init commit

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

app.py

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+import cv2
+import numpy as np
+import gradio as gr
+from infer import Model
+
+
+def hex_to_rgb(hex_color, div=255):
+    hex_color = hex_color.lstrip('#')
+    r = int(hex_color[0:2], 16) / div
+    g = int(hex_color[2:4], 16) / div
+    b = int(hex_color[4:6], 16) / div
+
+    return r, g, b
+
+
+def draw_circle(image, color, x, y, radius, thickness):
+
+    circle_color = hex_to_rgb(color, 1)
+
+    overlay = image.copy()
+    overlay = cv2.circle(overlay, (x, y), radius, circle_color, -1)
+    image = cv2.addWeighted(overlay, 0.5, image, 0.5, 0)
+    image = cv2.circle(image, (x, y), radius, circle_color, thickness)
+
+    return image
+
+
+model = Model()
+
+with gr.Blocks() as app:
+
+    with gr.Row():
+
+        original_image = gr.Image(visible=False, type="numpy")
+        input_image = gr.Image(label="Input Image",
+                               sources="upload",
+                               type="numpy",
+                               interactive=True)
+        with gr.Tab("Output Image"):
+            output_image = gr.Image(type="numpy", interactive=False)
+        with gr.Tab("Output Depth Image"):
+            depth_image = gr.Image(type="numpy", interactive=False)
+    with gr.Column():
+        pos_x = gr.Slider(0.0,
+                          1.0,
+                          value=0.5,
+                          step=0.1,
+                          label="X",
+                          interactive=True)
+        pos_y = gr.Slider(0.0,
+                          1.0,
+                          value=0.5,
+                          step=0.1,
+                          label="Y",
+                          interactive=True)
+        pos_z = gr.Slider(-1.0,
+                          1.0,
+                          value=-0.7,
+                          step=0.05,
+                          label="Z",
+                          interactive=True)
+        light = gr.Slider(0.0,
+                          2.0,
+                          value=0.7,
+                          step=0.1,
+                          label="Light Intensity",
+                          interactive=True)
+        color = gr.ColorPicker(value="#FFFFFF",
+                               label="Light Color",
+                               interactive=True)
+
+    def on_upload_image(image, x, y, z, power, color):
+        r, g, b = hex_to_rgb(color)
+        x_ = (x - 0.5) * 2
+        y_ = (-y + 0.5) * 2
+
+        d_img, o_img = model.inference_image(image, x_, y_, z, r, g, b, power)
+        return d_img, o_img, image
+
+    input_image.upload(on_upload_image,
+                       [input_image, pos_x, pos_y, pos_z, light, color],
+                       [depth_image, output_image, original_image])
+
+    def on_change_image(image, x, y, color):
+        x_ = int(x * image.shape[1])
+        y_ = int(y * image.shape[0])
+
+        r = int(max(min(image.shape[0], image.shape[1]) / 10, 10))
+
+        return draw_circle(image, color, x_, y_, r, r // 10)
+
+    original_image.change(on_change_image,
+                          [original_image, pos_x, pos_y, color], [input_image])
+
+    def get_point(image, color, z, power, evt: gr.SelectData):
+        x_ = evt.index[0]
+        y_ = evt.index[1]
+        x = (x_ / image.shape[1])
+        y = (y_ / image.shape[0])
+
+        r = int(max(min(image.shape[0], image.shape[1]) / 10, 10))
+
+        input_image = draw_circle(image, color, x_, y_, r, r // 10)
+        output_image = on_change_parameter(x, y, z, power, color)
+        return output_image, input_image, x, y
+
+    input_image.select(
+        get_point,
+        [original_image, color, pos_z, light],
+        [output_image, input_image, pos_x, pos_y],
+        show_progress="hidden",
+    )
+
+    def on_change_parameter_and_update_image(image, x, y, z, power, color):
+
+        x_ = int(image.shape[1] * x)
+        y_ = int(image.shape[0] * y)
+        r = int(max(min(image.shape[0], image.shape[1]) / 10, 10))
+
+        input_image = draw_circle(image, color, x_, y_, r, r // 10)
+        output_image = on_change_parameter(x, y, z, power, color)
+
+        return input_image, output_image
+
+    def on_change_parameter(x, y, z, power, color):
+        r, g, b = hex_to_rgb(color)
+        xx = (x - 0.5) * 2
+        yy = (-y + 0.5) * 2
+
+        return model.add_light(xx, yy, z, r, g, b, power)
+
+    pos_x.input(on_change_parameter_and_update_image,
+                [original_image, pos_x, pos_y, pos_z, light, color],
+                [input_image, output_image],
+                show_progress="hidden",
+                trigger_mode="always_last")
+    pos_y.input(on_change_parameter_and_update_image,
+                [original_image, pos_x, pos_y, pos_z, light, color],
+                [input_image, output_image],
+                show_progress="hidden",
+                trigger_mode="always_last")
+    pos_z.input(on_change_parameter, [pos_x, pos_y, pos_z, light, color],
+                [output_image],
+                show_progress="hidden",
+                trigger_mode="always_last")
+    light.input(on_change_parameter, [pos_x, pos_y, pos_z, light, color],
+                [output_image],
+                show_progress="hidden",
+                trigger_mode="always_last")
+    color.input(on_change_parameter, [pos_x, pos_y, pos_z, light, color],
+                [output_image],
+                show_progress="hidden",
+                trigger_mode="always_last")
+
+app.queue().launch()