string& name = res.get_any_name(); +-#else +- auto out = res.get_node()->input(0).get_source_output(); +- std::string name = out.get_node()->get_friendly_name(); +- if (out.get_node()->get_output_size() > 1) +- name += "." + std::to_string(out.get_index()); +-#endif + if (res.get_node()->get_friendly_name() != name) + res.get_node()->set_friendly_name(name); + } +@@ -759,7 +696,7 @@ Net NetImplOpenVINO::createNetworkFromModelOptimizer(InferenceEngine::CNNNetwork + + Ptr backendNode; + { +- auto fake_node = std::make_shared(ngraph::element::f32, ngraph::Shape {}); ++ auto fake_node = std::make_shared(ov::element::f32, ov::Shape {}); + Ptr backendNodeNGraph(new InfEngineNgraphNode(fake_node)); + backendNodeNGraph->net = Ptr(new InfEngineNgraphNet(openvino_impl, ieNet)); + backendNode = backendNodeNGraph; +@@ -767,9 +704,9 @@ Net NetImplOpenVINO::createNetworkFromModelOptimizer(InferenceEngine::CNNNetwork + + CV_TRACE_REGION_NEXT("register_outputs"); + +- std::vector> ngraphOperations = ngraphFunction->get_ops(); ++ std::vector> ngraphOperations = ieNet->get_ops(); + +- for (auto& it : ngraphFunction->get_results()) ++ for (auto& it : ieNet->get_results()) + { + CV_TRACE_REGION("output"); + const auto& outputName = it->get_friendly_name(); +@@ -834,11 +771,11 @@ Net openvino_readNetwork(const String& modelPath, const String& binPath) + { + FPDenormalsIgnoreHintScope fp_denormals_ignore_scope; + +- InferenceEngine::Core& ie = getCore(""); +- InferenceEngine::CNNNetwork ieNet; ++ ov::Core& ie = getCore(""); ++ std::shared_ptr ieNet; + try + { +- ieNet = ie.ReadNetwork(modelPath, binPath); ++ ieNet = ie.read_model(modelPath, binPath); + } + catch (const std::exception& e) + { +@@ -857,22 +794,15 @@ Net openvino_readNetwork( + { + FPDenormalsIgnoreHintScope fp_denormals_ignore_scope; + +- InferenceEngine::Core& ie = getCore(""); ++ ov::Core& ie = getCore(""); + + std::string model; model.assign((char*)bufferModelConfigPtr, bufferModelConfigSize); + +- InferenceEngine::CNNNetwork ieNet; ++ std::shared_ptr ieNet; + try + { +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + ov::Tensor weights_blob(ov::element::u8, {bufferWeightsSize}, (void*)bufferWeightsPtr); + ieNet = ie.read_model(model, weights_blob); +-#else +- InferenceEngine::TensorDesc tensorDesc(InferenceEngine::Precision::U8, { bufferWeightsSize }, InferenceEngine::Layout::C); +- InferenceEngine::Blob::CPtr weights_blob = InferenceEngine::make_shared_blob(tensorDesc, (uint8_t*)bufferWeightsPtr, bufferWeightsSize); +- +- ieNet = ie.ReadNetwork(model, weights_blob); +-#endif + } + catch (const std::exception& e) + { +diff --git a/modules/dnn/src/op_inf_engine.cpp b/modules/dnn/src/op_inf_engine.cpp +index f9e3993d20..04f1da7c71 100644 +--- a/modules/dnn/src/op_inf_engine.cpp ++++ b/modules/dnn/src/op_inf_engine.cpp +@@ -10,7 +10,7 @@ + #include + + #ifdef HAVE_INF_ENGINE +-#include ++#include + #elif defined(ENABLE_PLUGINS) + // using plugin API + #include "backend.hpp" +@@ -39,60 +39,6 @@ cv::String setInferenceEngineBackendType(const cv::String& newBackendType) + + CV__DNN_INLINE_NS_END + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) +-namespace InferenceEngine { +- +-CNNNetwork::CNNNetwork() {} +- +-CNNNetwork::CNNNetwork(std::shared_ptr model) : model(model) {} +- +-std::shared_ptr CNNNetwork::getFunction() const { +- return model; +-} +- +-void CNNNetwork::serialize(const std::string& xmlPath, const std::string& binPath) { +- ov::pass::Serialize(xmlPath, binPath).run_on_model(model); +-} +- +-void CNNNetwork::reshape(const std::map >& shapes) { +- std::map partialShapes; +- for (const auto& it : shapes) { +- ov::PartialShape shape; +- shape.insert(shape.begin(), it.second.begin(), it.second.end()); +- partialShapes.insert({it.first, shape}); +- } +- model->reshape(partialShapes); +-} +- +-std::vector Core::GetAvailableDevices() { +- return get_available_devices(); +-} +- +-void Core::UnregisterPlugin(const std::string& id) { +- unload_plugin(id); +-} +- +-CNNNetwork Core::ReadNetwork(const std::string& xmlPath, const std::string& binPath) { +- return read_model(xmlPath, binPath); +-} +- +-ExecutableNetwork Core::LoadNetwork(CNNNetwork net, const std::string& device, +- const std::map& config) { +- ov::AnyMap props; +- for (const auto& it : config) { +- props.insert(it); +- } +- return compile_model(net.getFunction(), device, props); +-} +- +-ExecutableNetwork::ExecutableNetwork() {} +- +-ExecutableNetwork::ExecutableNetwork(const ov::CompiledModel& copy) : CompiledModel(copy) {} +- +-ov::InferRequest ExecutableNetwork::CreateInferRequest() { return create_infer_request(); } +- +-} // namespace InferenceEngine +- + Mat infEngineBlobToMat(const ov::Tensor& blob) + { + std::vector dims = blob.get_shape(); +@@ -118,67 +64,40 @@ void infEngineBlobsToMats(const ov::TensorVector& blobs, + mats[i] = infEngineBlobToMat(blobs[i]); + } + +-#else +- +-Mat infEngineBlobToMat(const InferenceEngine::Blob::Ptr& blob) +-{ +- // NOTE: Inference Engine sizes are reversed. +- std::vector dims = blob->getTensorDesc().getDims(); +- std::vector size(dims.begin(), dims.end()); +- auto precision = blob->getTensorDesc().getPrecision(); +- +- int type = -1; +- switch (precision) +- { +- case InferenceEngine::Precision::FP32: type = CV_32F; break; +- case InferenceEngine::Precision::U8: type = CV_8U; break; +- default: +- CV_Error(Error::StsNotImplemented, "Unsupported blob precision"); +- } +- return Mat(size, type, (void*)blob->buffer()); +-} +- +-void infEngineBlobsToMats(const std::vector& blobs, +- std::vector& mats) +-{ +- mats.resize(blobs.size()); +- for (int i = 0; i < blobs.size(); ++i) +- mats[i] = infEngineBlobToMat(blobs[i]); +-} +-#endif // OpenVINO >= 2022.1 + + static bool init_IE_plugins() + { + // load and hold IE plugins +- static InferenceEngine::Core* init_core = new InferenceEngine::Core(); // 'delete' is never called +- (void)init_core->GetAvailableDevices(); ++ static ov::Core* init_core = new ov::Core(); // 'delete' is never called ++ (void)init_core->get_available_devices(); + return true; + } +-static InferenceEngine::Core& retrieveIECore(const std::string& id, std::map >& cores) ++static ov::Core& retrieveIECore(const std::string& id, std::map >& cores) + { + AutoLock lock(getInitializationMutex()); +- std::map >::iterator i = cores.find(id); ++ std::map >::iterator i = cores.find(id); + if (i == cores.end()) + { +- std::shared_ptr core = std::make_shared(); ++ std::shared_ptr core = std::make_shared(); + cores[id] = core; + return *core.get(); + } + return *(i->second).get(); + } +-static InferenceEngine::Core& create_IE_Core_instance(const std::string& id) ++static ov::Core& create_IE_Core_instance(const std::string& id) + { +- static std::map > cores; ++ static std::map > cores; + return retrieveIECore(id, cores); + } +-static InferenceEngine::Core& create_IE_Core_pointer(const std::string& id) ++static ov::Core& create_IE_Core_pointer(const std::string& id) + { + // load and hold IE plugins +- static std::map >* cores = +- new std::map >(); ++ static std::map >* cores = ++ new std::map >(); + return retrieveIECore(id, *cores); + } +-InferenceEngine::Core& getCore(const std::string& id) ++ ++ov::Core& getCore(const std::string& id) + { + // to make happy memory leak tools use: + // - OPENCV_DNN_INFERENCE_ENGINE_HOLD_PLUGINS=0 +@@ -195,7 +114,7 @@ InferenceEngine::Core& getCore(const std::string& id) + #endif + ); + +- InferenceEngine::Core& core = param_DNN_INFERENCE_ENGINE_CORE_LIFETIME_WORKAROUND ++ ov::Core& core = param_DNN_INFERENCE_ENGINE_CORE_LIFETIME_WORKAROUND + ? create_IE_Core_pointer(id) + : create_IE_Core_instance(id); + return core; +@@ -204,17 +123,13 @@ InferenceEngine::Core& getCore(const std::string& id) + + static bool detectArmPlugin_() + { +- InferenceEngine::Core& ie = getCore("CPU"); +- const std::vector devices = ie.GetAvailableDevices(); ++ ov::Core& ie = getCore("CPU"); ++ const std::vector devices = ie.get_available_devices(); + for (std::vector::const_iterator i = devices.begin(); i != devices.end(); ++i) + { + if (i->find("CPU") != std::string::npos) + { +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + const std::string name = ie.get_property(*i, ov::device::full_name); +-#else +- const std::string name = ie.GetMetric(*i, METRIC_KEY(FULL_DEVICE_NAME)).as(); +-#endif + CV_LOG_INFO(NULL, "CPU plugin: " << name); + return name.find("arm_compute::NEON") != std::string::npos; + } +@@ -228,17 +143,13 @@ static bool detectMyriadX_(const std::string& device) + AutoLock lock(getInitializationMutex()); + + // Lightweight detection +- InferenceEngine::Core& ie = getCore(device); +- const std::vector devices = ie.GetAvailableDevices(); ++ ov::Core& ie = getCore(device); ++ const std::vector devices = ie.get_available_devices(); + for (std::vector::const_iterator i = devices.begin(); i != devices.end(); ++i) + { + if (i->find(device) != std::string::npos) + { +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + const std::string name = ie.get_property(*i, ov::device::full_name); +-#else +- const std::string name = ie.GetMetric(*i, METRIC_KEY(FULL_DEVICE_NAME)).as(); +-#endif + CV_LOG_INFO(NULL, "Myriad device: " << name); + return name.find("MyriadX") != std::string::npos || name.find("Myriad X") != std::string::npos || name.find("HDDL") != std::string::npos; + } +@@ -259,11 +170,11 @@ void resetMyriadDevice() + + AutoLock lock(getInitializationMutex()); + +- InferenceEngine::Core& ie = getCore("MYRIAD"); ++ ov::Core& ie = getCore("MYRIAD"); + try + { +- ie.UnregisterPlugin("MYRIAD"); +- ie.UnregisterPlugin("HETERO"); ++ ie.unload_plugin("MYRIAD"); ++ ie.unload_plugin("HETERO"); + } + catch (...) {} + #endif // HAVE_INF_ENGINE +@@ -276,11 +187,11 @@ void releaseHDDLPlugin() + + AutoLock lock(getInitializationMutex()); + +- InferenceEngine::Core& ie = getCore("HDDL"); ++ ov::Core& ie = getCore("HDDL"); + try + { +- ie.UnregisterPlugin("HDDL"); +- ie.UnregisterPlugin("HETERO"); ++ ie.unload_plugin("HDDL"); ++ ie.unload_plugin("HETERO"); + } + catch (...) {} + #endif // HAVE_INF_ENGINE +@@ -351,7 +262,7 @@ namespace openvino { + bool checkTarget(Target target) + { + // Lightweight detection +- const std::vector devices = getCore("").GetAvailableDevices(); ++ const std::vector devices = getCore("").get_available_devices(); + for (std::vector::const_iterator i = devices.begin(); i != devices.end(); ++i) + { + if (std::string::npos != i->find("MYRIAD") && target == DNN_TARGET_MYRIAD) +diff --git a/modules/dnn/src/op_inf_engine.hpp b/modules/dnn/src/op_inf_engine.hpp +index c5a2e58683..236b21b1a3 100644 +--- a/modules/dnn/src/op_inf_engine.hpp ++++ b/modules/dnn/src/op_inf_engine.hpp +@@ -19,19 +19,13 @@ + + #ifdef HAVE_INF_ENGINE + +-#define INF_ENGINE_RELEASE_2020_2 2020020000 +-#define INF_ENGINE_RELEASE_2020_3 2020030000 +-#define INF_ENGINE_RELEASE_2020_4 2020040000 +-#define INF_ENGINE_RELEASE_2021_1 2021010000 +-#define INF_ENGINE_RELEASE_2021_2 2021020000 +-#define INF_ENGINE_RELEASE_2021_3 2021030000 +-#define INF_ENGINE_RELEASE_2021_4 2021040000 + #define INF_ENGINE_RELEASE_2022_1 2022010000 + #define INF_ENGINE_RELEASE_2023_0 2023000000 ++#define INF_ENGINE_RELEASE_2024_0 2024000000 + + #ifndef INF_ENGINE_RELEASE +-#warning("IE version have not been provided via command-line. Using 2021.4 by default") +-#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2021_4 ++#warning("IE version have not been provided via command-line. Using 2022.1 by default") ++#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2022_1 + #endif + + #define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000)) +@@ -45,13 +39,9 @@ + #pragma GCC diagnostic ignored "-Wsuggest-override" + #endif + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + #include + #include + #include +-#else +-#include +-#endif + + #if defined(__GNUC__) && __GNUC__ >= 5 + //#pragma GCC diagnostic pop +@@ -76,18 +66,10 @@ CV__DNN_INLINE_NS_END + + Backend& getInferenceEngineBackendTypeParam(); + +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) + Mat infEngineBlobToMat(const ov::Tensor& blob); + + void infEngineBlobsToMats(const ov::TensorVector& blobs, + std::vector& mats); +-#else +-Mat infEngineBlobToMat(const InferenceEngine::Blob::Ptr& blob); +- +-void infEngineBlobsToMats(const std::vector& blobs, +- std::vector& mats); +-#endif // OpenVINO >= 2022.1 +- + + CV__DNN_INLINE_NS_BEGIN + +@@ -99,54 +81,7 @@ bool isArmComputePlugin(); + + CV__DNN_INLINE_NS_END + +-// A series of wrappers for classes from OpenVINO API 2.0. +-// Need just for less conditional compilation inserts. +-#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2022_1) +-namespace InferenceEngine { +- +-class CNNNetwork { +-public: +- CNNNetwork(); +- +- CNNNetwork(std::shared_ptr model); +- +- std::shared_ptr getFunction() const; +- +- void serialize(const std::string& xmlPath, const std::string& binPath); +- +- void reshape(const std::map >& shapes); +- +-private: +- std::shared_ptr model = nullptr; +-}; +- +-typedef ov::InferRequest InferRequest; +- +-class ExecutableNetwork : public ov::CompiledModel { +-public: +- ExecutableNetwork(); +- +- ExecutableNetwork(const ov::CompiledModel& copy); +- +- ov::InferRequest CreateInferRequest(); +-}; +- +-class Core : public ov::Core { +-public: +- std::vector GetAvailableDevices(); +- +- void UnregisterPlugin(const std::string& id); +- +- CNNNetwork ReadNetwork(const std::string& xmlPath, const std::string& binPath); +- +- ExecutableNetwork LoadNetwork(CNNNetwork net, const std::string& device, +- const std::map& config); +-}; +- +-} +-#endif // OpenVINO >= 2022.1 +- +-InferenceEngine::Core& getCore(const std::string& id); ++ov::Core& getCore(const std::string& id); + + template + static inline std::vector getShape(const Mat& mat) +diff --git a/modules/dnn/src/op_webnn.hpp b/modules/dnn/src/op_webnn.hpp +index 5b77b10827..6f96289b80 100644 +--- a/modules/dnn/src/op_webnn.hpp ++++ b/modules/dnn/src/op_webnn.hpp +@@ -111,7 +111,7 @@ public: + void addBlobs(const std::vector >& ptrs); + + void createNet(Target targetId); +- // void setNodePtr(std::shared_ptr* ptr); ++ // void setNodePtr(std::shared_ptr* ptr); + + void reset(); + +diff --git a/modules/dnn/test/test_ie_models.cpp b/modules/dnn/test/test_ie_models.cpp +index c6667c7ad2..eff389035d 100644 +--- a/modules/dnn/test/test_ie_models.cpp ++++ b/modules/dnn/test/test_ie_models.cpp +@@ -9,7 +9,6 @@ + #ifdef HAVE_INF_ENGINE + #include + +- + // + // Synchronize headers include statements with src/op_inf_engine.hpp + // +@@ -26,14 +25,11 @@ + #pragma GCC visibility push(default) + #endif + +-#include +-#include +-#include +- + #if defined(__GNUC__) + #pragma GCC visibility pop + #endif + ++#include + + namespace opencv_test { namespace { + +@@ -62,7 +58,6 @@ static void initDLDTDataPath() + + using namespace cv; + using namespace cv::dnn; +-using namespace InferenceEngine; + + struct OpenVINOModelTestCaseInfo + { +@@ -161,27 +156,6 @@ inline static std::string getOpenVINOModel(const std::string &modelName, bool is + return std::string(); + } + +-static inline void genData(const InferenceEngine::TensorDesc& desc, Mat& m, Blob::Ptr& dataPtr) +-{ +- const std::vector& dims = desc.getDims(); +- if (desc.getPrecision() == InferenceEngine::Precision::FP32) +- { +- m.create(std::vector(dims.begin(), dims.end()), CV_32F); +- randu(m, -1, 1); +- dataPtr = make_shared_blob(desc, (float*)m.data); +- } +- else if (desc.getPrecision() == InferenceEngine::Precision::I32) +- { +- m.create(std::vector(dims.begin(), dims.end()), CV_32S); +- randu(m, -100, 100); +- dataPtr = make_shared_blob(desc, (int*)m.data); +- } +- else +- { +- FAIL() << "Unsupported precision: " << desc.getPrecision(); +- } +-} +- + void runIE(Target target, const std::string& xmlPath, const std::string& binPath, + std::map& inputsMap, std::map& outputsMap) + { +@@ -189,25 +163,12 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath + + std::string device_name; + +-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2019010000) +- Core ie; +-#else +- InferenceEnginePluginPtr enginePtr; +- InferencePlugin plugin; +-#endif +- +-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2019030000) +- CNNNetwork net = ie.ReadNetwork(xmlPath, binPath); +-#else +- CNNNetReader reader; +- reader.ReadNetwork(xmlPath); +- reader.ReadWeights(binPath); ++ ov::Core core; + +- CNNNetwork net = reader.getNetwork(); +-#endif ++ auto model = core.read_model(xmlPath, binPath); + +- ExecutableNetwork netExec; +- InferRequest infRequest; ++ ov::CompiledModel compiledModel; ++ ov::InferRequest infRequest; + + try + { +@@ -230,10 +191,6 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath + CV_Error(Error::StsNotImplemented, "Unknown target"); + }; + +-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_LE(2019010000) +- auto dispatcher = InferenceEngine::PluginDispatcher({""}); +- enginePtr = dispatcher.getPluginByDevice(device_name); +-#endif + if (target == DNN_TARGET_CPU || target == DNN_TARGET_FPGA) + { + std::string suffixes[] = {"_avx2", "_sse4", ""}; +@@ -255,68 +212,90 @@ void runIE(Target target, const std::string& xmlPath, const std::string& binPath + #endif // _WIN32 + try + { +- IExtensionPtr extension = make_so_pointer(libName); +-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2019010000) +- ie.AddExtension(extension, device_name); +-#else +- enginePtr->AddExtension(extension, 0); +-#endif ++ core.add_extension(libName); + break; + } + catch(...) {} + } + // Some of networks can work without a library of extra layers. + } +-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GT(2019010000) +- netExec = ie.LoadNetwork(net, device_name); +-#else +- plugin = InferencePlugin(enginePtr); +- netExec = plugin.LoadNetwork(net, {}); +-#endif +- infRequest = netExec.CreateInferRequest(); ++ compiledModel = core.compile_model(model, device_name); ++ infRequest = compiledModel.create_infer_request(); + } + catch (const std::exception& ex) + { + CV_Error(Error::StsAssert, format("Failed to initialize Inference Engine backend: %s", ex.what())); + } + +- // Fill input blobs. ++ // Fill input tensors. + inputsMap.clear(); +- BlobMap inputBlobs; +- for (auto& it : net.getInputsInfo()) ++ for (auto&& it : model->inputs()) + { +- const InferenceEngine::TensorDesc& desc = it.second->getTensorDesc(); +- genData(desc, inputsMap[it.first], inputBlobs[it.first]); ++ auto type = it.get_element_type(); ++ auto shape = it.get_shape(); ++ auto& m = inputsMap[it.get_any_name()]; ++ ++ auto tensor = ov::Tensor(type, shape); ++ if (type == ov::element::f32) ++ { ++ m.create(std::vector(shape.begin(), shape.end()), CV_32F); ++ randu(m, -1, 1); ++ } ++ else if (type == ov::element::i32) ++ { ++ m.create(std::vector(shape.begin(), shape.end()), CV_32S); ++ randu(m, -100, 100); ++ } ++ else ++ { ++ FAIL() << "Unsupported precision: " << type; ++ } ++ std::memcpy(tensor.data(), m.data, tensor.get_byte_size()); ++ + if (cvtest::debugLevel > 0) + { +- const std::vector& dims = desc.getDims(); +- std::cout << "Input: '" << it.first << "' precision=" << desc.getPrecision() << " dims=" << dims.size() << " ["; +- for (auto d : dims) ++ std::cout << "Input: '" << it.get_any_name() << "' precision=" << type << " dims=" << shape << " ["; ++ for (auto d : shape) + std::cout << " " << d; +- std::cout << "] ocv_mat=" << inputsMap[it.first].size << " of " << typeToString(inputsMap[it.first].type()) << std::endl; ++ std::cout << "] ocv_mat=" << inputsMap[it.get_any_name()].size << " of " << typeToString(inputsMap[it.get_any_name()].type()) << std::endl; + } ++ infRequest.set_tensor(it, tensor); + } +- infRequest.SetInput(inputBlobs); ++ infRequest.infer(); ++ + +- // Fill output blobs. ++ // Fill output tensors. + outputsMap.clear(); +- BlobMap outputBlobs; +- for (auto& it : net.getOutputsInfo()) ++ for (const auto& it : model->outputs()) + { +- const InferenceEngine::TensorDesc& desc = it.second->getTensorDesc(); +- genData(desc, outputsMap[it.first], outputBlobs[it.first]); ++ auto type = it.get_element_type(); ++ auto shape = it.get_shape(); ++ auto& m = outputsMap[it.get_any_name()]; ++ ++ auto tensor = infRequest.get_tensor(it); ++ if (type == ov::element::f32) ++ { ++ m.create(std::vector(shape.begin(), shape.end()), CV_32F); ++ } ++ else if (type == ov::element::i32) ++ { ++ m.create(std::vector(shape.begin(), shape.end()), CV_32S); ++ } ++ else ++ { ++ FAIL() << "Unsupported precision: " << type; ++ } ++ std::memcpy(m.data, tensor.data(), tensor.get_byte_size()); ++ + if (cvtest::debugLevel > 0) + { +- const std::vector& dims = desc.getDims(); +- std::cout << "Output: '" << it.first << "' precision=" << desc.getPrecision() << " dims=" << dims.size() << " ["; +- for (auto d : dims) ++ std::cout << "Output: '" << it.get_any_name() << "' precision=" << type << " dims=" << shape << " ["; ++ for (auto d : shape) + std::cout << " " << d; +- std::cout << "] ocv_mat=" << outputsMap[it.first].size << " of " << typeToString(outputsMap[it.first].type()) << std::endl; ++ std::cout << "] ocv_mat=" << outputsMap[it.get_any_name()].size << " of " << typeToString(outputsMap[it.get_any_name()].type()) << std::endl; + } +- } +- infRequest.SetOutput(outputBlobs); + +- infRequest.Infer(); ++ } + } + + void runCV(Backend backendId, Target targetId, const std::string& xmlPath, const std::string& binPath, From aad1a457b97e9006a71bcb6c9c2397c14c993608 Mon Sep 17 00:00:00 2001 From: Mark Harfouche Date: Thu, 21 Mar 2024 07:07:32 -0400 Subject: [PATCH 5/7] remove prototbuf build matrix --- recipe/conda_build_config.yaml | 11 ----------- 1 file changed, 11 deletions(-) diff --git a/recipe/conda_build_config.yaml b/recipe/conda_build_config.yaml index f53695bc..6303092a 100644 --- a/recipe/conda_build_config.yaml +++ b/recipe/conda_build_config.yaml @@ -9,17 +9,6 @@ MACOSX_DEPLOYMENT_TARGET: # [osx and qt_version == 6] MACOSX_SDK_VERSION: # [osx and qt_version == 6] - '12.3' # [osx and qt_version == 6] -# Save the size of our build matrix. -# Build with older protobuf upon request -# https://github.com/conda-forge/libprotobuf-feedstock/issues/198 -# https://github.com/conda-forge/tensorflow-feedstock/issues/378 -# hmaarrfk - 2024/03 - requested to have builds for linux64 -# 4.25.2 is the latest protobuf migration as of 2024/03/11 -# 4.24.4 is the version that tensorflow 2.15 was last built with -libprotobuf: # [linux64] -- '4.25.2' # [linux64] -- '4.24.4' # [linux64] - # As of 2024/03 -- OSX basically never had qt builds. If somebody asks, we can build them # As of 2024/03 -- qt6 works better than qt5 on aarch64. So drop qt5. # As of 2024/03 -- No windows users have expressed concerns about the qt libraries. don't build None From c2ba9b846748b516bf021f988e011cc7be727f4f Mon Sep 17 00:00:00 2001 From: "conda-forge-webservices[bot]" <91080706+conda-forge-webservices[bot]@users.noreply.github.com> Date: Thu, 21 Mar 2024 11:11:03 +0000 Subject: [PATCH 6/7] MNT: Re-rendered with conda-build 24.1.2, conda-smithy 3.32.0, and conda-forge-pinning 2024.03.21.10.02.09 --- .azure-pipelines/azure-pipelines-linux.yml | 8 +-- ...3python3.11.____cpythonqt_versionnone.yaml | 71 ------------------- ...python3.11.____cpythonqt_versionnone.yaml} | 0 .ci_support/migrations/ffmpeg6.yaml | 8 --- README.md | 11 +-- 5 files changed, 4 insertions(+), 94 deletions(-) delete mode 100644 .ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone.yaml rename .ci_support/{linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone.yaml => linux_64_numpy1.23python3.11.____cpythonqt_versionnone.yaml} (100%) delete mode 100644 .ci_support/migrations/ffmpeg6.yaml diff --git a/.azure-pipelines/azure-pipelines-linux.yml b/.azure-pipelines/azure-pipelines-linux.yml index 706a61d6..252c05d7 100755 --- a/.azure-pipelines/azure-pipelines-linux.yml +++ b/.azure-pipelines/azure-pipelines-linux.yml @@ -8,12 +8,8 @@ jobs: vmImage: ubuntu-latest strategy: matrix: - linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone - UPLOAD_PACKAGES: 'True' - DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 - linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone: - CONFIG: linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone + linux_64_numpy1.23python3.11.____cpythonqt_versionnone: + CONFIG: linux_64_numpy1.23python3.11.____cpythonqt_versionnone UPLOAD_PACKAGES: 'True' DOCKER_IMAGE: quay.io/condaforge/linux-anvil-cos7-x86_64 linux_aarch64_numpy1.23python3.11.____cpythonqt_versionnone: diff --git a/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone.yaml deleted file mode 100644 index 42ba37b7..00000000 --- a/.ci_support/linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnone.yaml +++ /dev/null @@ -1,71 +0,0 @@ -c_compiler: -- gcc -c_compiler_version: -- '12' -cdt_name: -- cos7 -channel_sources: -- conda-forge -channel_targets: -- conda-forge main -cxx_compiler: -- gxx -cxx_compiler_version: -- '12' -docker_image: -- quay.io/condaforge/linux-anvil-cos7-x86_64 -ffmpeg: -- '6' -freetype: -- '2' -glib: -- '2' -harfbuzz: -- '8' -hdf5: -- 1.14.3 -jasper: -- '4' -libcblas: -- 3.9 *netlib -libiconv: -- '1' -libjpeg_turbo: -- '3' -liblapack: -- 3.9 *netlib -liblapacke: -- 3.9 *netlib -libopenvino_dev: -- 2024.0.0 -libpng: -- '1.6' -libprotobuf: -- 4.24.4 -libtiff: -- '4.6' -libwebp: -- '1' -numpy: -- '1.23' -openexr: -- '3.2' -pin_run_as_build: - python: - min_pin: x.x - max_pin: x.x -python: -- 3.11.* *_cpython -qt: -- '5.15' -qt_version: -- none -target_platform: -- linux-64 -zip_keys: -- - c_compiler_version - - cxx_compiler_version -- - python - - numpy -zlib: -- '1.2' diff --git a/.ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone.yaml b/.ci_support/linux_64_numpy1.23python3.11.____cpythonqt_versionnone.yaml similarity index 100% rename from .ci_support/linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone.yaml rename to .ci_support/linux_64_numpy1.23python3.11.____cpythonqt_versionnone.yaml diff --git a/.ci_support/migrations/ffmpeg6.yaml b/.ci_support/migrations/ffmpeg6.yaml deleted file mode 100644 index 4fff8dcb..00000000 --- a/.ci_support/migrations/ffmpeg6.yaml +++ /dev/null @@ -1,8 +0,0 @@ -__migrator: - build_number: 1 - kind: version - migration_number: 1 -ffmpeg: -- '5' -- '6' -migrator_ts: 1684252387.6420875 diff --git a/README.md b/README.md index 90dae9b1..806ca5c0 100644 --- a/README.md +++ b/README.md @@ -31,17 +31,10 @@ Current build status - + - - - From 3aa77790837a68059ff558f1b39bdb4f377690e1 Mon Sep 17 00:00:00 2001 From: Ilya Lavrenov Date: Thu, 21 Mar 2024 15:23:33 +0400 Subject: [PATCH 7/7] Added G-API patch --- recipe/meta.yaml | 2 + .../0006-opencv-gapi-openvino.patch | 79 +++++++++++++++++++ 2 files changed, 81 insertions(+) create mode 100644 recipe/patches_opencv/0006-opencv-gapi-openvino.patch diff --git a/recipe/meta.yaml b/recipe/meta.yaml index 8553d354..69030d39 100644 --- a/recipe/meta.yaml +++ b/recipe/meta.yaml @@ -52,6 +52,8 @@ source: - patches_opencv/0004-fix-detection-for-protobuf-23.x.patch # backport of https://github.com/opencv/opencv/pull/25199 - patches_opencv/0005-openvino-2022.1.0-and-newer.patch + # backport of https://github.com/opencv/opencv/pull/24878 + - patches_opencv/0006-opencv-gapi-openvino.patch - url: https://github.com/opencv/opencv_contrib/archive/{{ version }}.tar.gz fn: opencv_contrib-{{ version }}.tar.gz sha256: 8952c45a73b75676c522dd574229f563e43c271ae1d5bbbd26f8e2b6bc1a4dae diff --git a/recipe/patches_opencv/0006-opencv-gapi-openvino.patch b/recipe/patches_opencv/0006-opencv-gapi-openvino.patch new file mode 100644 index 00000000..b24f2424 --- /dev/null +++ b/recipe/patches_opencv/0006-opencv-gapi-openvino.patch @@ -0,0 +1,79 @@ +commit d1d314dcd7d3ec9acde5f6e0104aa4d4ed0e09bf +Author: TolyaTalamanov +Date: Wed Jan 17 13:28:53 2024 +0000 + + Ifdef OpenVINO API 1.0 usage in G-API module + +diff --git a/modules/gapi/src/backends/ie/giebackend.cpp b/modules/gapi/src/backends/ie/giebackend.cpp +index 935f81d275..cdb246e4a2 100644 +--- a/modules/gapi/src/backends/ie/giebackend.cpp ++++ b/modules/gapi/src/backends/ie/giebackend.cpp +@@ -2,7 +2,7 @@ + // It is subject to the license terms in the LICENSE file found in the top-level directory + // of this distribution and at http://opencv.org/license.html. + // +-// Copyright (C) 2018-2023 Intel Corporation ++// Copyright (C) 2018-2024 Intel Corporation + + #include "precomp.hpp" + +@@ -10,7 +10,7 @@ + // (cv::gapi::ie::backend() is still there and is defined always) + #include "backends/ie/giebackend.hpp" + +-#ifdef HAVE_INF_ENGINE ++#if defined HAVE_INF_ENGINE && INF_ENGINE_RELEASE < 2024000000 + + #if INF_ENGINE_RELEASE <= 2019010000 + # error G-API IE module supports only OpenVINO IE >= 2019 R1 +diff --git a/modules/gapi/src/backends/ie/giebackend.hpp b/modules/gapi/src/backends/ie/giebackend.hpp +index c7d938878d..98715fc2db 100644 +--- a/modules/gapi/src/backends/ie/giebackend.hpp ++++ b/modules/gapi/src/backends/ie/giebackend.hpp +@@ -2,7 +2,7 @@ + // It is subject to the license terms in the LICENSE file found in the top-level directory + // of this distribution and at http://opencv.org/license.html. + // +-// Copyright (C) 2018-2020 Intel Corporation ++// Copyright (C) 2018-2024 Intel Corporation + + #ifndef OPENCV_GAPI_GIEBACKEND_HPP + #define OPENCV_GAPI_GIEBACKEND_HPP +@@ -10,7 +10,7 @@ + // Include anyway - cv::gapi::ie::backend() still needs to be defined + #include "opencv2/gapi/infer/ie.hpp" + +-#ifdef HAVE_INF_ENGINE ++#if defined HAVE_INF_ENGINE && INF_ENGINE_RELEASE < 2024000000 + + #include // type_list_index + #include +diff --git a/modules/gapi/src/backends/ie/giebackend/giewrapper.cpp b/modules/gapi/src/backends/ie/giebackend/giewrapper.cpp +index a185e7b8ce..6df8187e16 100644 +--- a/modules/gapi/src/backends/ie/giebackend/giewrapper.cpp ++++ b/modules/gapi/src/backends/ie/giebackend/giewrapper.cpp +@@ -2,9 +2,9 @@ + // It is subject to the license terms in the LICENSE file found in the top-level directory + // of this distribution and at http://opencv.org/license.html. + // +-// Copyright (C) 2020 Intel Corporation ++// Copyright (C) 2020-2024 Intel Corporation + +-#ifdef HAVE_INF_ENGINE ++#if defined HAVE_INF_ENGINE && INF_ENGINE_RELEASE < 2024000000 + + #include + #include +diff --git a/modules/gapi/test/infer/gapi_infer_ie_test.cpp b/modules/gapi/test/infer/gapi_infer_ie_test.cpp +index 92de39abfa..8e91d576aa 100644 +--- a/modules/gapi/test/infer/gapi_infer_ie_test.cpp ++++ b/modules/gapi/test/infer/gapi_infer_ie_test.cpp +@@ -6,7 +6,7 @@ + + #include "../test_precomp.hpp" + +-#ifdef HAVE_INF_ENGINE ++#if defined HAVE_INF_ENGINE && INF_ENGINE_RELEASE < 2024000000 + + #include + #include
VariantStatus
linux_64_libprotobuf4.24.4numpy1.23python3.11.____cpythonqt_versionnonelinux_64_numpy1.23python3.11.____cpythonqt_versionnone - variant - -
linux_64_libprotobuf4.25.2numpy1.23python3.11.____cpythonqt_versionnone - - variant + variant