From bda9632d5cfbc6ae266755e8bbc238e83b92c13f Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Thu, 18 May 2023 13:15:18 +0100 Subject: [PATCH 01/85] Update README.md Change CAD 1 version --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c5fa833c1..f1a467840 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/claritychallenge/clarity/main.svg)](https://results.pre-commit.ci/latest/github/claritychallenge/clarity/main) [![Downloads](https://pepy.tech/badge/pyclarity)](https://pepy.tech/project/pyclarity) -[![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.3.2&color=orange)](https://pypi.org/project/pyclarity/0.3.2/) +[![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.3.3&color=orange)](https://pypi.org/project/pyclarity/0.3.3/) [![PyPI](https://img.shields.io/static/v1?label=ICASSP%202023%20Challenge%20-%20pypi&message=v0.2.1&color=orange)](https://pypi.org/project/pyclarity/0.2.1/) [![PyPI](https://img.shields.io/static/v1?label=CEC2%20Challenge%20-%20pypi&message=v0.1.1&color=orange)](https://pypi.org/project/pyclarity/0.1.1/) From abfb956b40f6e44368d0558be0ef1374951aff49 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 30 May 2023 05:04:54 +0000 Subject: [PATCH 02/85] [pre-commit.ci] pre-commit-autoupdate MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/charliermarsh/ruff-pre-commit: v0.0.267 → v0.0.270](https://github.com/charliermarsh/ruff-pre-commit/compare/v0.0.267...v0.0.270) --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index fc3a6dc4f..93491bf71 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -73,7 +73,7 @@ repos: - repo: https://github.com/charliermarsh/ruff-pre-commit # Ruff version. - rev: "v0.0.267" + rev: "v0.0.270" hooks: - id: ruff From 1a743ad24f25d9dd454c7507c719ca5b34fa179f Mon Sep 17 00:00:00 2001 From: Neil Shephard Date: Tue, 30 May 2023 13:38:10 +0100 Subject: [PATCH 03/85] Adding ORDA workflow, tweaking README with badge --- .github/workflows/ORDA.yaml | 28 ++++++++++++++++++++++++++++ README.md | 4 ++-- 2 files changed, 30 insertions(+), 2 deletions(-) create mode 100644 .github/workflows/ORDA.yaml diff --git a/.github/workflows/ORDA.yaml b/.github/workflows/ORDA.yaml new file mode 100644 index 000000000..d9313c05a --- /dev/null +++ b/.github/workflows/ORDA.yaml @@ -0,0 +1,28 @@ +name: Release to ORDA +on: + workflow_dispatch: + release: + types: [published] +jobs: + upload: + runs-on: ubuntu-latest + env: + ARCHIVE_NAME: ${{ github.event.repository.name }}-${{ github.event.release.tag_name }} + steps: + - name: prepare-data-folder + run : mkdir 'data' + - name: download-archive + run: | + curl -sL "${{ github.event.release.zipball_url }}" > "$ARCHIVE_NAME".zip + curl -sL "${{ github.event.release.tarball_url }}" > "$ARCHIVE_NAME".tar.gz + - name: move-archive + run: | + mv "$ARCHIVE_NAME".zip data/ + mv "$ARCHIVE_NAME".tar.gz data/ + - name: upload-to-figshare + uses: figshare/github-upload-action@v1.1 + with: + FIGSHARE_TOKEN: ${{ secrets.FIGSHARE_TOKEN }} + FIGSHARE_ENDPOINT: 'https://api.figshare.com/v2' + FIGSHARE_ARTICLE_ID: 23230694 + DATA_DIR: 'data' diff --git a/README.md b/README.md index c5fa833c1..2d6eef2ad 100644 --- a/README.md +++ b/README.md @@ -18,10 +18,10 @@ [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/claritychallenge/clarity/main.svg)](https://results.pre-commit.ci/latest/github/claritychallenge/clarity/main) [![Downloads](https://pepy.tech/badge/pyclarity)](https://pepy.tech/project/pyclarity) -[![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.3.2&color=orange)](https://pypi.org/project/pyclarity/0.3.2/) +[![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.3.3&color=orange)](https://pypi.org/project/pyclarity/0.3.3/) [![PyPI](https://img.shields.io/static/v1?label=ICASSP%202023%20Challenge%20-%20pypi&message=v0.2.1&color=orange)](https://pypi.org/project/pyclarity/0.2.1/) [![PyPI](https://img.shields.io/static/v1?label=CEC2%20Challenge%20-%20pypi&message=v0.1.1&color=orange)](https://pypi.org/project/pyclarity/0.1.1/) - +[![ORDA](https://img.shields.io/badge/ORDA--DOI-10.15131%2Fshef.data.23230694.v.1-lightgrey)](https://figshare.shef.ac.uk/articles/software/clarity/23230694/1)

From 14a2ec6805dc3912965c7add6553893f780e454b Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 13 Jun 2023 07:09:26 +0000 Subject: [PATCH 04/85] [pre-commit.ci] pre-commit-autoupdate MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/asottile/pyupgrade: v3.4.0 → v3.6.0](https://github.com/asottile/pyupgrade/compare/v3.4.0...v3.6.0) - [github.com/DavidAnson/markdownlint-cli2: v0.7.1 → v0.8.1](https://github.com/DavidAnson/markdownlint-cli2/compare/v0.7.1...v0.8.1) - [github.com/charliermarsh/ruff-pre-commit: v0.0.270 → v0.0.272](https://github.com/charliermarsh/ruff-pre-commit/compare/v0.0.270...v0.0.272) --- .pre-commit-config.yaml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 93491bf71..dfffba6e4 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -20,7 +20,7 @@ repos: - id: check-toml - repo: https://github.com/asottile/pyupgrade - rev: v3.4.0 + rev: v3.6.0 hooks: - id: pyupgrade args: [--py38-plus] @@ -33,7 +33,7 @@ repos: additional_dependencies: ["click==8.0.4"] - repo: https://github.com/DavidAnson/markdownlint-cli2 - rev: v0.7.1 + rev: v0.8.1 hooks: - id: markdownlint-cli2 @@ -73,7 +73,7 @@ repos: - repo: https://github.com/charliermarsh/ruff-pre-commit # Ruff version. - rev: "v0.0.270" + rev: "v0.0.272" hooks: - id: ruff From 34a979794e891ef972a08de0e2dd448ba5def6a4 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 27 Jun 2023 06:57:52 +0000 Subject: [PATCH 05/85] [pre-commit.ci] pre-commit-autoupdate MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/asottile/pyupgrade: v3.6.0 → v3.7.0](https://github.com/asottile/pyupgrade/compare/v3.6.0...v3.7.0) - [github.com/pre-commit/mirrors-mypy: v1.3.0 → v1.4.1](https://github.com/pre-commit/mirrors-mypy/compare/v1.3.0...v1.4.1) - [github.com/charliermarsh/ruff-pre-commit: v0.0.272 → v0.0.275](https://github.com/charliermarsh/ruff-pre-commit/compare/v0.0.272...v0.0.275) --- .pre-commit-config.yaml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index dfffba6e4..19bf70fa0 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -20,7 +20,7 @@ repos: - id: check-toml - repo: https://github.com/asottile/pyupgrade - rev: v3.6.0 + rev: v3.7.0 hooks: - id: pyupgrade args: [--py38-plus] @@ -65,7 +65,7 @@ repos: - id: nbstripout - repo: https://github.com/pre-commit/mirrors-mypy - rev: v1.3.0 + rev: v1.4.1 hooks: - id: mypy args: @@ -73,7 +73,7 @@ repos: - repo: https://github.com/charliermarsh/ruff-pre-commit # Ruff version. - rev: "v0.0.272" + rev: "v0.0.275" hooks: - id: ruff From 3212ed936ff3b51fce5cca54296b6ecd3f120b71 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 18 Jul 2023 08:18:06 +0000 Subject: [PATCH 06/85] [pre-commit.ci] pre-commit-autoupdate MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/asottile/pyupgrade: v3.7.0 → v3.9.0](https://github.com/asottile/pyupgrade/compare/v3.7.0...v3.9.0) - [github.com/psf/black: 23.3.0 → 23.7.0](https://github.com/psf/black/compare/23.3.0...23.7.0) - https://github.com/charliermarsh/ruff-pre-commit → https://github.com/astral-sh/ruff-pre-commit - [github.com/astral-sh/ruff-pre-commit: v0.0.275 → v0.0.278](https://github.com/astral-sh/ruff-pre-commit/compare/v0.0.275...v0.0.278) --- .pre-commit-config.yaml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 19bf70fa0..3670f4fa3 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -20,13 +20,13 @@ repos: - id: check-toml - repo: https://github.com/asottile/pyupgrade - rev: v3.7.0 + rev: v3.9.0 hooks: - id: pyupgrade args: [--py38-plus] - repo: https://github.com/psf/black - rev: 23.3.0 + rev: 23.7.0 hooks: - id: black types: [python] @@ -71,9 +71,9 @@ repos: args: - --explicit-package-bases - - repo: https://github.com/charliermarsh/ruff-pre-commit + - repo: https://github.com/astral-sh/ruff-pre-commit # Ruff version. - rev: "v0.0.275" + rev: "v0.0.278" hooks: - id: ruff From 3d07e1a9b8c2075639d7848aaad4741593244d46 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 25 Jul 2023 07:28:11 +0000 Subject: [PATCH 07/85] [pre-commit.ci] pre-commit-autoupdate MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/astral-sh/ruff-pre-commit: v0.0.278 → v0.0.280](https://github.com/astral-sh/ruff-pre-commit/compare/v0.0.278...v0.0.280) --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 3670f4fa3..7167117a7 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -73,7 +73,7 @@ repos: - repo: https://github.com/astral-sh/ruff-pre-commit # Ruff version. - rev: "v0.0.278" + rev: "v0.0.280" hooks: - id: ruff From 56686d86915f301eae6ad7b07882ea4c29b28280 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Mon, 11 Sep 2023 17:14:33 +0100 Subject: [PATCH 08/85] Script to generate ICASSP 2024 dataset Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/__init__.py | 0 .../generate_dataset/config.yaml | 17 ++ .../generates_at_mic_musdb18.py | 217 ++++++++++++++++++ 3 files changed, 234 insertions(+) create mode 100644 recipes/cad_icassp_2024/__init__.py create mode 100644 recipes/cad_icassp_2024/generate_dataset/config.yaml create mode 100644 recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py diff --git a/recipes/cad_icassp_2024/__init__.py b/recipes/cad_icassp_2024/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/recipes/cad_icassp_2024/generate_dataset/config.yaml b/recipes/cad_icassp_2024/generate_dataset/config.yaml new file mode 100644 index 000000000..70a7ba784 --- /dev/null +++ b/recipes/cad_icassp_2024/generate_dataset/config.yaml @@ -0,0 +1,17 @@ +path: + root: ??? + metadata_dir: ${path.root}/metadata + music_dir: ${path.root}/audio/music # musdb18 dataset + hrtf_dir: ${path.root}/audio/hrtf + scene_file: ${path.metadata_dir}/scenes.train.json + music_file: ${path.metadata_dir}/musdb18.train.json + gain_file: ${path.metadata_dir}/gains.json + head_positions_file: ${path.metadata_dir}/head_positions.json + output_music_dir: ${path.root}/audio/at_mic_music # at microphone musdb18 dataset + output_music_file: ${path.metadata_dir}/at_mic_music.train.json + +sample_rate: 44100 + +hydra: + run: + dir: . diff --git a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py new file mode 100644 index 000000000..2b73780ba --- /dev/null +++ b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py @@ -0,0 +1,217 @@ +""" +Script creates the dataset for the ICASSP 2024 Grand Challenge. + +It takes the music from the MUSDB18 dataset and applies the HRTF signals +to simulate the music at the microphone position. +The output is saved in the same format as the MUSDB18 dataset. + +The script takes as input: + - The metadata of the scenes. + - The metadata of the music. + - The metadata of the head positions. + - The HRTF signals. + - The music signals. + +The script outputs: + - The metadata of the music at the hearing aids microphone. + - The music signals at the hearing aids microphone. +""" +from __future__ import annotations + +# pylint: disable=import-error +import json +import logging +import warnings +from pathlib import Path + +import hydra +import numpy as np +import pyloudnorm as pyln +from numpy import ndarray +from omegaconf import DictConfig +from scipy.signal import lfilter + +from clarity.utils.file_io import read_signal, write_signal + +logger = logging.getLogger(__name__) + + +def apply_hrtf(signal: ndarray, hrtf_left: ndarray, hrtf_right) -> ndarray: + """Applies the Left and Right HRTF to a signal. + + Args: + signal (ndarray): Signal. + hrtf_left (ndarray): Left HRTF. + hrtf_right (ndarray): Right HRTF. + + Returns: + ndarray: Signal with applied HRTF. + """ + output_left_ear = lfilter(hrtf_left[:, 0], 1, signal[:, 0]) + output_right_ear = lfilter(hrtf_left[:, 1], 1, signal[:, 0]) + + output_left_ear += lfilter(hrtf_right[:, 0], 1, signal[:, 1]) + output_right_ear += lfilter(hrtf_right[:, 1], 1, signal[:, 1]) + + return np.stack([output_left_ear, output_right_ear], axis=1) + + +def load_hrtf_signals(hrtf_path: str, hp: dict) -> tuple[ndarray, ndarray]: + """Loads the HRTF signals for a given head position. + + Args: + hrtf_path (str): Path to the HRTF signals. + hp (dict): Head position. + + Returns: + tuple(ndarray, ndarray): Left and right HRTF signals. + """ + + hp_left_path = ( + Path(hrtf_path) / f"{hp['mic']}-{hp['subject']}-n{abs(hp['left_angle'])}.wav" + ) + hp_right_path = ( + Path(hrtf_path) / f"{hp['mic']}-{hp['subject']}-p{abs(hp['right_angle'])}.wav" + ) + + hp_left_signal = read_signal(hp_left_path) + hp_right_signal = read_signal(hp_right_path) + + return hp_left_signal, hp_right_signal + + +def normalise_lufs_level( + signal: ndarray, reference_signal: ndarray, sample_rate: float +) -> ndarray: + """Normalises the signal to the LUFS level of the reference signal. + + Args: + signal (ndarray): Signal to normalise. + reference_signal (ndarray): Reference signal. + sample_rate (float): Sample rate of the signal. + + Returns: + ndarray: Normalised signal. + """ + loudness_meter = pyln.Meter(int(sample_rate)) + + signal_lufs = loudness_meter.integrated_loudness(signal) + reference_signal_lufs = loudness_meter.integrated_loudness(reference_signal) + + gain = reference_signal_lufs - signal_lufs + return pyln.normalize.loudness(signal, signal_lufs, signal_lufs + gain) + + +def find_precreated_samples(source_dir: str | Path) -> list[str]: + """Finds music tracks created in a previous run. + This avoids reprocessing them. + + Args: + source_dir (str| Path): Source directory. + + Returns: + list[str]: List of precreated samples. + """ + if isinstance(source_dir, str): + source_dir = Path(source_dir) + + return [f.name for f in source_dir.glob("*/*")] + + +@hydra.main(config_path="", config_name="config") +def run(cfg: DictConfig) -> None: + """Main function of the script.""" + + logger.info("Generating dataset for the ICASSP 2024 Grand Challenge.\n") + logger.info(f"Processing music for scenes: {cfg.path.scene_file}") + logger.info(f"Transforming music signals from: {cfg.path.music_dir}") + logger.info(f"and save them to {cfg.path.output_music_dir}") + + # Load precraeted samples to avoid reprocessing them + precreated_samples = find_precreated_samples(cfg.path.output_music_dir) + if len(precreated_samples) > 0: + logger.warning(f"Found {len(precreated_samples)} precreated samples.\n") + + # Load the scenes metadata + with open(cfg.path.scene_file, encoding="utf-8") as f: + scenes_metadata = json.load(f) + + # Load the music metadata + with open(cfg.path.music_file, encoding="utf-8") as f: + music_metadata = json.load(f) + music_metadata = {m["Track Name"]: m for m in music_metadata} + + # Load the head positions metadata + with open(cfg.path.head_positions_file, encoding="utf-8") as f: + head_positions_metadata = json.load(f) + + # From the scenes, get the samples names and parameters + toprocess_samples = { + f"{v['music']}-{v['head_position']}": { + "music": v["music"], + "head_position": v["head_position"], + } + for _, v in scenes_metadata.items() + } + + # create output metadata content + out_music = [] + for idx, sample in enumerate(toprocess_samples.items(), 1): + sample_name, sample_detail = sample + music = music_metadata[sample_detail["music"]] + head_position = sample_detail["head_position"] + + out_music.append( + { + "Track Name": sample_name, + "Split": music["Split"], + "Path": f"{music['Split']}/{sample_name}", + } + ) + + if sample_name in precreated_samples: + logger.info( + f"[{idx}/{len(toprocess_samples)}] Skipping sample: {sample_name}" + ) + continue + + scene_path = Path(cfg.path.output_music_dir) / music["Split"] / sample_name + scene_path.mkdir(parents=True, exist_ok=True) + + logger.info(f"[{idx}/{len(toprocess_samples)}] Creating sample: {sample_name}") + + hrtf_left, hrtf_rigth = load_hrtf_signals( + cfg.path.hrtf_dir, head_positions_metadata[head_position] + ) + + for stem_name in ["mixture", "vocals", "drums", "bass", "other"]: + music_signal = read_signal( + Path(cfg.path.music_dir) / music["Path"] / f"{stem_name}.wav" + ) + + at_mic_signal = apply_hrtf(music_signal, hrtf_left, hrtf_rigth) + + with warnings.catch_warnings(): + warnings.filterwarnings( + "ignore", message="Possible clipped samples in output" + ) + at_mic_signal = normalise_lufs_level( + at_mic_signal, music_signal, cfg.sample_rate + ) + + # Save the signal + save_path = scene_path / f"{stem_name}.wav" + write_signal( + save_path, at_mic_signal, cfg.sample_rate, floating_point=False + ) + + precreated_samples.append(sample_name) + + # Save the metadata + with open(cfg.path.output_music_file, "w", encoding="utf-8") as f: + json.dump(out_music, f, indent=4) + + +# pylint: disable = no-value-for-parameter +if __name__ == "__main__": + run() From cbbaac558c5e9d7bfdde0bc8305bc42c2bfc6aaf Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Mon, 11 Sep 2023 17:15:34 +0100 Subject: [PATCH 09/85] recipe files Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/README.md | 189 +++++++++++++++++++ recipes/cad_icassp_2024/baseline/config.yaml | 42 +++++ 2 files changed, 231 insertions(+) create mode 100644 recipes/cad_icassp_2024/baseline/README.md create mode 100644 recipes/cad_icassp_2024/baseline/config.yaml diff --git a/recipes/cad_icassp_2024/baseline/README.md b/recipes/cad_icassp_2024/baseline/README.md new file mode 100644 index 000000000..7732be324 --- /dev/null +++ b/recipes/cad_icassp_2024/baseline/README.md @@ -0,0 +1,189 @@ +# The First Cadenza Challenge (CAD1) - Task 1: Listening music via headphones + +Cadenza challenge code for the First Cadenza Challenge (CAD1) Task1. + +For more information please visit the [challenge website](https://cadenzachallenge.org/docs/cadenza1/cc1_intro). + +## 1. Data structure + +The First Cadenza Challenge - task 1 is using the MUSDB18-HQ dataset. +The data is split into train, validation and test following the same split from museval. +I.e., 86 songs are for training, 16 for validation and 50 for evaluation. + +To download the data, please visit [here](https://forms.gle/UQkuCxqQVxZtGggPA). The data is split into `cadenza_cad1_task1_core_musdb18hq.tar.gz` (containing the MUSDB18-HQ dataset) and +`cadenza_cad1_task1_core_metadata.tar.gz` (containing the list of songs and listeners' characteristics per split). +Alternatively, you can download the MUSDB18-HQ dataset from the official [SigSep website](https://sigsep.github.io/datasets/musdb.html#musdb18-hq-uncompressed-wav). +If you opt for this alternative, be sure to download the uncompressed wav version. Note that you will need both packages to run the baseline system. + +If you need additional music data for training your model, please restrict to the use of [MedleyDB](https://medleydb.weebly.com/) [4] [5], +[BACH10](https://labsites.rochester.edu/air/resource.html) [6] and [FMA-small](https://github.com/mdeff/fma) [7]. +Theses are shared as `cadenza_cad1_task1_augmentation_medleydb.tar.gz`, `cadenza_cad1_task1_augmentation_bach10.tar.gz` +and `cadenza_cad1_task1_augmentation_fma_small.tar.gz`. +**Keeping the augmentation data restricted to these datasets will ensure that the evaluation is fair for all participants**. + +Unpack packages under the same root directory using + +```bash +tar -xvzf +``` + +### 1.1 Necessary data + +* **Music** contains the MUSDB18-HQ music dataset for training, validation and evaluation. + +```text +cadenza_data +└───task1 + └───audio + └───musdb18hq + ├───train + └───test +``` + +* **Metadata** contains the metadata for the systems. + +```text +cadenza_data +└───task1 + └───metadata + └───musdb18hq + ├───listeners.train.json + ├───listeners.valid.json + ├───musdb18.train.json + ├───musdb18.valid.json + └───musdb18.test.json +``` + +### 1.2 Additional optional data + +* **MedleyDB** contains both MedleyDB versions 1 [[4](#references)] and 2 [[5](#references)] datasets. + +Tracks from the MedleyDB dataset are not included in the evaluation set. +However, is your responsibility to exclude any song that may be already contained in the training set. + +```text +cadenza_data +└───task1 + └───audio + └───MedleyDB + ├───Audio + └───Metadata +``` + +* **BACH10** contains the BACH10 dataset [[6](#references)]. + +Tracks from the BACH10 dataset are not included in MUSDB18-HQ and can all be used as training augmentation data. + +```text +cadenza_data +└───task1 + └───audio + └───fma_small + ├───000 + ├───001 + ├───... +``` + +* **FMA Small** contains the FMA small subset of the FMA dataset [[7](references)]. + +Tracks from the FMA small dataset are not included in the MUSDB18-HQ. +This dataset does not provide independent stems but only the full mix. +However, it can be used to train an unsupervised model to better initialise a supervised model. + +```text +cadenza_data +└───task1 + └───audio + └───fma_small + ├───000 + ├───001 + ├───... +``` + +### 1.3 Demo data + +To help you to start with the challenge, we provide a small subset of the data. +The `demo_data` folder contains a single song and two listeners from the validation set. + +To use the demo data, simply download the package `cadenza_data_demo.tar.xz` +from [here](https://drive.google.com/drive/folders/1Yxo_R-yPByEUvX5O5lhsHk3tW1ek5qKW?usp=share_link) +and unpack it under `recipes/cad1/task1/`, i.e., one level above the baseline directory. +Note that the `root.path` variable in `config.yaml` is already set to the demo data by default. + +To unpack the demo data, run: + +```bash +tar -xvf cadenza_data_demo.tar.xz +``` + +## 2. Baseline + +In the `baseline/` folder, we provide code for running the baseline enhancement system and performing the objective evaluation. +Note that we use [hydra](https://hydra.cc/docs/intro/) for config handling. + +### 2.1 Enhancement + +The baseline enhance simply takes the out-of-the-box [Hybrid Demucs](https://github.com/facebookresearch/demucs) [1] +source separation model distributed on [TorchAudio](https://pytorch.org/audio/main/tutorials/hybrid_demucs_tutorial.html) +and applies a simple NAL-R [2] fitting amplification to each VDBO (`vocals`, `drums`, `bass` and `others`) stem. + +The remixing is performed by summing the amplified VDBO stems. + +The baseline generates a left and right signal for each VDBO stem and a remixed signal, totalling 9 signals per song-listener. + +To run the baseline enhancement system first, make sure that `paths.root` in `config.yaml` points to +where you have installed the Cadenza data. This parameter defaults to the working directory. +You can also define your own `path.exp_folder` to store enhanced +signals and evaluated results. + +Then run: + +```bash +python enhance.py +``` + +Alternatively, you can provide the root variable on the command line, e.g., + +```bash +python enhance.py path.root=/full/path/to/my/cadenza_data +``` + +To get a full list of the parameters, run: + +```bash +python enhance.py --help +``` + +The folder `enhanced_signals` will appear in the `exp` folder. + +### 2.2 Evaluation + +The `evaluate.py` simply takes the signals stored in `enhanced_signals` and computes the HAAQI [[3](#references)] score +for each of the eight left and right VDBO stems. +The average of these eight scores is computed and returned for each signal. + +To run the evaluation stage, make sure that `path.root` is set in the `config.yaml` file and then run + +```bash +python evaluate.py +``` + +A csv file containing the eight HAAQI scores and the combined score will be generated in the `path.exp_folder`. + +To check the HAAQI code, see [here](../../../../clarity/evaluator/haaqi). + +Please note: you will not get identical HAAQI scores for the same signals if the random seed is not defined +(in the given recipe, the random seed for each signal is set as the last eight digits of the song md5). +As there are random noises generated within HAAQI, but the differences should be sufficiently small. + +The score for the baseline is 0.3608 HAAQI overall. + +## References + +* [1] Défossez, A. "Hybrid Spectrogram and Waveform Source Separation". Proceedings of the ISMIR 2021 Workshop on Music Source Separation. [doi:10.48550/arXiv.2111.03600](https://arxiv.org/abs/2111.03600) +* [2] Byrne, Denis, and Harvey Dillon. "The National Acoustic Laboratories'(NAL) new procedure for selecting the gain and frequency response of a hearing aid." Ear and hearing 7.4 (1986): 257-265. [doi:10.1097/00003446-198608000-00007](https://doi.org/10.1097/00003446-198608000-00007) +* [3] Kates J M, Arehart K H. "The Hearing-Aid Audio Quality Index (HAAQI)". IEEE/ACM transactions on audio, speech, and language processing, 24(2), 354–365. [doi:10.1109/TASLP.2015.2507858](https://doi.org/10.1109%2FTASLP.2015.2507858) +* [4] R. Bittner, J. Salamon, M. Tierney, M. Mauch, C. Cannam and J. P. Bello, "MedleyDB: A Multitrack Dataset for Annotation-Intensive MIR Research", in 15th International Society for Music Information Retrieval Conference, Taipei, Taiwan, Oct. 2014. [pdf](https://archives.ismir.net/ismir2014/paper/000322.pdf) +* [5] Rachel M. Bittner, Julia Wilkins, Hanna Yip and Juan P. Bello, "MedleyDB 2.0: New Data and a System for Sustainable Data Collection" Late breaking/demo extended abstract, 17th International Society for Music Information Retrieval (ISMIR) conference, August 2016. [pdf](https://wp.nyu.edu/ismir2016/wp-content/uploads/sites/2294/2016/08/bittner-medleydb.pdf) +* [6] Zhiyao Duan, Bryan Pardo and Changshui Zhang, "Multiple fundamental frequency estimation by modeling spectral peaks and non-peak regions," IEEE Trans. Audio Speech Language Process., vol. 18, no. 8, pp. 2121-2133, 2010. [doi:10.1109/TASL.2010.2042119](https://doi.org/10.1109/TASL.2010.2042119) +* [7] Defferrard, M., Benzi, K., Vandergheynst, P., & Bresson, X. (2016). "FMA: A dataset for music analysis". arXiv preprint arXiv:1612.01840. [doi:10.48550/arXiv.1612.01840](https://doi.org/10.48550/arXiv.1612.01840) diff --git a/recipes/cad_icassp_2024/baseline/config.yaml b/recipes/cad_icassp_2024/baseline/config.yaml new file mode 100644 index 000000000..caba995a5 --- /dev/null +++ b/recipes/cad_icassp_2024/baseline/config.yaml @@ -0,0 +1,42 @@ +path: + root: /media/gerardo/Extended_old/cadenza_data/icassp_2024 + metadata_dir: ${path.root}/metadata + music_dir: ${path.root}/audio/at_mic_music + gains_file: ${path.metadata_dir}/gains.json + head_positions_file: ${path.metadata_dir}/head_positions.json + listeners_file: ${path.metadata_dir}/listeners.train.json + music_file: ${path.metadata_dir}/at_mic_music.train.json + scenes_file: ${path.metadata_dir}/scenes.train.json + scene_listeners_file: ${path.metadata_dir}/scene_listeners.train.json + exp_folder: ./exp # folder to store enhanced signals and final results + +sample_rate: 44100 + +nalr: + nfir: 220 + sample_rate: ${sample_rate} + +apply_compressor: False +compressor: + threshold: 0.35 + attenuation: 0.1 + attack: 50 + release: 1000 + rms_buffer_size: 0.064 + +soft_clip: True + +separator: + model: demucs # demucs or openunmix + device: ~ + +evaluate: + set_random_seed: True + small_test: True + batch_size: 1 # Number of batches + batch: 0 # Batch number to evaluate + +# hydra config +hydra: + run: + dir: ${path.exp_folder} \ No newline at end of file From 84e87525d65ea8f6457728c8a9db47a7d6c9897f Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Mon, 11 Sep 2023 17:16:54 +0100 Subject: [PATCH 10/85] Add source_separation_utils to keep enhance cleaner Signed-off-by: Gerardo Roa Dabike --- .../baseline/source_separation_utils.py | 99 +++++++++++++++++++ 1 file changed, 99 insertions(+) create mode 100644 recipes/cad_icassp_2024/baseline/source_separation_utils.py diff --git a/recipes/cad_icassp_2024/baseline/source_separation_utils.py b/recipes/cad_icassp_2024/baseline/source_separation_utils.py new file mode 100644 index 000000000..5ecbe2041 --- /dev/null +++ b/recipes/cad_icassp_2024/baseline/source_separation_utils.py @@ -0,0 +1,99 @@ +"""Module that contains functions for source separation.""" +from __future__ import annotations + +# pylint: disable=import-error +import torch +from torchaudio.transforms import Fade + + +def separate_sources( + model: torch.nn.Module, + mix: torch.Tensor, + sample_rate: int, + segment: float = 10.0, + overlap: float = 0.1, + device: torch.device | str | None = None, +): + """ + Apply model to a given mixture. + Use fade, and add segments together in order to add model segment by segment. + + Args: + model (torch.nn.Module): model to use for separation + mix (torch.Tensor): mixture to separate, shape (batch, channels, time) + sample_rate (int): sampling rate of the mixture + segment (float): segment length in seconds + overlap (float): overlap between segments, between 0 and 1 + device (torch.device, str, or None): if provided, device on which to + execute the computation, otherwise `mix.device` is assumed. + When `device` is different from `mix.device`, only local computations will + be on `device`, while the entire tracks will be stored on `mix.device`. + + Returns: + torch.Tensor: estimated sources + + Based on https://pytorch.org/audio/main/tutorials/hybrid_demucs_tutorial.html + """ + device = mix.device if device is None else torch.device(device) + mix = torch.as_tensor(mix, device=device) + + if mix.ndim == 1: + # one track and mono audio + mix = mix.unsqueeze(0) + elif mix.ndim == 2: + # one track and stereo audio + mix = mix.unsqueeze(0) + + batch, channels, length = mix.shape + + chunk_len = int(sample_rate * segment * (1 + overlap)) + start = 0 + end = chunk_len + overlap_frames = overlap * sample_rate + fade = Fade(fade_in_len=0, fade_out_len=int(overlap_frames), fade_shape="linear") + + final = torch.zeros(batch, 4, channels, length, device=device) + + while start < length - overlap_frames: + chunk = mix[:, :, start:end] + with torch.no_grad(): + out = model.forward(chunk) + out = fade(out) + final[:, :, :, start:end] += out + if start == 0: + fade.fade_in_len = int(overlap_frames) + start += int(chunk_len - overlap_frames) + else: + start += chunk_len + end += chunk_len + if end >= length: + fade.fade_out_len = 0 + + return final.cpu().detach().numpy() + + +def get_device(device: str) -> tuple: + """Get the Torch device. + + Args: + device (str): device type, e.g. "cpu", "gpu0", "gpu1", etc. + + Returns: + torch.device: torch.device() appropiate to the hardware available. + str: device type selected, e.g. "cpu", "cuda". + """ + if device is None: + if torch.cuda.is_available(): + return torch.device("cuda"), "cuda" + return torch.device("cpu"), "cpu" + + if device.startswith("gpu"): + device_index = int(device.replace("gpu", "")) + if device_index > torch.cuda.device_count(): + raise ValueError(f"GPU device index {device_index} is not available.") + return torch.device(f"cuda:{device_index}"), "cuda" + + if device == "cpu": + return torch.device("cpu"), "cpu" + + raise ValueError(f"Unsupported device type: {device}") From e035f0a24dcd564674686b56650c80e08ca079ef Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Mon, 11 Sep 2023 17:19:22 +0100 Subject: [PATCH 11/85] Add enhancer Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/enhance.py | 280 ++++++++++++++++++++ 1 file changed, 280 insertions(+) create mode 100644 recipes/cad_icassp_2024/baseline/enhance.py diff --git a/recipes/cad_icassp_2024/baseline/enhance.py b/recipes/cad_icassp_2024/baseline/enhance.py new file mode 100644 index 000000000..f93394bca --- /dev/null +++ b/recipes/cad_icassp_2024/baseline/enhance.py @@ -0,0 +1,280 @@ +""" Run the dummy enhancement. """ +from __future__ import annotations + +import json +import logging +from pathlib import Path + +# pylint: disable=import-error +import hydra +import numpy as np +import torch +from evaluate import apply_gains, make_scene_listener_list, remix_stems +from numpy import ndarray +from omegaconf import DictConfig +from source_separation_utils import get_device, separate_sources +from torchaudio.pipelines import HDEMUCS_HIGH_MUSDB + +from clarity.enhancer.compressor import Compressor +from clarity.enhancer.nalr import NALR +from clarity.utils.audiogram import Audiogram, Listener +from clarity.utils.file_io import read_signal, write_signal +from clarity.utils.signal_processing import ( + denormalize_signals, + normalize_signal, + resample, +) + +logger = logging.getLogger(__name__) + + +# pylint: disable=unused-argument +def decompose_signal( + model: torch.nn.Module, + model_sample_rate: int, + signal: ndarray, + signal_sample_rate: int, + device: torch.device, + sources_list: list[str], + listener: Listener, + normalise: bool = True, +) -> dict[str, ndarray]: + """ + Decompose signal into 8 stems. + + The listener is ignored by the baseline system as it + is not performing personalised decomposition. + Instead, it performs a standard music decomposition using a pre-trained + model trained on the MUSDB18 dataset. + + Args: + model (torch.nn.Module): Torch model. + model_sample_rate (int): Sample rate of the model. + signal (ndarray): Signal to be decomposed. + signal_sample_rate (int): Sample frequency. + device (torch.device): Torch device to use for processing. + sources_list (list): List of strings used to index dictionary. + listener (Listener). + normalise (bool): Whether to normalise the signal. + + Returns: + Dictionary: Indexed by sources with the associated model as values. + """ + if signal.shape[0] > signal.shape[1]: + signal = signal.T + + if signal_sample_rate != model_sample_rate: + signal = resample(signal, signal_sample_rate, model_sample_rate) + + if normalise: + signal, ref = normalize_signal(signal) + + sources = separate_sources( + model, + torch.from_numpy(signal.astype(np.float32)), + model_sample_rate, + device=device, + ) + + # only one element in the batch + sources = sources[0] + if normalise: + sources = denormalize_signals(sources, ref) + + sources = np.transpose(sources, (0, 2, 1)) + return dict(zip(sources_list, sources)) + + +def apply_baseline_ha( + enhancer: NALR, + compressor: Compressor | None, + signal: ndarray, + audiogram: Audiogram, + apply_compressor: bool = False, +) -> np.ndarray: + """ + Apply NAL-R prescription hearing aid to a signal. + + Args: + enhancer (NALR): A NALR object that enhances the signal. + compressor (Compressor | None): A Compressor object that compresses the signal. + signal (ndarray): An ndarray representing the audio signal. + audiogram (Audiogram): An Audiogram object representing the listener's + audiogram. + apply_compressor (bool): Whether to apply the compressor. + + Returns: + An ndarray representing the processed signal. + """ + nalr_fir, _ = enhancer.build(audiogram) + proc_signal = enhancer.apply(nalr_fir, signal) + if apply_compressor: + if compressor is None: + raise ValueError("Compressor must be provided to apply compressor.") + + proc_signal, _, _ = compressor.process(proc_signal) + return proc_signal + + +def process_remix_for_listener( + signal: ndarray, + enhancer: NALR, + compressor: Compressor, + listener: Listener, + apply_compressor: bool = False, +) -> ndarray: + """Process the stems from sources. + + Args: + stems (dict) : Dictionary of stems + sample_rate (float) : Sample rate of the signal + enhancer (NALR) : NAL-R prescription hearing aid + compressor (Compressor) : Compressor + listener: Listener object + apply_compressor (bool) : Whether to apply the compressor + Returns: + ndarray: Processed signal. + """ + left_output = apply_baseline_ha( + enhancer, compressor, signal[:, 0], listener.audiogram_left, apply_compressor + ) + right_output = apply_baseline_ha( + enhancer, compressor, signal[:, 1], listener.audiogram_right, apply_compressor + ) + + return np.stack([left_output, right_output], axis=1) + + +@hydra.main(config_path="", config_name="config") +def enhance(config: DictConfig) -> None: + """ + Run the music enhancement. + The system decomposes the music into vocal, drums, bass, and other stems. + Then, the NAL-R prescription procedure is applied to each stem. + Args: + config (dict): Dictionary of configuration options for enhancing music. + + Returns 8 stems for each song: + - left channel vocal, drums, bass, and other stems + - right channel vocal, drums, bass, and other stems + """ + + # Set the output directory where processed signals will be saved + enhanced_folder = Path("enhanced_signals") + enhanced_folder.mkdir(parents=True, exist_ok=True) + + # Loading pretrained source separation model + if config.separator.model == "demucs": + separation_model = HDEMUCS_HIGH_MUSDB.get_model() + model_sample_rate = HDEMUCS_HIGH_MUSDB.sample_rate + sources_order = separation_model.sources + normalise = True + elif config.separator.model == "openunmix": + separation_model = torch.hub.load("sigsep/open-unmix-pytorch", "umxhq", niter=0) + model_sample_rate = separation_model.sample_rate + sources_order = ["vocals", "drums", "bass", "other"] + normalise = False + else: + raise ValueError(f"Separator model {config.separator.model} not supported.") + + device, _ = get_device(config.separator.device) + separation_model.to(device) + + # Load listener audiograms and songs + listener_dict = Listener.load_listener_dict(config.path.listeners_file) + + with Path(config.path.gains_file).open("r", encoding="utf-8") as file: + gains = json.load(file) + + with Path(config.path.scenes_file).open("r", encoding="utf-8") as file: + scenes = json.load(file) + + with Path(config.path.scene_listeners_file).open("r", encoding="utf-8") as file: + scenes_listeners = json.load(file) + + with Path(config.path.music_file).open("r", encoding="utf-8") as file: + songs = json.load(file) + + enhancer = NALR(**config.nalr) + compressor = Compressor(**config.compressor) + + # Select a batch to process + scene_listener_pairs = make_scene_listener_list( + scenes_listeners, config.evaluate.small_test + ) + scene_listener_pairs = scene_listener_pairs[ + config.evaluate.batch :: config.evaluate.batch_size + ] + + # Decompose each song into left and right vocal, drums, bass, and other stems + # and process each stem for the listener + previous_song = "" + num_scenes = len(scene_listener_pairs) + for idx, scene_listener_pair in enumerate(scene_listener_pairs): + scene_id, listener_id = scene_listener_pair + + scene = scenes[scene_id] + song_name = f"{scene['music']}-{scene['head_position']}" + + logger.info( + f"[{idx:03d}/{num_scenes:03d}] " + f"Processing {song_name} for listener {listener_id}" + ) + # Get the listener's audiogram + listener = listener_dict[listener_id] + + # Read the mixture signal + # Convert to 32-bit floating point and transpose + # from [samples, channels] to [channels, samples] + if song_name != previous_song: + mixture_signal = read_signal( + filename=Path(config.path.music_dir) + / songs[song_name]["Path"] + / "mixture.wav", + sample_rate=config.sample_rate, + allow_resample=True, + ) + + stems: dict[str, ndarray] = decompose_signal( + model=separation_model, + model_sample_rate=model_sample_rate, + signal=mixture_signal, + signal_sample_rate=config.sample_rate, + device=device, + sources_list=sources_order, + listener=listener, + normalise=normalise, + ) + + stems = apply_gains(stems, config.sample_rate, gains[scene["gain"]]) + enhanced_signal = remix_stems(stems, mixture_signal, model_sample_rate) + + enhanced_signal = process_remix_for_listener( + signal=enhanced_signal, + enhancer=enhancer, + compressor=compressor, + listener=listener, + apply_compressor=config.apply_compressor, + ) + + filename = Path( + enhanced_folder + / f"{listener.id}" + / f"{song_name}" + / f"{scene_id}_{listener.id}_remix.wav" + ) + filename.parent.mkdir(parents=True, exist_ok=True) + write_signal( + filename=filename, + signal=enhanced_signal, + sample_rate=config.sample_rate, + floating_point=False, + strict=False, + ) + + logger.info("Done!") + + +# pylint: disable = no-value-for-parameter +if __name__ == "__main__": + enhance() From 394d7429bf25e1c70877d4685f8b4a5df612ab8a Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Mon, 11 Sep 2023 17:21:37 +0100 Subject: [PATCH 12/85] evaluate Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/evaluate.py | 332 +++++++++++++++++++ 1 file changed, 332 insertions(+) create mode 100644 recipes/cad_icassp_2024/baseline/evaluate.py diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py new file mode 100644 index 000000000..b8c3a4dfb --- /dev/null +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -0,0 +1,332 @@ +"""Evaluate the enhanced signals using the HAAQI metric.""" +from __future__ import annotations + +# pylint: disable=import-error +import csv +import hashlib +import json +import logging +import warnings +from pathlib import Path + +import hydra +import numpy as np +import pyloudnorm as pyln +from numpy import ndarray +from omegaconf import DictConfig + +from clarity.enhancer.nalr import NALR +from clarity.evaluator.haaqi import compute_haaqi +from clarity.utils.audiogram import Listener +from clarity.utils.file_io import read_signal +from clarity.utils.signal_processing import compute_rms + +logger = logging.getLogger(__name__) + + +class ResultsFile: + """A utility class for writing results to a CSV file. + + Attributes: + file_name (str): The name of the file to write results to. + """ + + def __init__(self, file_name: str): + """Initialize the ResultsFile instance. + + Args: + file_name (str): The name of the file to write results to. + """ + self.file_name = file_name + + def write_header(self): + """Write the header row to the CSV file.""" + with open(self.file_name, "w", encoding="utf-8", newline="") as csv_file: + csv_writer = csv.writer( + csv_file, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL + ) + csv_writer.writerow( + [ + "scene", + "song", + "listener", + "left_score", + "right_score", + "score", + ] + ) + + def add_result( + self, + scene: str, + song: str, + listener_id: str, + left_score: float, + right_score: float, + score: float, + ): + """Add a result to the CSV file. + + Args: + scene (str): The name of the scene that the result is for. + song (str): The name of the song that the result is for. + listener_id (str): The name of the listener who submitted the result. + left_score (float): The score for the left channel. + right_score (float): The score for the right channel. + score (float): The combined score. + """ + logger.info(f"The combined score is {score}") + + with open(self.file_name, "a", encoding="utf-8", newline="") as csv_file: + csv_writer = csv.writer( + csv_file, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL + ) + csv_writer.writerow( + [ + scene, + song, + listener_id, + str(left_score), + str(right_score), + str(score), + ] + ) + + +def apply_gains(stems: dict, sample_rate: float, gains: dict) -> dict: + """Apply gain to the signal by using LUFS. + + Args: + stems (dict): Dictionary of stems. + sample_rate (float): Sample rate of the signal. + gains (dict): Dictionary of gains. + + Returns: + dict: Dictionary of stems with applied gains. + """ + meter = pyln.Meter(int(sample_rate)) + stems_gain = {} + for stem_str, stem_signal in stems.items(): + if stem_signal.shape[0] < stem_signal.shape[1]: + stem_signal = stem_signal.T + + stem_lufs = meter.integrated_loudness(stem_signal) + if stem_lufs == -np.inf: + stem_lufs = -80 + + gain = stem_lufs + gains[stem_str] + with warnings.catch_warnings(): + warnings.filterwarnings( + "ignore", message="Possible clipped samples in output" + ) + stems_gain[stem_str] = pyln.normalize.loudness(stem_signal, stem_lufs, gain) + return stems_gain + + +def level_normalisation( + signal: ndarray, reference_signal: ndarray, sample_rate: float +) -> ndarray: + """Normalise the signal to the LUFS level of the reference signal. + + Args: + signal (ndarray): Signal to normalise. + reference_signal (ndarray): Reference signal. + sample_rate (float): Sample rate of the signal. + + Returns: + ndarray: Normalised signal. + """ + meter = pyln.Meter(int(sample_rate)) + signal_lufs = meter.integrated_loudness(signal) + reference_signal_lufs = meter.integrated_loudness(reference_signal) + + if signal_lufs == -np.inf: + signal_lufs = -80 + + if reference_signal_lufs == -np.inf: + reference_signal_lufs = -80 + + gain = reference_signal_lufs - signal_lufs + + with warnings.catch_warnings(): + warnings.filterwarnings("ignore", message="Possible clipped samples in output") + normed_signal = pyln.normalize.loudness(signal, signal_lufs, signal_lufs + gain) + return normed_signal + + +def remix_stems(stems: dict, reference_signal, sample_rate: float) -> ndarray: + """Remix the stems into a stereo signal. + + The remixing is done by summing the stems. + Then, the signal is normalised to the LUFS level of the reference signal. + + Args: + stems (dict): Dictionary of stems. + reference_signal (ndarray): Reference signal. + sample_rate (float): Sample rate of the signal. + + Returns: + ndarray: Stereo signal. + """ + remix_signal = np.zeros(stems["vocals"].shape) + for _, stem_signal in stems.items(): + remix_signal += stem_signal + return level_normalisation(remix_signal, reference_signal, sample_rate) + + +def make_scene_listener_list(scenes_listeners, small_test=False): + """Make the list of scene-listener pairing to process""" + scene_listener_pairs = [ + (scene, listener) + for scene in scenes_listeners + for listener in scenes_listeners[scene] + ] + + # Can define a standard 'small_test' with just 1/50 of the data + if small_test: + scene_listener_pairs = scene_listener_pairs[::50] + + return scene_listener_pairs + + +def set_song_seed(song: str) -> None: + """Set a seed that is unique for the given song""" + song_encoded = hashlib.md5(song.encode("utf-8")).hexdigest() + song_md5 = int(song_encoded, 16) % (10**8) + np.random.seed(song_md5) + + +def load_reference_stems(music_dir: str | Path) -> tuple[dict[str, ndarray], ndarray]: + """Load the reference stems for a given scene. + + Args: + scene (dict): The scene to load the stems for. + music_dir (str | Path): The path to the music directory. + Returns: + reference_stems (dict): A dictionary of reference stems. + original_mixture (ndarray): The original mixture. + """ + reference_stems = {} + for instrument in ["drums", "bass", "other", "vocals"]: + stem = read_signal(Path(music_dir) / f"{instrument}.wav") + reference_stems[instrument] = stem + + return reference_stems, read_signal(Path(music_dir) / "mixture.wav") + + +@hydra.main(config_path="", config_name="config") +def run_calculate_aq(config: DictConfig) -> None: + """Evaluate the enhanced signals using the HAAQI metric.""" + + enhanced_folder = Path("enhanced_signals") + logger.info(f"Evaluating from {enhanced_folder} directory") + + # Load listener audiograms and songs + listener_dict = Listener.load_listener_dict(config.path.listeners_file) + + with Path(config.path.gains_file).open("r", encoding="utf-8") as file: + gains = json.load(file) + + with Path(config.path.scenes_file).open("r", encoding="utf-8") as file: + scenes = json.load(file) + + with Path(config.path.scene_listeners_file).open("r", encoding="utf-8") as file: + scenes_listeners = json.load(file) + + with Path(config.path.music_file).open("r", encoding="utf-8") as file: + songs = json.load(file) + + enhancer = NALR(**config.nalr) + + if config.evaluate.batch_size == 1: + results_file = ResultsFile("scores.csv") + else: + results_file = ResultsFile( + f"scores_{config.evaluate.batch + 1}-{config.evaluate.batch_size}.csv" + ) + results_file.write_header() + + scene_listener_pairs = make_scene_listener_list( + scenes_listeners, config.evaluate.small_test + ) + scene_listener_pairs = scene_listener_pairs[ + config.evaluate.batch :: config.evaluate.batch_size + ] + num_scenes = len(scene_listener_pairs) + for idx, scene_listener_pair in enumerate(scene_listener_pairs): + scene_id, listener_id = scene_listener_pair + + scene = scenes[scene_id] + song_name = f"{scene['music']}-{scene['head_position']}" + + logger.info( + f"[{idx:03d}/{num_scenes:03d}] " + f"Processing {song_name} for listener {listener_id}" + ) + + # Load reference signals + reference_stems, original_mixture = load_reference_stems( + Path(config.path.music_dir) / songs[song_name]["Path"] + ) + reference_stems = apply_gains( + reference_stems, config.sample_rate, gains[scene["gain"]] + ) + reference_mixture = remix_stems( + reference_stems, original_mixture, config.sample_rate + ) + + # Set the random seed for the scene + if config.evaluate.set_random_seed: + set_song_seed(scene_id) + + # Evaluate listener + listener = listener_dict[listener_id] + + # Load enhanced signal + enhanced_signal = read_signal( + Path( + enhanced_folder + / f"{listener.id}" + / f"{song_name}" + / f"{scene_id}_{listener.id}_remix.wav" + ) + ) + + # Compute the score for left channel + nalr_fir, _ = enhancer.build(listener.audiogram_left) + left_reference = enhancer.apply(nalr_fir, reference_mixture[:, 0]) + left_score = compute_haaqi( + enhanced_signal[:, 0], + left_reference, + listener.audiogram_left, + config.sample_rate, + 65 - 20 * np.log10(compute_rms(left_reference)), + ) + + # Compute score for right channel + nalr_fir, _ = enhancer.build(listener.audiogram_right) + right_reference = enhancer.apply(nalr_fir, reference_mixture[:, 1]) + right_score = compute_haaqi( + enhanced_signal[:, 1], + right_reference, + listener.audiogram_left, + config.sample_rate, + 65 - 20 * np.log10(compute_rms(left_reference)), + ) + + # Save scores + results_file.add_result( + scene=scene_id, + song=song_name, + listener_id=listener.id, + left_score=left_score, + right_score=right_score, + score=np.mean([left_score, right_score])[0], + ) + + logger.info("Done!") + + +# pylint: disable = no-value-for-parameter +if __name__ == "__main__": + run_calculate_aq() From 9b1bf5a05bf0c214ca645bbe87f22ecf22bceac3 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Mon, 11 Sep 2023 17:22:26 +0100 Subject: [PATCH 13/85] Add merge batches Signed-off-by: Gerardo Roa Dabike --- .../baseline/merge_batches_results.py | 31 +++++++++++++++++++ 1 file changed, 31 insertions(+) create mode 100644 recipes/cad_icassp_2024/baseline/merge_batches_results.py diff --git a/recipes/cad_icassp_2024/baseline/merge_batches_results.py b/recipes/cad_icassp_2024/baseline/merge_batches_results.py new file mode 100644 index 000000000..ff29762da --- /dev/null +++ b/recipes/cad_icassp_2024/baseline/merge_batches_results.py @@ -0,0 +1,31 @@ +"""Join batches scores into a single file.""" + +# pylint: disable=import-error +import hydra +import pandas as pd +from omegaconf import DictConfig + + +@hydra.main(config_path="", config_name="config") +def join_batches(config: DictConfig) -> None: + """ + Join batches scores into a single file. + + Args: + config (DictConfig): Dictionary of configuration options. + The `.evaluate.batch_size` is extracted to determine how many + batches there are to combine. + + """ + batches_results = [] + for batch in range(config.evaluate.batch_size): + batches_results.append( + pd.read_csv(f"scores_{batch + 1}-{config.evaluate.batch_size}.csv") + ) + df_res = pd.concat(batches_results, ignore_index=True) + df_res.to_csv("scores.csv", index=False) + + +# pylint: disable=no-value-for-parameter +if __name__ == "__main__": + join_batches() From 95f4ff3f4d17b70c6ab8a0a2e521e26c60af84ca Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Mon, 11 Sep 2023 18:18:59 +0100 Subject: [PATCH 14/85] equalization to 2 in HAAQI Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/evaluate.py | 22 +++++++++++--------- 1 file changed, 12 insertions(+), 10 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index b8c3a4dfb..e728af1a0 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -296,22 +296,24 @@ def run_calculate_aq(config: DictConfig) -> None: nalr_fir, _ = enhancer.build(listener.audiogram_left) left_reference = enhancer.apply(nalr_fir, reference_mixture[:, 0]) left_score = compute_haaqi( - enhanced_signal[:, 0], - left_reference, - listener.audiogram_left, - config.sample_rate, - 65 - 20 * np.log10(compute_rms(left_reference)), + processed_signal=enhanced_signal[:, 0], + reference_signal=left_reference, + audiogram=listener.audiogram_left, + sample_rate=config.sample_rate, + equalisation=2, + level1=65 - 20 * np.log10(compute_rms(left_reference)), ) # Compute score for right channel nalr_fir, _ = enhancer.build(listener.audiogram_right) right_reference = enhancer.apply(nalr_fir, reference_mixture[:, 1]) right_score = compute_haaqi( - enhanced_signal[:, 1], - right_reference, - listener.audiogram_left, - config.sample_rate, - 65 - 20 * np.log10(compute_rms(left_reference)), + processed_signal=enhanced_signal[:, 1], + reference_signal=right_reference, + audiogram=listener.audiogram_left, + sample_rate=config.sample_rate, + equalisation=2, + level1=65 - 20 * np.log10(compute_rms(left_reference)), ) # Save scores From da4874b3e6989b1538e889e4740ea6c6e8cdd95e Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Mon, 11 Sep 2023 18:20:04 +0100 Subject: [PATCH 15/85] readme Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/README.md | 170 ++++++++++----------- 1 file changed, 78 insertions(+), 92 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/README.md b/recipes/cad_icassp_2024/baseline/README.md index 7732be324..704086ff3 100644 --- a/recipes/cad_icassp_2024/baseline/README.md +++ b/recipes/cad_icassp_2024/baseline/README.md @@ -1,25 +1,18 @@ -# The First Cadenza Challenge (CAD1) - Task 1: Listening music via headphones +# The ICASSP 2024 Cadenza Challenge (CAD_ICASSP_2024) -Cadenza challenge code for the First Cadenza Challenge (CAD1) Task1. +Cadenza challenge code for the ICASSP 2024 Cadenza Challenge. -For more information please visit the [challenge website](https://cadenzachallenge.org/docs/cadenza1/cc1_intro). +For more information please visit the [challenge website](https://cadenzachallenge.org/docs/icassp_2024/intro). ## 1. Data structure -The First Cadenza Challenge - task 1 is using the MUSDB18-HQ dataset. -The data is split into train, validation and test following the same split from museval. -I.e., 86 songs are for training, 16 for validation and 50 for evaluation. +The ICASSP 2024 Cadenza Challenge dataset is based on the MUSDB18-HQ dataset. +To download the data, please visit [Download data and software](https://cadenzachallenge.org/docs/icassp_2024/take_part/download) +webpage. -To download the data, please visit [here](https://forms.gle/UQkuCxqQVxZtGggPA). The data is split into `cadenza_cad1_task1_core_musdb18hq.tar.gz` (containing the MUSDB18-HQ dataset) and -`cadenza_cad1_task1_core_metadata.tar.gz` (containing the list of songs and listeners' characteristics per split). -Alternatively, you can download the MUSDB18-HQ dataset from the official [SigSep website](https://sigsep.github.io/datasets/musdb.html#musdb18-hq-uncompressed-wav). -If you opt for this alternative, be sure to download the uncompressed wav version. Note that you will need both packages to run the baseline system. - -If you need additional music data for training your model, please restrict to the use of [MedleyDB](https://medleydb.weebly.com/) [4] [5], -[BACH10](https://labsites.rochester.edu/air/resource.html) [6] and [FMA-small](https://github.com/mdeff/fma) [7]. -Theses are shared as `cadenza_cad1_task1_augmentation_medleydb.tar.gz`, `cadenza_cad1_task1_augmentation_bach10.tar.gz` -and `cadenza_cad1_task1_augmentation_fma_small.tar.gz`. -**Keeping the augmentation data restricted to these datasets will ensure that the evaluation is fair for all participants**. +The data is split into four packages: `cadenza_icassp2024_core.v1_0.tgz`, +`cadenza_icassp2024_augmentation_medleydb.tar.gz`, `cadenza_icassp2024_augmentation_bach10.tar.gz` +and `cadenza_icassp2024_augmentation_fma_small.tar.gz`. Unpack packages under the same root directory using @@ -29,62 +22,70 @@ tar -xvzf ### 1.1 Necessary data -* **Music** contains the MUSDB18-HQ music dataset for training, validation and evaluation. +* **Core** contains the metadata and audio signal to generate the ICASSP 2024 dataset. ```text cadenza_data -└───task1 - └───audio - └───musdb18hq - ├───train - └───test -``` - -* **Metadata** contains the metadata for the systems. +├───audio +| ├───hrtf (336 kB) +| | | BTE_fr-VP_E1-n22.5.wav +| | | BTE_fr-VP_E1-n30.0.wav +| | | ... +| | +| └───music +| └───train (20.2 GB) +| ├───A Classic Education - NightOwl +| | | bass.wav +| | | drums.wav +| | | other.wav +| | | vocals.wav +| | | mixture.wav +| | +| ├───... +| +└───metadata (328 kB) + | gains.json + | head_positions.json + | listeners.train.json + | listeners.valid.json + | musdb18.train.json + | musdb18.valid.json + | scene_listeners.train.json + | scenes.train.json + | ... -```text -cadenza_data -└───task1 - └───metadata - └───musdb18hq - ├───listeners.train.json - ├───listeners.valid.json - ├───musdb18.train.json - ├───musdb18.valid.json - └───musdb18.test.json ``` ### 1.2 Additional optional data -* **MedleyDB** contains both MedleyDB versions 1 [[4](#references)] and 2 [[5](#references)] datasets. +If you need additional music data for training your model, please restrict to the use of [MedleyDB](https://medleydb.weebly.com/) [[5](#references)] [[6](#references)], +[BACH10](https://labsites.rochester.edu/air/resource.html) [7] and [FMA-small](https://github.com/mdeff/fma) [7]. + +**Keeping the augmentation data restricted to these datasets will ensure that the evaluation is fair for all participants**. -Tracks from the MedleyDB dataset are not included in the evaluation set. -However, is your responsibility to exclude any song that may be already contained in the training set. +* **MedleyDB** contains both MedleyDB versions 1 [[5](#references)] and 2 [[6](#references)] datasets. ```text cadenza_data -└───task1 - └───audio - └───MedleyDB - ├───Audio - └───Metadata +└───audio + └───MedleyDB (164 GB) + ├───Audio + └───Metadata ``` -* **BACH10** contains the BACH10 dataset [[6](#references)]. +* **BACH10** contains the BACH10 dataset [[7](#references)]. Tracks from the BACH10 dataset are not included in MUSDB18-HQ and can all be used as training augmentation data. ```text cadenza_data -└───task1 - └───audio - └───fma_small - ├───000 - ├───001 - ├───... +└───audio + └───Bach10 (150 MB) + ├───01-AchGottundHerr + ├───... ``` -* **FMA Small** contains the FMA small subset of the FMA dataset [[7](references)]. +* **FMA Small** contains the FMA small subset of the FMA dataset [[8](references)]. Tracks from the FMA small dataset are not included in the MUSDB18-HQ. This dataset does not provide independent stems but only the full mix. @@ -92,28 +93,11 @@ However, it can be used to train an unsupervised model to better initialise a su ```text cadenza_data -└───task1 - └───audio - └───fma_small - ├───000 - ├───001 - ├───... -``` - -### 1.3 Demo data - -To help you to start with the challenge, we provide a small subset of the data. -The `demo_data` folder contains a single song and two listeners from the validation set. - -To use the demo data, simply download the package `cadenza_data_demo.tar.xz` -from [here](https://drive.google.com/drive/folders/1Yxo_R-yPByEUvX5O5lhsHk3tW1ek5qKW?usp=share_link) -and unpack it under `recipes/cad1/task1/`, i.e., one level above the baseline directory. -Note that the `root.path` variable in `config.yaml` is already set to the demo data by default. - -To unpack the demo data, run: - -```bash -tar -xvf cadenza_data_demo.tar.xz +└───audio + └───fma_small (8 GB) + ├───000 + ├───001 + ├───... ``` ## 2. Baseline @@ -123,16 +107,19 @@ Note that we use [hydra](https://hydra.cc/docs/intro/) for config handling. ### 2.1 Enhancement -The baseline enhance simply takes the out-of-the-box [Hybrid Demucs](https://github.com/facebookresearch/demucs) [1] -source separation model distributed on [TorchAudio](https://pytorch.org/audio/main/tutorials/hybrid_demucs_tutorial.html) -and applies a simple NAL-R [2] fitting amplification to each VDBO (`vocals`, `drums`, `bass` and `others`) stem. +The baseline enhance takes an out-of-the-box source separation model and estimates +the VDBO (vocals, drums, bass and others) stems for each song-listener pair. + +For each estimated stem, the baseline applies the gains and remix the signal. +A simple NAL-R [2] fitting amplification is applied to the final remix -The remixing is performed by summing the amplified VDBO stems. +The basile offers 2 source separation options: -The baseline generates a left and right signal for each VDBO stem and a remixed signal, totalling 9 signals per song-listener. +1. [Hybrid Demucs](https://github.com/facebookresearch/demucs) [[1](#references)] distributed on [TorchAudio](https://pytorch.org/audio/main/tutorials/hybrid_demucs_tutorial.html) +2. [Open-Unmix](https://github.com/sigsep/open-unmix-pytorch) [[2](#references)] distributed through Pytorch hub. To run the baseline enhancement system first, make sure that `paths.root` in `config.yaml` points to -where you have installed the Cadenza data. This parameter defaults to the working directory. +where you have installed the Cadenza data. You can also define your own `path.exp_folder` to store enhanced signals and evaluated results. @@ -145,7 +132,7 @@ python enhance.py Alternatively, you can provide the root variable on the command line, e.g., ```bash -python enhance.py path.root=/full/path/to/my/cadenza_data +python enhance.py path.root=/Volumes/data/cadenza_data ``` To get a full list of the parameters, run: @@ -158,9 +145,7 @@ The folder `enhanced_signals` will appear in the `exp` folder. ### 2.2 Evaluation -The `evaluate.py` simply takes the signals stored in `enhanced_signals` and computes the HAAQI [[3](#references)] score -for each of the eight left and right VDBO stems. -The average of these eight scores is computed and returned for each signal. +The `evaluate.py` simply takes the signals stored in `enhanced_signals` and computes the HAAQI [[3](#references)] scores To run the evaluation stage, make sure that `path.root` is set in the `config.yaml` file and then run @@ -168,22 +153,23 @@ To run the evaluation stage, make sure that `path.root` is set in the `config.ya python evaluate.py ``` -A csv file containing the eight HAAQI scores and the combined score will be generated in the `path.exp_folder`. +A csv file containing the left and right channels HAAQI scores and the mean of both will be generated in the `path.exp_folder`. -To check the HAAQI code, see [here](../../../../clarity/evaluator/haaqi). +To check the HAAQI code, see [here](https://github.com/claritychallenge/clarity/blob/main/clarity/evaluator/haaqi/haaqi.py). Please note: you will not get identical HAAQI scores for the same signals if the random seed is not defined (in the given recipe, the random seed for each signal is set as the last eight digits of the song md5). As there are random noises generated within HAAQI, but the differences should be sufficiently small. -The score for the baseline is 0.3608 HAAQI overall. +The score for the baseline is XXXX HAAQI overall. ## References * [1] Défossez, A. "Hybrid Spectrogram and Waveform Source Separation". Proceedings of the ISMIR 2021 Workshop on Music Source Separation. [doi:10.48550/arXiv.2111.03600](https://arxiv.org/abs/2111.03600) -* [2] Byrne, Denis, and Harvey Dillon. "The National Acoustic Laboratories'(NAL) new procedure for selecting the gain and frequency response of a hearing aid." Ear and hearing 7.4 (1986): 257-265. [doi:10.1097/00003446-198608000-00007](https://doi.org/10.1097/00003446-198608000-00007) -* [3] Kates J M, Arehart K H. "The Hearing-Aid Audio Quality Index (HAAQI)". IEEE/ACM transactions on audio, speech, and language processing, 24(2), 354–365. [doi:10.1109/TASLP.2015.2507858](https://doi.org/10.1109%2FTASLP.2015.2507858) -* [4] R. Bittner, J. Salamon, M. Tierney, M. Mauch, C. Cannam and J. P. Bello, "MedleyDB: A Multitrack Dataset for Annotation-Intensive MIR Research", in 15th International Society for Music Information Retrieval Conference, Taipei, Taiwan, Oct. 2014. [pdf](https://archives.ismir.net/ismir2014/paper/000322.pdf) -* [5] Rachel M. Bittner, Julia Wilkins, Hanna Yip and Juan P. Bello, "MedleyDB 2.0: New Data and a System for Sustainable Data Collection" Late breaking/demo extended abstract, 17th International Society for Music Information Retrieval (ISMIR) conference, August 2016. [pdf](https://wp.nyu.edu/ismir2016/wp-content/uploads/sites/2294/2016/08/bittner-medleydb.pdf) -* [6] Zhiyao Duan, Bryan Pardo and Changshui Zhang, "Multiple fundamental frequency estimation by modeling spectral peaks and non-peak regions," IEEE Trans. Audio Speech Language Process., vol. 18, no. 8, pp. 2121-2133, 2010. [doi:10.1109/TASL.2010.2042119](https://doi.org/10.1109/TASL.2010.2042119) -* [7] Defferrard, M., Benzi, K., Vandergheynst, P., & Bresson, X. (2016). "FMA: A dataset for music analysis". arXiv preprint arXiv:1612.01840. [doi:10.48550/arXiv.1612.01840](https://doi.org/10.48550/arXiv.1612.01840) +* [2] Stöter, F. R., Liutkus, A., Ito, N., Nakashika, T., Ono, N., & Mitsufuji, Y. (2019). "Open-Unmix: A Reference Implementation for Music Source Separation". Journal of Open Source Software, 4(41), 1667. [doi:10.21105/joss.01667](https://doi.org/10.21105/joss.01667) +* [3] Byrne, Denis, and Harvey Dillon. "The National Acoustic Laboratories'(NAL) new procedure for selecting the gain and frequency response of a hearing aid." Ear and hearing 7.4 (1986): 257-265. [doi:10.1097/00003446-198608000-00007](https://doi.org/10.1097/00003446-198608000-00007) +* [4] Kates J M, Arehart K H. "The Hearing-Aid Audio Quality Index (HAAQI)". IEEE/ACM transactions on audio, speech, and language processing, 24(2), 354–365. [doi:10.1109/TASLP.2015.2507858](https://doi.org/10.1109%2FTASLP.2015.2507858) +* [5] R. Bittner, J. Salamon, M. Tierney, M. Mauch, C. Cannam and J. P. Bello, "MedleyDB: A Multitrack Dataset for Annotation-Intensive MIR Research", in 15th International Society for Music Information Retrieval Conference, Taipei, Taiwan, Oct. 2014. [pdf](https://archives.ismir.net/ismir2014/paper/000322.pdf) +* [6] Rachel M. Bittner, Julia Wilkins, Hanna Yip and Juan P. Bello, "MedleyDB 2.0: New Data and a System for Sustainable Data Collection" Late breaking/demo extended abstract, 17th International Society for Music Information Retrieval (ISMIR) conference, August 2016. [pdf](https://wp.nyu.edu/ismir2016/wp-content/uploads/sites/2294/2016/08/bittner-medleydb.pdf) +* [7] Zhiyao Duan, Bryan Pardo and Changshui Zhang, "Multiple fundamental frequency estimation by modeling spectral peaks and non-peak regions," IEEE Trans. Audio Speech Language Process., vol. 18, no. 8, pp. 2121-2133, 2010. [doi:10.1109/TASL.2010.2042119](https://doi.org/10.1109/TASL.2010.2042119) +* [8] Defferrard, M., Benzi, K., Vandergheynst, P., & Bresson, X. (2016). "FMA: A dataset for music analysis". arXiv preprint arXiv:1612.01840. [doi:10.48550/arXiv.1612.01840](https://doi.org/10.48550/arXiv.1612.01840) From 333f13b592574268007aa689aeaa2f393c192925 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Mon, 11 Sep 2023 19:25:03 +0100 Subject: [PATCH 16/85] readme gen dataset Signed-off-by: Gerardo Roa Dabike --- .../generate_dataset/README.md | 67 +++++++++++++++++++ 1 file changed, 67 insertions(+) create mode 100644 recipes/cad_icassp_2024/generate_dataset/README.md diff --git a/recipes/cad_icassp_2024/generate_dataset/README.md b/recipes/cad_icassp_2024/generate_dataset/README.md new file mode 100644 index 000000000..5c3556a05 --- /dev/null +++ b/recipes/cad_icassp_2024/generate_dataset/README.md @@ -0,0 +1,67 @@ +# Generate music dataset for the ICASSP 2024 Cadenza Challenge + +The ICASSP 2024 Cadenza Challenge music dataset is based on the MUSDB18-HQ dataset. + +Steps: + +1. Download `cadenza_cad1_task1_core_musdb18hq.tar.gz` and `cadenza_cad1_task1_core_metadata.tar.gz` +packages from the [Cadenza Challenge website](https://cadenza-challenge.github.io/). +2. Unpack packages under the same root directory. +3. Run the script + +## Unpack the data + +To unpack the data run: + +```bash +tar -xvzf +``` + +## Generate the dataset + +To generate the dataset, set the `path.root` parameter in the `generate_dataset/config.yaml` +to where you unpacked the data. Then run: + +```bash +python generates_at_mic_musdb18.py +``` + +or, run the script with the `path.root` parameter: + +```bash +python generates_at_mic_musdb18.py path.root +``` + +The script will generate the dataset in the `path.root` directory. + +The script should create the `at_mic_microphone` where all music samples +picked up by the microphones (at the mic) are saved. + +In the next example, `A Classic Education - NightOwl-hp_0103` corresponds to the +song `A Classic Education - NightOwl` with the `hp_0103` head position. + +```text +cadenza_data +├───audio +| ├───at_mic_music +| | └───train (20.2 GB) +| | ├───A Classic Education - NightOwl-hp_0103 +| | | | bass.wav +| | | | drums.wav +| | | | other.wav +| | | | vocals.wav +| | | | mixture.wav +| | | +| | ├───A Classic Education - NightOwl-hp_0138 +| | | .... +| | +| ├───hrtf (336 kB) +| | +| └───music +| └───train (20.2 GB) +| +└───metadata (328 kB) +| gains.json + | at_mic_music.train.json + | ... +``` From d5db7710615d271fb974d8563921e106f2c7b075 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 12:32:23 +0100 Subject: [PATCH 17/85] readme gen dataset Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/generate_dataset/README.md | 2 +- recipes/cad_icassp_2024/generate_dataset/config.yaml | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/recipes/cad_icassp_2024/generate_dataset/README.md b/recipes/cad_icassp_2024/generate_dataset/README.md index 5c3556a05..2d4236d0f 100644 --- a/recipes/cad_icassp_2024/generate_dataset/README.md +++ b/recipes/cad_icassp_2024/generate_dataset/README.md @@ -44,7 +44,7 @@ song `A Classic Education - NightOwl` with the `hp_0103` head position. cadenza_data ├───audio | ├───at_mic_music -| | └───train (20.2 GB) +| | └───train (80.8 GB) | | ├───A Classic Education - NightOwl-hp_0103 | | | | bass.wav | | | | drums.wav diff --git a/recipes/cad_icassp_2024/generate_dataset/config.yaml b/recipes/cad_icassp_2024/generate_dataset/config.yaml index 70a7ba784..0e1f04ff0 100644 --- a/recipes/cad_icassp_2024/generate_dataset/config.yaml +++ b/recipes/cad_icassp_2024/generate_dataset/config.yaml @@ -5,7 +5,6 @@ path: hrtf_dir: ${path.root}/audio/hrtf scene_file: ${path.metadata_dir}/scenes.train.json music_file: ${path.metadata_dir}/musdb18.train.json - gain_file: ${path.metadata_dir}/gains.json head_positions_file: ${path.metadata_dir}/head_positions.json output_music_dir: ${path.root}/audio/at_mic_music # at microphone musdb18 dataset output_music_file: ${path.metadata_dir}/at_mic_music.train.json From dd8aa75e8343cd9a2748f0a41e954c41db9fda77 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Tue, 12 Sep 2023 12:11:11 +0000 Subject: [PATCH 18/85] [pre-commit.ci] pre-commit-autoupdate MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/asottile/pyupgrade: v3.9.0 → v3.10.1](https://github.com/asottile/pyupgrade/compare/v3.9.0...v3.10.1) - [github.com/psf/black: 23.7.0 → 23.9.1](https://github.com/psf/black/compare/23.7.0...23.9.1) - [github.com/DavidAnson/markdownlint-cli2: v0.8.1 → v0.9.2](https://github.com/DavidAnson/markdownlint-cli2/compare/v0.8.1...v0.9.2) - [github.com/pycqa/flake8.git: 6.0.0 → 6.1.0](https://github.com/pycqa/flake8.git/compare/6.0.0...6.1.0) - [github.com/pre-commit/mirrors-mypy: v1.4.1 → v1.5.1](https://github.com/pre-commit/mirrors-mypy/compare/v1.4.1...v1.5.1) - [github.com/astral-sh/ruff-pre-commit: v0.0.280 → v0.0.288](https://github.com/astral-sh/ruff-pre-commit/compare/v0.0.280...v0.0.288) - [github.com/pycqa/pylint: v3.0.0a6 → v3.0.0a7](https://github.com/pycqa/pylint/compare/v3.0.0a6...v3.0.0a7) --- .pre-commit-config.yaml | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 7167117a7..04742edae 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -20,25 +20,25 @@ repos: - id: check-toml - repo: https://github.com/asottile/pyupgrade - rev: v3.9.0 + rev: v3.10.1 hooks: - id: pyupgrade args: [--py38-plus] - repo: https://github.com/psf/black - rev: 23.7.0 + rev: 23.9.1 hooks: - id: black types: [python] additional_dependencies: ["click==8.0.4"] - repo: https://github.com/DavidAnson/markdownlint-cli2 - rev: v0.8.1 + rev: v0.9.2 hooks: - id: markdownlint-cli2 - repo: https://github.com/pycqa/flake8.git - rev: 6.0.0 + rev: 6.1.0 hooks: - id: flake8 additional_dependencies: [flake8-print, Flake8-pyproject] @@ -65,7 +65,7 @@ repos: - id: nbstripout - repo: https://github.com/pre-commit/mirrors-mypy - rev: v1.4.1 + rev: v1.5.1 hooks: - id: mypy args: @@ -73,13 +73,13 @@ repos: - repo: https://github.com/astral-sh/ruff-pre-commit # Ruff version. - rev: "v0.0.280" + rev: "v0.0.288" hooks: - id: ruff # Serious pylint errors that will be enforced by CI - repo: https://github.com/pycqa/pylint - rev: v3.0.0a6 + rev: v3.0.0a7 hooks: - id: pylint args: From ee4c61cabe7284bc30770d9cd1fa35fbad1f4244 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 14:56:37 +0100 Subject: [PATCH 19/85] fix output from gen dataset Signed-off-by: Gerardo Roa Dabike --- .../generate_dataset/generates_at_mic_musdb18.py | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py index 2b73780ba..571a77903 100644 --- a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py +++ b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py @@ -155,19 +155,17 @@ def run(cfg: DictConfig) -> None: } # create output metadata content - out_music = [] + out_music = {} for idx, sample in enumerate(toprocess_samples.items(), 1): sample_name, sample_detail = sample music = music_metadata[sample_detail["music"]] head_position = sample_detail["head_position"] - out_music.append( - { - "Track Name": sample_name, - "Split": music["Split"], - "Path": f"{music['Split']}/{sample_name}", - } - ) + out_music[sample_name] = { + "Track Name": sample_name, + "Split": music["Split"], + "Path": f"{music['Split']}/{sample_name}", + } if sample_name in precreated_samples: logger.info( From 27b9d515a8a9b738a2d3499c13c319b84e542e40 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 15:03:45 +0100 Subject: [PATCH 20/85] better meta at_mic_music Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/enhance.py | 1 + .../generate_dataset/generates_at_mic_musdb18.py | 5 +++++ 2 files changed, 6 insertions(+) diff --git a/recipes/cad_icassp_2024/baseline/enhance.py b/recipes/cad_icassp_2024/baseline/enhance.py index f93394bca..aef38e1e9 100644 --- a/recipes/cad_icassp_2024/baseline/enhance.py +++ b/recipes/cad_icassp_2024/baseline/enhance.py @@ -202,6 +202,7 @@ def enhance(config: DictConfig) -> None: scene_listener_pairs = make_scene_listener_list( scenes_listeners, config.evaluate.small_test ) + scene_listener_pairs = scene_listener_pairs[ config.evaluate.batch :: config.evaluate.batch_size ] diff --git a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py index 571a77903..4cbc488e9 100644 --- a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py +++ b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py @@ -165,6 +165,8 @@ def run(cfg: DictConfig) -> None: "Track Name": sample_name, "Split": music["Split"], "Path": f"{music['Split']}/{sample_name}", + "Original Track Name": music["Track Name"], + "Head Position": head_position, } if sample_name in precreated_samples: @@ -209,6 +211,9 @@ def run(cfg: DictConfig) -> None: with open(cfg.path.output_music_file, "w", encoding="utf-8") as f: json.dump(out_music, f, indent=4) + logger.info(f"Saved metadata to: {cfg.path.output_music_file}") + logger.info("Done.") + # pylint: disable = no-value-for-parameter if __name__ == "__main__": From 73a07e0635a45c424deabfc0e16d57898c32513d Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 16:24:10 +0100 Subject: [PATCH 21/85] Utilities from v0.3 not in v0.4 Signed-off-by: Gerardo Roa Dabike --- clarity/utils/flac_encoder.py | 262 +++++++++++++++++++++++++++++ clarity/utils/signal_processing.py | 34 ++++ 2 files changed, 296 insertions(+) create mode 100644 clarity/utils/flac_encoder.py diff --git a/clarity/utils/flac_encoder.py b/clarity/utils/flac_encoder.py new file mode 100644 index 000000000..55718a98c --- /dev/null +++ b/clarity/utils/flac_encoder.py @@ -0,0 +1,262 @@ +""" +Class for encoding and decoding audio signals + using flac compression. +""" +from __future__ import annotations + +import logging +import tempfile + +# pylint: disable=import-error, protected-access +from pathlib import Path + +import numpy as np +import pyflac as pf +import soundfile as sf + +logger = logging.getLogger(__name__) + + +class WavEncoder(pf.encoder._Encoder): + """ + Class offers an adaptation of the pyflac.encoder.FileEncoder + to work directly with WAV signals as input. + + """ + + def __init__( + self, + signal: np.ndarray, + sample_rate: int, + output_file: str | Path | None = None, + compression_level: int = 5, + blocksize: int = 0, + streamable_subset: bool = True, + verify: bool = False, + ) -> None: + """ + Initialise the encoder. + + Args: + signal (np.ndarray): The raw audio data to be encoded. + sample_rate (int): The sample rate of the audio data. + output_file (str | Path | None): Path to the output FLAC file, + a temporary file will be created if unspecified. + compression_level (int): The compression level parameter that + varies from 0 (fastest) to 8 (slowest). The default setting + is 5, see https://en.wikipedia.org/wiki/FLAC for more details. + blocksize (int): The size of the block to be returned in the + callback. The default is 0 which allows libFLAC to determine + the best block size. + streamable_subset (bool): Whether to use the streamable subset for encoding. + If true the encoder will check settings for compatibility. If false, the + settings may take advantage of the full range that the format allows. + verify (bool): If `True`, the encoder will verify it's own + encoded output by feeding it through an internal decoder and + comparing the original signal against the decoded signal. + If a mismatch occurs, the `process` method will raise a + `EncoderProcessException`. Note that this will slow the + encoding process by the extra time required for decoding and comparison. + """ + super().__init__() + + self.__raw_audio = signal + self._sample_rate = sample_rate + + if output_file: + self.__output_file = ( + Path(output_file) if isinstance(output_file, str) else output_file + ) + else: + with tempfile.NamedTemporaryFile(suffix=".flac") as ofile: + self.__output_file = Path(ofile.name) + + self._blocksize = blocksize + self._compression_level = compression_level + self._streamable_subset = streamable_subset + self._verify = verify + self._initialised = False + + def _init(self): + """ + Initialise the encoder to write to a file. + + Raises: + EncoderInitException: if initialisation fails. + """ + c_output_filename = pf.encoder._ffi.new( + "char[]", str(self.__output_file).encode("utf-8") + ) + rc = pf.encoder._lib.FLAC__stream_encoder_init_file( + self._encoder, + c_output_filename, + pf.encoder._lib._progress_callback, + self._encoder_handle, + ) + pf.encoder._ffi.release(c_output_filename) + if rc != pf.encoder._lib.FLAC__STREAM_ENCODER_INIT_STATUS_OK: + raise pf.EncoderInitException(rc) + + self._initialised = True + + def process(self) -> bytes: + """ + Process the audio data from the WAV file. + + Returns: + (bytes): The FLAC encoded bytes. + + Raises: + EncoderProcessException: if an error occurs when processing the samples + """ + super().process(self.__raw_audio) + self.finish() + with open(self.__output_file, "rb") as f: + return f.read() + + +class FileDecoder(pf.decoder.FileDecoder): + def process(self) -> tuple[np.ndarray, int]: + """ + Overwritten version of the process method from the pyflac decoder. + Original process returns stereo signals in float64 format. + + In this version, the data is returned using the original number + of channels and in in16 format. + + Returns: + (tuple): A tuple of the decoded numpy audio array, and the sample rate + of the audio data. + + Raises: + DecoderProcessException: if any fatal read, write, or memory allocation + error occurred (meaning decoding must stop) + """ + result = pf.decoder._lib.FLAC__stream_decoder_process_until_end_of_stream( + self._decoder + ) + if self.state != pf.decoder.DecoderState.END_OF_STREAM and not result: + raise pf.DecoderProcessException(str(self.state)) + + self.finish() + self.__output.close() + return sf.read(str(self.__output_file), always_2d=False, dtype="int16") + + +class FlacEncoder: + """ + Class for encoding and decoding audio signals using FLAC + + It uses the pyflac library to encode and decode the audio data. + And offers convenient methods for encoding and decoding audio data. + """ + + def __init__(self, compression_level: int = 5) -> None: + """ + Initialise the compressor. + + Args: + compression_level (int): The compression level parameter that + varies from 0 (fastest) to 8 (slowest). The default setting + is 5, see https://en.wikipedia.org/wiki/FLAC for more details. + """ + self.compression_level = compression_level + + def encode( + self, + signal: np.ndarray, + sample_rate: int, + output_file: str | Path | None = None, + ) -> bytes: + """ + Method to encode the audio data using FLAC compressor. + + It creates a WavEncoder object and uses it to encode the audio data. + + Args: + signal (np.ndarray): The raw audio data to be compressed. + sample_rate (int): The sample rate of the audio data. + output_file (str | Path): Path to where to + save the output FLAC file. If not specified, a temporary file + will be created. + + Returns: + (bytes): The FLAC encoded audio signal. + + Raises: + ValueError: If the audio signal is not in `np.int16` format. + """ + if signal.dtype != np.int16: + logger.error( + f"FLAC encoder only supports 16-bit integer signals, " + f"but got {signal.dtype}" + ) + raise ValueError( + f"FLAC encoder only supports 16-bit integer signals, " + f"but got {signal.dtype}" + ) + + wav_encoder = WavEncoder( + signal=signal, + sample_rate=sample_rate, + compression_level=self.compression_level, + output_file=output_file, + ) + return wav_encoder.process() + + @staticmethod + def decode(input_filename: Path | str) -> tuple[np.ndarray, float]: + """ + Method to decode a flac file to wav audio data. + + It uses the pyflac library to decode the flac file. + + Args: + input_filename (pathlib.Path | str): Path to the input FLAC file. + + Returns: + (np.ndarray): The raw audio data. + + Raises: + FileNotFoundError: If the flac file to decode does not exist. + """ + input_filename = ( + Path(input_filename) if isinstance(input_filename, str) else input_filename + ) + + if not input_filename.exists(): + logger.error(f"File {input_filename} not found.") + raise FileNotFoundError(f"File {input_filename} not found.") + + decoder = FileDecoder(input_filename) + signal, sample_rate = decoder.process() + + return signal, float(sample_rate) + + +def read_flac_signal(filename: Path) -> tuple[np.ndarray, float]: + """Read a FLAC signal and return it as a numpy array + + Args: + filename (Path): The path to the FLAC file to read. + + Returns: + signal (np.ndarray): The decoded signal. + sample_rate (float): The sample rate of the signal. + """ + # Create encoder object + flac_encoder = FlacEncoder() + + # Decode FLAC file + signal, sample_rate = flac_encoder.decode( + filename, + ) + signal = (signal / 32768.0).astype(np.float32) + + # Load scale factor + if filename.with_suffix(".txt").exists(): + with open(filename.with_suffix(".txt"), encoding="utf-8") as fp: + max_value = float(fp.read()) + # Scale signal + signal *= max_value + return signal, sample_rate diff --git a/clarity/utils/signal_processing.py b/clarity/utils/signal_processing.py index 0e9078ee6..fb7fd391f 100644 --- a/clarity/utils/signal_processing.py +++ b/clarity/utils/signal_processing.py @@ -1,12 +1,32 @@ """Signal processing utilities.""" from __future__ import annotations +# pylint: disable=import-error import numpy as np import scipy import soxr from numpy import ndarray +def clip_signal(signal: np.ndarray, soft_clip: bool = False) -> tuple[np.ndarray, int]: + """Clip the signal. + + Args: + signal (np.ndarray): Signal to be clipped and saved. + soft_clip (bool): Whether to use soft clipping. + + Returns: + signal (np.ndarray): Clipped signal. + n_clipped (int): Number of samples clipped. + """ + + if soft_clip: + signal = np.tanh(signal) + n_clipped = np.sum(np.abs(signal) > 1.0) + signal = np.clip(signal, -1.0, 1.0) + return signal, int(n_clipped) + + def compute_rms(signal: ndarray) -> float: """Compute RMS of signal @@ -86,3 +106,17 @@ def resample( ) raise ValueError(f"Unknown resampling method: {method}") + + +def to_16bit(signal: np.ndarray) -> np.ndarray: + """Convert the signal to 16 bit. + + Args: + signal (np.ndarray): Signal to be converted. + + Returns: + signal (np.ndarray): Converted signal. + """ + signal = signal * 32768.0 + signal = np.clip(signal, -32768.0, 32767.0) + return signal.astype(np.dtype("int16")) From 4ebc0c7fc3f0f8a1a906fcf246595d3480dc381b Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 16:29:47 +0100 Subject: [PATCH 22/85] Add apply HA Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/evaluate.py | 60 +++++++++++++++++--- 1 file changed, 52 insertions(+), 8 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index e728af1a0..1adcd3ae2 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -15,9 +15,10 @@ from numpy import ndarray from omegaconf import DictConfig +from clarity.enhancer.compressor import Compressor from clarity.enhancer.nalr import NALR from clarity.evaluator.haaqi import compute_haaqi -from clarity.utils.audiogram import Listener +from clarity.utils.audiogram import Audiogram, Listener from clarity.utils.file_io import read_signal from clarity.utils.signal_processing import compute_rms @@ -93,6 +94,37 @@ def add_result( ) +def apply_ha( + enhancer: NALR, + compressor: Compressor | None, + signal: ndarray, + audiogram: Audiogram, + apply_compressor: bool = False, +) -> np.ndarray: + """ + Apply NAL-R prescription hearing aid to a signal. + + Args: + enhancer (NALR): A NALR object that enhances the signal. + compressor (Compressor | None): A Compressor object that compresses the signal. + signal (ndarray): An ndarray representing the audio signal. + audiogram (Audiogram): An Audiogram object representing the listener's + audiogram. + apply_compressor (bool): Whether to apply the compressor. + + Returns: + An ndarray representing the processed signal. + """ + nalr_fir, _ = enhancer.build(audiogram) + proc_signal = enhancer.apply(nalr_fir, signal) + if apply_compressor: + if compressor is None: + raise ValueError("Compressor must be provided to apply compressor.") + + proc_signal, _, _ = compressor.process(proc_signal) + return proc_signal + + def apply_gains(stems: dict, sample_rate: float, gains: dict) -> dict: """Apply gain to the signal by using LUFS. @@ -292,28 +324,40 @@ def run_calculate_aq(config: DictConfig) -> None: ) ) + # Compute the scores + # First, we apply NAL-R to the reference signal # Compute the score for left channel - nalr_fir, _ = enhancer.build(listener.audiogram_left) - left_reference = enhancer.apply(nalr_fir, reference_mixture[:, 0]) + left_reference = apply_ha( + enhancer=enhancer, + compressor=None, + signal=reference_mixture[:, 0], + audiogram=listener.audiogram_left, + apply_compressor=False, + ) left_score = compute_haaqi( processed_signal=enhanced_signal[:, 0], reference_signal=left_reference, audiogram=listener.audiogram_left, sample_rate=config.sample_rate, equalisation=2, - level1=65 - 20 * np.log10(compute_rms(left_reference)), + level1=65 - 20 * np.log10(compute_rms(reference_mixture[:, 0])), ) # Compute score for right channel - nalr_fir, _ = enhancer.build(listener.audiogram_right) - right_reference = enhancer.apply(nalr_fir, reference_mixture[:, 1]) + right_reference = apply_ha( + enhancer=enhancer, + compressor=None, + signal=reference_mixture[:, 1], + audiogram=listener.audiogram_right, + apply_compressor=False, + ) right_score = compute_haaqi( processed_signal=enhanced_signal[:, 1], reference_signal=right_reference, - audiogram=listener.audiogram_left, + audiogram=listener.audiogram_right, sample_rate=config.sample_rate, equalisation=2, - level1=65 - 20 * np.log10(compute_rms(left_reference)), + level1=65 - 20 * np.log10(compute_rms(right_reference)), ) # Save scores From d45a3acf8dac18700f818e7d9d9b14ca59628f2d Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 16:31:57 +0100 Subject: [PATCH 23/85] output sample rate in config Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/config.yaml | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/config.yaml b/recipes/cad_icassp_2024/baseline/config.yaml index caba995a5..615d4c12c 100644 --- a/recipes/cad_icassp_2024/baseline/config.yaml +++ b/recipes/cad_icassp_2024/baseline/config.yaml @@ -1,5 +1,5 @@ path: - root: /media/gerardo/Extended_old/cadenza_data/icassp_2024 + root: ??? metadata_dir: ${path.root}/metadata music_dir: ${path.root}/audio/at_mic_music gains_file: ${path.metadata_dir}/gains.json @@ -11,6 +11,7 @@ path: exp_folder: ./exp # folder to store enhanced signals and final results sample_rate: 44100 +remix_sample_rate: 32000 nalr: nfir: 220 @@ -32,7 +33,7 @@ separator: evaluate: set_random_seed: True - small_test: True + small_test: False batch_size: 1 # Number of batches batch: 0 # Batch number to evaluate From 0cffe9a9d1a0175c10ee470dc45b03561aa3ba8f Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 16:32:15 +0100 Subject: [PATCH 24/85] save flac and 32 kHz Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/enhance.py | 118 +++++++++++++------- 1 file changed, 77 insertions(+), 41 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/enhance.py b/recipes/cad_icassp_2024/baseline/enhance.py index aef38e1e9..0f8f49bad 100644 --- a/recipes/cad_icassp_2024/baseline/enhance.py +++ b/recipes/cad_icassp_2024/baseline/enhance.py @@ -9,7 +9,6 @@ import hydra import numpy as np import torch -from evaluate import apply_gains, make_scene_listener_list, remix_stems from numpy import ndarray from omegaconf import DictConfig from source_separation_utils import get_device, separate_sources @@ -17,17 +16,83 @@ from clarity.enhancer.compressor import Compressor from clarity.enhancer.nalr import NALR -from clarity.utils.audiogram import Audiogram, Listener -from clarity.utils.file_io import read_signal, write_signal +from clarity.utils.audiogram import Listener +from clarity.utils.file_io import read_signal +from clarity.utils.flac_encoder import FlacEncoder from clarity.utils.signal_processing import ( + clip_signal, denormalize_signals, normalize_signal, resample, + to_16bit, +) +from recipes.cad_icassp_2024.baseline.evaluate import ( + apply_gains, + apply_ha, + make_scene_listener_list, + remix_stems, ) logger = logging.getLogger(__name__) +def save_flac_signal( + signal: np.ndarray, + filename: Path, + signal_sample_rate, + output_sample_rate, + do_clip_signal: bool = False, + do_soft_clip: bool = False, + do_scale_signal: bool = False, +) -> None: + """ + Function to save output signals. + + - The output signal will be resample to ``output_sample_rate`` + - The output signal will be clipped to [-1, 1] if ``do_clip_signal`` is True + and use soft clipped if ``do_soft_clip`` is True. Note that if + ``do_clip_signal`` is False, ``do_soft_clip`` will be ignored. + Note that if ``do_clip_signal`` is True, ``do_scale_signal`` will be ignored. + - The output signal will be scaled to [-1, 1] if ``do_scale_signal`` is True. + If signal is scale, the scale factor will be saved in a TXT file. + Note that if ``do_clip_signal`` is True, ``do_scale_signal`` will be ignored. + - The output signal will be saved as a FLAC file. + + Args: + signal (np.ndarray) : Signal to save + filename (Path) : Path to save signal + signal_sample_rate (int) : Sample rate of the input signal + output_sample_rate (int) : Sample rate of the output signal + do_clip_signal (bool) : Whether to clip signal + do_soft_clip (bool) : Whether to apply soft clipping + do_scale_signal (bool) : Whether to scale signal + """ + # Resample signal to expected output sample rate + if signal_sample_rate != output_sample_rate: + signal = resample(signal, signal_sample_rate, output_sample_rate) + + if do_scale_signal: + # Scale stem signal + max_value = np.max(np.abs(signal)) + signal = signal / max_value + + # Save scale factor + with open(filename.with_suffix(".txt"), "w", encoding="utf-8") as file: + file.write(f"{max_value}") + + elif do_clip_signal: + # Clip the signal + signal, n_clipped = clip_signal(signal, do_soft_clip) + if n_clipped > 0: + logger.warning(f"Writing {filename}: {n_clipped} samples clipped") + + # Convert signal to 16-bit integer + signal = to_16bit(signal) + + # Create flac encoder object to compress and save the signal + FlacEncoder().encode(signal, output_sample_rate, filename) + + # pylint: disable=unused-argument def decompose_signal( model: torch.nn.Module, @@ -85,37 +150,6 @@ def decompose_signal( return dict(zip(sources_list, sources)) -def apply_baseline_ha( - enhancer: NALR, - compressor: Compressor | None, - signal: ndarray, - audiogram: Audiogram, - apply_compressor: bool = False, -) -> np.ndarray: - """ - Apply NAL-R prescription hearing aid to a signal. - - Args: - enhancer (NALR): A NALR object that enhances the signal. - compressor (Compressor | None): A Compressor object that compresses the signal. - signal (ndarray): An ndarray representing the audio signal. - audiogram (Audiogram): An Audiogram object representing the listener's - audiogram. - apply_compressor (bool): Whether to apply the compressor. - - Returns: - An ndarray representing the processed signal. - """ - nalr_fir, _ = enhancer.build(audiogram) - proc_signal = enhancer.apply(nalr_fir, signal) - if apply_compressor: - if compressor is None: - raise ValueError("Compressor must be provided to apply compressor.") - - proc_signal, _, _ = compressor.process(proc_signal) - return proc_signal - - def process_remix_for_listener( signal: ndarray, enhancer: NALR, @@ -135,10 +169,10 @@ def process_remix_for_listener( Returns: ndarray: Processed signal. """ - left_output = apply_baseline_ha( + left_output = apply_ha( enhancer, compressor, signal[:, 0], listener.audiogram_left, apply_compressor ) - right_output = apply_baseline_ha( + right_output = apply_ha( enhancer, compressor, signal[:, 1], listener.audiogram_right, apply_compressor ) @@ -264,13 +298,15 @@ def enhance(config: DictConfig) -> None: / f"{song_name}" / f"{scene_id}_{listener.id}_remix.wav" ) + filename.parent.mkdir(parents=True, exist_ok=True) - write_signal( - filename=filename, + save_flac_signal( signal=enhanced_signal, - sample_rate=config.sample_rate, - floating_point=False, - strict=False, + filename=filename, + signal_sample_rate=config.sample_rate, + output_sample_rate=config.remix_sample_rate, + do_clip_signal=True, + do_soft_clip=config.soft_clip, ) logger.info("Done!") From 4c510c891eea0a3f39b31196730644cd3186a2f6 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 16:34:07 +0100 Subject: [PATCH 25/85] save flac and 32 kHz Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/enhance.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/recipes/cad_icassp_2024/baseline/enhance.py b/recipes/cad_icassp_2024/baseline/enhance.py index 0f8f49bad..eec12d75f 100644 --- a/recipes/cad_icassp_2024/baseline/enhance.py +++ b/recipes/cad_icassp_2024/baseline/enhance.py @@ -296,7 +296,7 @@ def enhance(config: DictConfig) -> None: enhanced_folder / f"{listener.id}" / f"{song_name}" - / f"{scene_id}_{listener.id}_remix.wav" + / f"{scene_id}_{listener.id}_remix.flac" ) filename.parent.mkdir(parents=True, exist_ok=True) From 32504bdeb723eb356dc7f9d2acf93f4e9b2a3af6 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 16:37:50 +0100 Subject: [PATCH 26/85] allows processed and reference different sample rate Signed-off-by: Gerardo Roa Dabike --- clarity/evaluator/haaqi/haaqi.py | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/clarity/evaluator/haaqi/haaqi.py b/clarity/evaluator/haaqi/haaqi.py index f4d19662c..b3ba3b035 100644 --- a/clarity/evaluator/haaqi/haaqi.py +++ b/clarity/evaluator/haaqi/haaqi.py @@ -178,8 +178,9 @@ def haaqi_v1( def compute_haaqi( processed_signal: ndarray, reference_signal: ndarray, + processed_sample_rate: float, + reference_sample_rate: float, audiogram: Audiogram, - sample_rate: float, equalisation: int = 1, level1: float = 65.0, ) -> float: @@ -191,8 +192,9 @@ def compute_haaqi( reference_signal (np.ndarray): Input reference speech signal with no noise or distortion. If a hearing loss is specified, NAL-R equalization is optional + processed_sample_rate (float): Sampling rate in Hz for processed signal. + reference_sample_rate (float): Sampling rate in Hz for reference signal. audiogram (Audiogram): Audiogram object. - sample_rate (int): Sample rate in Hz. equalisation (int): hearing loss equalization mode for reference signal: 1 = no EQ has been provided, the function will add NAL-R 2 = NAL-R EQ has already been added to the reference signal @@ -211,9 +213,9 @@ def compute_haaqi( score, _, _, _ = haaqi_v1( reference=reference_signal, - reference_freq=sample_rate, + reference_freq=reference_sample_rate, processed=processed_signal, - processed_freq=sample_rate, + processed_freq=processed_sample_rate, audiogram=audiogram, equalisation=equalisation, level1=level1, From 19180e33bdb7de2d4e27fb992978656b6882be0a Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 16:39:01 +0100 Subject: [PATCH 27/85] allows processed and reference different sample rate Signed-off-by: Gerardo Roa Dabike --- tests/evaluator/haaqi/test_haaqi.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/tests/evaluator/haaqi/test_haaqi.py b/tests/evaluator/haaqi/test_haaqi.py index c38ec5a60..bf29363e0 100644 --- a/tests/evaluator/haaqi/test_haaqi.py +++ b/tests/evaluator/haaqi/test_haaqi.py @@ -1,4 +1,5 @@ """Tests for haaqi module""" +# pylint: disable=import-error import numpy as np import pytest @@ -57,8 +58,9 @@ def test_compute_haaqi(levels, freqs, expected_result): score = compute_haaqi( processed_signal=enh_signal, reference_signal=ref_signal, + processed_sample_rate=sample_rate, + reference_sample_rate=sample_rate, audiogram=audiogram, - sample_rate=sample_rate, ) # Check that the score is a float between 0 and 1 From e6912d787451ede14bce0089cb984b166dd184c6 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 16:51:50 +0100 Subject: [PATCH 28/85] reading flac and evaluate Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/evaluate.py | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index 1adcd3ae2..eae37963f 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -20,6 +20,7 @@ from clarity.evaluator.haaqi import compute_haaqi from clarity.utils.audiogram import Audiogram, Listener from clarity.utils.file_io import read_signal +from clarity.utils.flac_encoder import read_flac_signal from clarity.utils.signal_processing import compute_rms logger = logging.getLogger(__name__) @@ -293,7 +294,7 @@ def run_calculate_aq(config: DictConfig) -> None: logger.info( f"[{idx:03d}/{num_scenes:03d}] " - f"Processing {song_name} for listener {listener_id}" + f"Evaluating {song_name} for listener {listener_id}" ) # Load reference signals @@ -315,12 +316,12 @@ def run_calculate_aq(config: DictConfig) -> None: listener = listener_dict[listener_id] # Load enhanced signal - enhanced_signal = read_signal( + enhanced_signal, _ = read_flac_signal( Path( enhanced_folder / f"{listener.id}" / f"{song_name}" - / f"{scene_id}_{listener.id}_remix.wav" + / f"{scene_id}_{listener.id}_remix.flac" ) ) @@ -337,8 +338,9 @@ def run_calculate_aq(config: DictConfig) -> None: left_score = compute_haaqi( processed_signal=enhanced_signal[:, 0], reference_signal=left_reference, + processed_sample_rate=config.remix_sample_rate, + reference_sample_rate=config.sample_rate, audiogram=listener.audiogram_left, - sample_rate=config.sample_rate, equalisation=2, level1=65 - 20 * np.log10(compute_rms(reference_mixture[:, 0])), ) @@ -354,8 +356,9 @@ def run_calculate_aq(config: DictConfig) -> None: right_score = compute_haaqi( processed_signal=enhanced_signal[:, 1], reference_signal=right_reference, + processed_sample_rate=config.remix_sample_rate, + reference_sample_rate=config.sample_rate, audiogram=listener.audiogram_right, - sample_rate=config.sample_rate, equalisation=2, level1=65 - 20 * np.log10(compute_rms(right_reference)), ) From 6b1db3ce9a3686fb9f3d4b6ea11700fa3f43ea91 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 18:04:24 +0100 Subject: [PATCH 29/85] test enhance Signed-off-by: Gerardo Roa Dabike --- tests/recipes/cad_icassp_2024/__init__.py | 0 .../cad_icassp_2024/baseline/__init__.py | 0 .../cad_icassp_2024/baseline/test_enhance.py | 134 ++++++++++++++++++ ...t_enhance.test_decompose_signal_demucs.npy | Bin 0 -> 706145 bytes ...nhance.test_decompose_signal_openunmix.npy | Bin 0 -> 706145 bytes ...rocess_remix_for_listener_w_compressor.npy | Bin 0 -> 3680 bytes ...ocess_remix_for_listener_wo_compressor.npy | Bin 0 -> 3680 bytes 7 files changed, 134 insertions(+) create mode 100644 tests/recipes/cad_icassp_2024/__init__.py create mode 100644 tests/recipes/cad_icassp_2024/baseline/__init__.py create mode 100644 tests/recipes/cad_icassp_2024/baseline/test_enhance.py create mode 100644 tests/resources/recipes/cad_icassp_2024/test_enhance.test_decompose_signal_demucs.npy create mode 100644 tests/resources/recipes/cad_icassp_2024/test_enhance.test_decompose_signal_openunmix.npy create mode 100644 tests/resources/recipes/cad_icassp_2024/test_enhance.test_process_remix_for_listener_w_compressor.npy create mode 100644 tests/resources/recipes/cad_icassp_2024/test_enhance.test_process_remix_for_listener_wo_compressor.npy diff --git a/tests/recipes/cad_icassp_2024/__init__.py b/tests/recipes/cad_icassp_2024/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/tests/recipes/cad_icassp_2024/baseline/__init__.py b/tests/recipes/cad_icassp_2024/baseline/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/tests/recipes/cad_icassp_2024/baseline/test_enhance.py b/tests/recipes/cad_icassp_2024/baseline/test_enhance.py new file mode 100644 index 000000000..36fac0a43 --- /dev/null +++ b/tests/recipes/cad_icassp_2024/baseline/test_enhance.py @@ -0,0 +1,134 @@ +"""Tests for the enhance module""" +# pylint:: disable=import-error +from pathlib import Path + +import numpy as np +import pytest +import torch +from torchaudio.pipelines import HDEMUCS_HIGH_MUSDB + +from clarity.enhancer.compressor import Compressor +from clarity.enhancer.nalr import NALR +from clarity.utils.audiogram import Audiogram, Listener +from clarity.utils.flac_encoder import read_flac_signal +from recipes.cad_icassp_2024.baseline.enhance import ( + decompose_signal, + process_remix_for_listener, + save_flac_signal, +) + +BASE_DIR = Path.cwd() +RESOURCES = BASE_DIR / "tests" / "resources" / "recipes" / "cad_icassp_2024" + + +def test_save_flac_signal(tmp_path): + """Test save flac signal""" + np.random.seed(2024) + sample_rate = 44100 + duration = 0.5 + signal = np.random.rand(int(sample_rate * duration)) + + filename = Path(tmp_path) / "signal.flac" + save_flac_signal(signal, filename, sample_rate, sample_rate) + + signal_out, sample_rate_out = read_flac_signal(filename) + assert np.sum(signal) == pytest.approx(11040.050741283) + assert np.sum(signal_out) == pytest.approx(11039.716) + assert sample_rate_out == sample_rate + + +@pytest.mark.parametrize( + "separation_model", + [ + pytest.param("demucs"), + pytest.param("openunmix", marks=pytest.mark.slow), + ], +) +def test_decompose_signal(separation_model): + """Takes a signal and decomposes it into + VDBO sources using the HDEMUCS model""" + np.random.seed(2024) + # Load Separation Model + if separation_model == "demucs": + model = HDEMUCS_HIGH_MUSDB.get_model() + model_sample_rate = HDEMUCS_HIGH_MUSDB.sample_rate + sources_order = model.sources + + elif separation_model == "openunmix": + model = torch.hub.load("sigsep/open-unmix-pytorch", "umxhq") + model_sample_rate = model.sample_rate + sources_order = ["vocals", "drums", "bass", "other"] + + device = torch.device("cpu") + model.to(device) + + # Create a mock signal to decompose + sample_rate = 44100 + duration = 0.5 + signal = np.random.uniform(size=(1, 2, int(sample_rate * duration))).astype( + np.float32 + ) + + # Call the decompose_signal function and check that the output has the expected keys + cfs = np.array([250, 500, 1000, 2000, 4000, 6000, 8000, 9000, 10000]) + audiogram = Audiogram(levels=np.ones(9), frequencies=cfs) + listener = Listener(audiogram, audiogram) + output = decompose_signal( + model, + model_sample_rate, + signal, + sample_rate, + device, + sources_order, + listener, + ) + expected_results = np.load( + RESOURCES / f"test_enhance.test_decompose_signal_{separation_model}.npy", + allow_pickle=True, + )[()] + + for key, item in output.items(): + np.testing.assert_array_almost_equal(item, expected_results[key]) + + +@pytest.mark.parametrize( + "apply_compressor", + [ + True, + False, + ], +) +def test_process_remix_for_listener(apply_compressor): + """Test the process remix for listener""" + np.random.seed(2024) + sample_rate = 44100 + duration = 0.5 + signal = np.random.uniform(size=(2, int(duration * sample_rate))) + + audiogram = Audiogram( + levels=np.ones(9), + frequencies=np.array([250, 500, 1000, 2000, 4000, 6000, 8000, 9000, 10000]), + ) + listener = Listener(audiogram_left=audiogram, audiogram_right=audiogram) + enhancer = NALR(nfir=220, sample_rate=16000) + compressor = Compressor( + threshold=0.35, attenuation=0.1, attack=50, release=1000, rms_buffer_size=0.064 + ) + + output = process_remix_for_listener( + signal, enhancer, compressor, listener, apply_compressor=apply_compressor + ) + + if apply_compressor: + expected_results = np.load( + RESOURCES / "test_enhance.test_process_remix_for_listener_w_compressor.npy", + allow_pickle=True, + )[()] + else: + expected_results = np.load( + RESOURCES + / "test_enhance.test_process_remix_for_listener_wo_compressor.npy", + allow_pickle=True, + )[()] + + assert np.sum(output) == pytest.approx(np.sum(expected_results)) diff --git 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z+wJ5U*S%Rp>C4gV;2%S`$*)G()u#|ceq%+9M?X^bf8o%f*N@(vS|&t{H=#TUKA~KO zYE+iCW14*68A?3rC0=nZ3#gSmzd=*T1#O3JQ(R5T!R;&0haUMAga1Ai{Ehzi{j@WMb~&r@0{5b;QC046n{v+cogJ-JG-sAa+(zS;;nA}zf<)~dnp zA;m|le9eGZ%a*&@gh5F{I&XS%1k?JEv+Y5yk+@E@vTC}UAUllSR$1C>8Gc5wGEKJ|pL|6{j7eQv zr@IgXgY3m`RlUfMUHQkb)TaHYeVx%|DW+PfqE}8YUCs17K hl_GAu0e8a{fad8^F#ETTcv|5N7-=-;dqcYi{s(?j`n>=E literal 0 HcmV?d00001 From a85508e87a0fdf1e98b776dae8a30ee50f9a11aa Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 18:05:36 +0100 Subject: [PATCH 30/85] move source separation to utils Signed-off-by: Gerardo Roa Dabike --- .../utils/source_separation.py | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename recipes/cad_icassp_2024/baseline/source_separation_utils.py => clarity/utils/source_separation.py (100%) diff --git a/recipes/cad_icassp_2024/baseline/source_separation_utils.py b/clarity/utils/source_separation.py similarity index 100% rename from recipes/cad_icassp_2024/baseline/source_separation_utils.py rename to clarity/utils/source_separation.py From 4a2667b28d325ac3215edeecb67064385a82c32e Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 18:06:32 +0100 Subject: [PATCH 31/85] move source separation to utils Signed-off-by: Gerardo Roa Dabike --- .../{source_separation.py => source_separation_support.py} | 0 recipes/cad_icassp_2024/baseline/enhance.py | 2 +- 2 files changed, 1 insertion(+), 1 deletion(-) rename clarity/utils/{source_separation.py => source_separation_support.py} (100%) diff --git a/clarity/utils/source_separation.py b/clarity/utils/source_separation_support.py similarity index 100% rename from clarity/utils/source_separation.py rename to clarity/utils/source_separation_support.py diff --git a/recipes/cad_icassp_2024/baseline/enhance.py b/recipes/cad_icassp_2024/baseline/enhance.py index eec12d75f..9f962fd64 100644 --- a/recipes/cad_icassp_2024/baseline/enhance.py +++ b/recipes/cad_icassp_2024/baseline/enhance.py @@ -11,7 +11,6 @@ import torch from numpy import ndarray from omegaconf import DictConfig -from source_separation_utils import get_device, separate_sources from torchaudio.pipelines import HDEMUCS_HIGH_MUSDB from clarity.enhancer.compressor import Compressor @@ -26,6 +25,7 @@ resample, to_16bit, ) +from clarity.utils.source_separation_support import get_device, separate_sources from recipes.cad_icassp_2024.baseline.evaluate import ( apply_gains, apply_ha, From 7e953cb0a4aabc3d25f4a5f9bbc9ea95f707d7cc Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 18:12:06 +0100 Subject: [PATCH 32/85] test for source separation to utils Signed-off-by: Gerardo Roa Dabike --- tests/utils/test_source_separation_support.py | 66 +++++++++++++++++++ 1 file changed, 66 insertions(+) create mode 100644 tests/utils/test_source_separation_support.py diff --git a/tests/utils/test_source_separation_support.py b/tests/utils/test_source_separation_support.py new file mode 100644 index 000000000..3f56514c6 --- /dev/null +++ b/tests/utils/test_source_separation_support.py @@ -0,0 +1,66 @@ +""" Test module for the source separation support""" +# pylint: disable=import-error +from pathlib import Path + +import numpy as np +import torch + +from clarity.utils.source_separation_support import get_device, separate_sources + +BASE_DIR = Path.cwd() +RESOURCES = BASE_DIR / "tests" / "resources" / "utils" + + +def test_separate_sources(): + """Test that the separate_sources function returns the expected output""" + np.random.seed(123456789) + + # Create a dummy model + class DummyModel(torch.nn.Module): # pylint: disable=too-few-public-methods + """Dummy source separation model""" + + def __init__(self, sources): + """dummy init""" + super().__init__() + self.sources = sources + + def forward(self, x): + """dummy forward""" + return torch.Tensor( + np.random.uniform(size=(x.shape[0], len(self.sources), *x.shape[1:])) + ) + + # Set up some dummy input data + batch_size = 1 + num_channels = 1 + length = 1 + sample_rate = 16000 + sources = ["vocals", "drums", "bass", "other"] + mix = np.random.randn(batch_size, num_channels, length * sample_rate) + device = torch.device("cpu") + + # Create a dummy model + model = DummyModel(sources) + + # Call separate_sources + output = separate_sources(model, mix, sample_rate, device=device) + + expected_results = np.load( + RESOURCES / "test_esource_separation_support.test_separate_sources.npy", + allow_pickle=True, + ) + # Check that the output has the correct shape + assert output.shape == expected_results.shape + np.testing.assert_array_almost_equal(output, expected_results) + + +def test_get_device(): + """Test the correct device selection given the inputs""" + # Test default case (no argument passed) + device, device_type = get_device(None) + assert ( + device == torch.device("cuda") + if torch.cuda.is_available() + else torch.device("cpu") + ) + assert device_type == "cuda" if torch.cuda.is_available() else "cpu" From f8b53faf5cab8c2470806bf879b154dd7748c073 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 18:49:52 +0100 Subject: [PATCH 33/85] test for source separation to utils Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/evaluate.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index eae37963f..ed2c52255 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -370,7 +370,7 @@ def run_calculate_aq(config: DictConfig) -> None: listener_id=listener.id, left_score=left_score, right_score=right_score, - score=np.mean([left_score, right_score])[0], + score=float(np.mean([left_score, right_score])), ) logger.info("Done!") From 29defd1a32d103ac087a0ad923a9fe1caa46863d Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 19:06:44 +0100 Subject: [PATCH 34/85] add missing annotations Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/evaluate.py | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index ed2c52255..8da4b56ff 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -207,8 +207,17 @@ def remix_stems(stems: dict, reference_signal, sample_rate: float) -> ndarray: return level_normalisation(remix_signal, reference_signal, sample_rate) -def make_scene_listener_list(scenes_listeners, small_test=False): - """Make the list of scene-listener pairing to process""" +def make_scene_listener_list(scenes_listeners: dict, small_test: bool = False) -> list: + """Make the list of scene-listener pairing to process + + Args: + scenes_listeners (dict): Dictionary of scenes and listeners. + small_test (bool): Whether to use a small test set. + + Returns: + list: List of scene-listener pairings. + + """ scene_listener_pairs = [ (scene, listener) for scene in scenes_listeners From 46ef9e9e0d578bf4a07229b9d2a5197b48ac0f24 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 19:39:22 +0100 Subject: [PATCH 35/85] fix name of resource Signed-off-by: Gerardo Roa Dabike --- ...eparation_support.test_separate_sources.npy | Bin 0 -> 256128 bytes tests/utils/test_source_separation_support.py | 2 +- 2 files changed, 1 insertion(+), 1 deletion(-) create mode 100644 tests/resources/utils/test_source_separation_support.test_separate_sources.npy diff --git a/tests/resources/utils/test_source_separation_support.test_separate_sources.npy b/tests/resources/utils/test_source_separation_support.test_separate_sources.npy new file mode 100644 index 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z^T%UDzD=Rx#0+>WMukD~^&a8~b?z}!Y>Ni>xWX!gP9?5w&X zJw4sTj@g^i#LEqm{PlJ$b)}^wYRG$uX5Sw4W$6c&SZ~H+h45PCtV0Ut`qSM&WqR^h zg`TxtVv`3&*!;aeX>560D0?w9lHHx2!}ccUu=lB#*nt9lw#TuQsoV%+*Zd2{t{6C$ zt$VV8O-vanac`+({^KUI*e4StUaeVd+P_jsVtodSEFQ{6WD>jBJC?a<_)0we@>mVo zu&2$>C0Q=Y?8M4$taz)c&BVY*k~$q*cKOe3N&KitR$f>u`H&RK#-(;+{j3(T45y2d z0qKWq0we!Qw2Bz3dT!3<-N=_Xmp`!nzRyH*d&UyU8dqDJ%JWH*k&9y`>icpf;Xj8- oZUq$B{8SB>I6s{wSu349w)bMPDf(AGwr%$>>j+hS8!7SkKTxtYt^fc4 literal 0 HcmV?d00001 diff --git a/tests/utils/test_source_separation_support.py b/tests/utils/test_source_separation_support.py index 3f56514c6..0916afbaf 100644 --- a/tests/utils/test_source_separation_support.py +++ b/tests/utils/test_source_separation_support.py @@ -46,7 +46,7 @@ def forward(self, x): output = separate_sources(model, mix, sample_rate, device=device) expected_results = np.load( - RESOURCES / "test_esource_separation_support.test_separate_sources.npy", + RESOURCES / "test_source_separation_support.test_separate_sources.npy", allow_pickle=True, ) # Check that the output has the correct shape From 4f919520c7dd826331a45eed6dab4694e6028b02 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 19:39:31 +0100 Subject: [PATCH 36/85] test evaluate Signed-off-by: Gerardo Roa Dabike --- .../cad_icassp_2024/baseline/test_evaluate.py | 172 ++++++++++++++++++ 1 file changed, 172 insertions(+) create mode 100644 tests/recipes/cad_icassp_2024/baseline/test_evaluate.py diff --git a/tests/recipes/cad_icassp_2024/baseline/test_evaluate.py b/tests/recipes/cad_icassp_2024/baseline/test_evaluate.py new file mode 100644 index 000000000..a1e490149 --- /dev/null +++ b/tests/recipes/cad_icassp_2024/baseline/test_evaluate.py @@ -0,0 +1,172 @@ +"""Tests for the enhance module""" +# pylint:: disable=import-error +from pathlib import Path + +import numpy as np +import pyloudnorm as pyln +import pytest +from scipy.io import wavfile + +from clarity.enhancer.compressor import Compressor +from clarity.enhancer.nalr import NALR +from clarity.utils.audiogram import Audiogram +from recipes.cad_icassp_2024.baseline.evaluate import ( + apply_gains, + apply_ha, + level_normalisation, + load_reference_stems, + make_scene_listener_list, + remix_stems, + set_song_seed, +) + + +@pytest.mark.parametrize( + "apply_compressor,expected_result", + [(True, 5130.70234905519), (False, 11039.797138690315)], +) +def test_apply_ha(apply_compressor, expected_result): + """Test apply_ha""" + np.random.seed(2024) + + sample_rate = 44100 + duration = 0.5 + + signal = np.random.rand(int(sample_rate * duration)) + + audiogram = Audiogram( + levels=np.ones(9), + frequencies=np.array([250, 500, 1000, 2000, 4000, 6000, 8000, 9000, 10000]), + ) + enhancer = NALR(nfir=220, sample_rate=16000) + compressor = Compressor( + threshold=0.35, attenuation=0.1, attack=50, release=1000, rms_buffer_size=0.064 + ) + + output = apply_ha(enhancer, compressor, signal, audiogram, apply_compressor) + + assert np.sum(output) == pytest.approx(expected_result) + + +@pytest.mark.parametrize( + "gains,expected_result", + [ + ({"vocals": 0, "bass": 0, "drums": 0, "other": 0}, 88207.89862265925), + ({"vocals": 10, "bass": 0, "drums": 0, "other": 0}, 135801.06478181464), + ({"vocals": 0, "bass": 10, "drums": 0, "other": 0}, 135716.2197962051), + ({"vocals": 0, "bass": 0, "drums": 10, "other": 0}, 136040.5632722622), + ({"vocals": 0, "bass": 0, "drums": 0, "other": 10}, 136003.7152825283), + ({"vocals": 6, "bass": 0, "drums": 0, "other": 0}, 110114.28261802963), + ({"vocals": 3, "bass": 0, "drums": 0, "other": 0}, 97288.123734263), + ({"vocals": -3, "bass": 0, "drums": 0, "other": 0}, 81779.59153364039), + ({"vocals": -6, "bass": 0, "drums": 0, "other": 0}, 77228.6986292428), + ({"vocals": -10, "bass": 0, "drums": 0, "other": 0}, 73157.61801048138), + ], +) +def test_apply_gains(tmp_path, gains, expected_result): + """Test apply_gains + It test the 4 different gains for the 4 different stems + """ + np.random.seed(2024) + + sample_rate = 44100 + duration = 0.5 + + for stem in ["vocals", "drums", "bass", "other", "mixture"]: + filename = Path(tmp_path) / f"{stem}.wav" + signal = np.random.uniform(size=(int(sample_rate * duration), 2)) + wavfile.write(filename, sample_rate, signal) + + stems, _ = load_reference_stems(tmp_path) + output = apply_gains(stems, sample_rate, gains) + + result = 0 + for _, stem_signal in output.items(): + result += np.sum(stem_signal) + + assert result == pytest.approx(expected_result) + + +def test_level_normalisation(): + """Test level_normalisation""" + np.random.seed(2024) + + sample_rate = 44100 + duration = 0.5 + + reference_signal = np.random.rand(int(sample_rate * duration)) + signal = np.random.rand(int(sample_rate * duration)) * 2 + + meter = pyln.Meter(int(sample_rate)) + + normed_signal = level_normalisation(signal, reference_signal, sample_rate) + + assert np.sum(normed_signal) == pytest.approx(10899.6694813693) + + normed_signal_lufs = meter.integrated_loudness(normed_signal) + reference_signal_lufs = meter.integrated_loudness(reference_signal) + assert normed_signal_lufs == pytest.approx(reference_signal_lufs) + + +def test_remix_stems(tmp_path): + """Test remix_stems""" + np.random.seed(2024) + + sample_rate = 44100 + duration = 0.5 + + for stem in ["vocals", "drums", "bass", "other", "mixture"]: + filename = Path(tmp_path) / f"{stem}.wav" + signal = np.random.rand(int(sample_rate * duration)) + wavfile.write(filename, sample_rate, signal) + + stems, mixture = load_reference_stems(tmp_path) + remix = remix_stems(stems, mixture, sample_rate) + assert np.sum(remix) == pytest.approx(21950.335598725396) + + +def test_make_scene_listener_list(): + """Test make_scene_listener_list""" + song_list = { + "my favorite song": ["list1", "list2"], + "another song": ["list3", "list4"], + } + expected_output = [ + ("my favorite song", "list1"), + ("my favorite song", "list2"), + ("another song", "list3"), + ("another song", "list4"), + ] + assert make_scene_listener_list(song_list) == pytest.approx(expected_output) + + +@pytest.mark.parametrize( + "song,expected_result", + [("my favorite song", 83), ("another song", 3)], +) +def test_set_song_seed(song, expected_result): + """Thest the function set_song_seed using 2 different inputs""" + # Set seed for the same song + set_song_seed(song) + assert np.random.randint(100) == pytest.approx(expected_result) + + +def test_load_reference_stems(tmp_path): + """Test load_reference_stems""" + np.random.seed(2024) + + sample_rate = 44100 + duration = 0.5 + + for stem in ["vocals", "drums", "bass", "other", "mixture"]: + filename = Path(tmp_path) / f"{stem}.wav" + signal = np.random.rand(int(sample_rate * duration)) + wavfile.write(filename, sample_rate, signal) + + stems, mixture = load_reference_stems(tmp_path) + assert len(stems) == 4 + assert np.sum(stems["vocals"]) == pytest.approx(11040.05074128) + assert np.sum(stems["drums"]) == pytest.approx(10970.61284548) + assert np.sum(stems["bass"]) == pytest.approx(11062.77053343) + assert np.sum(stems["other"]) == pytest.approx(11058.65518849) + assert np.sum(mixture) == pytest.approx(11046.02394025) From 4b4a3397a1e750c3a2b68eae85a3edca2e2cbeee Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 20:16:15 +0100 Subject: [PATCH 37/85] Class ResultFile is very similar in all recipies. Change it to DataClass with variable colums Signed-off-by: Gerardo Roa Dabike --- clarity/utils/results_support.py | 63 +++++++++++ recipes/cad_icassp_2024/baseline/evaluate.py | 111 +++++-------------- tests/utils/test_results_support.py | 50 +++++++++ 3 files changed, 141 insertions(+), 83 deletions(-) create mode 100644 clarity/utils/results_support.py create mode 100644 tests/utils/test_results_support.py diff --git a/clarity/utils/results_support.py b/clarity/utils/results_support.py new file mode 100644 index 000000000..e77ffe7fa --- /dev/null +++ b/clarity/utils/results_support.py @@ -0,0 +1,63 @@ +"""Dataclass to save challenges results to a CSV file.""" +from __future__ import annotations + +# pylint: disable=import-error +import csv +from dataclasses import dataclass +from pathlib import Path + + +@dataclass +class ResultsFile: + """A utility class for writing results to a CSV file. + + Attributes: + file_name (str | Path): The name of the file to write results to. + header_columns (list[str]): The columns to write to the CSV file. + append_results (bool): Whether to append results to an existing file. + If False, a new file will be created and the header row will be written. + Defaults to False. + """ + + file_name: str | Path + header_columns: list[str] + append_results: bool = False + + def __post_init__(self): + """Write the header row to the CSV file.""" + if isinstance(self.file_name, str): + self.file_name = Path(self.file_name) + + if self.append_results: + if not Path(self.file_name).exists(): + raise FileNotFoundError( + "Cannot append results to non-existent file " + f"{self.file_name.as_posix()}" + " - please set append_results=False" + ) + else: + with open(self.file_name, "w", encoding="utf-8", newline="") as csv_file: + csv_writer = csv.writer( + csv_file, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL + ) + csv_writer.writerow(self.header_columns) + + def add_result( + self, + row_values: dict[str, str | float], + ): + """Add a result to the CSV file. + + Args: + row_values (dict[str, str | float]): The values to write to the CSV file. + """ + + with open(self.file_name, "a", encoding="utf-8", newline="") as csv_file: + csv_writer = csv.writer( + csv_file, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL + ) + row = [] + for column in self.header_columns: + row.append(row_values[column]) + + csv_writer.writerow(row) diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index 8da4b56ff..61aef84fc 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -2,7 +2,6 @@ from __future__ import annotations # pylint: disable=import-error -import csv import hashlib import json import logging @@ -21,80 +20,12 @@ from clarity.utils.audiogram import Audiogram, Listener from clarity.utils.file_io import read_signal from clarity.utils.flac_encoder import read_flac_signal +from clarity.utils.results_support import ResultsFile from clarity.utils.signal_processing import compute_rms logger = logging.getLogger(__name__) -class ResultsFile: - """A utility class for writing results to a CSV file. - - Attributes: - file_name (str): The name of the file to write results to. - """ - - def __init__(self, file_name: str): - """Initialize the ResultsFile instance. - - Args: - file_name (str): The name of the file to write results to. - """ - self.file_name = file_name - - def write_header(self): - """Write the header row to the CSV file.""" - with open(self.file_name, "w", encoding="utf-8", newline="") as csv_file: - csv_writer = csv.writer( - csv_file, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL - ) - csv_writer.writerow( - [ - "scene", - "song", - "listener", - "left_score", - "right_score", - "score", - ] - ) - - def add_result( - self, - scene: str, - song: str, - listener_id: str, - left_score: float, - right_score: float, - score: float, - ): - """Add a result to the CSV file. - - Args: - scene (str): The name of the scene that the result is for. - song (str): The name of the song that the result is for. - listener_id (str): The name of the listener who submitted the result. - left_score (float): The score for the left channel. - right_score (float): The score for the right channel. - score (float): The combined score. - """ - logger.info(f"The combined score is {score}") - - with open(self.file_name, "a", encoding="utf-8", newline="") as csv_file: - csv_writer = csv.writer( - csv_file, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL - ) - csv_writer.writerow( - [ - scene, - song, - listener_id, - str(left_score), - str(right_score), - str(score), - ] - ) - - def apply_ha( enhancer: NALR, compressor: Compressor | None, @@ -280,13 +211,25 @@ def run_calculate_aq(config: DictConfig) -> None: enhancer = NALR(**config.nalr) + scores_headers = [ + "scene", + "song", + "listener", + "left_score", + "right_score", + "score", + ] if config.evaluate.batch_size == 1: - results_file = ResultsFile("scores.csv") + results_file = ResultsFile( + "scores.csv", + header_columns=scores_headers, + ) else: results_file = ResultsFile( - f"scores_{config.evaluate.batch + 1}-{config.evaluate.batch_size}.csv" + f"scores_{config.evaluate.batch + 1}-{config.evaluate.batch_size}.csv", + header_columns=scores_headers, ) - results_file.write_header() + # results_file.write_header() scene_listener_pairs = make_scene_listener_list( scenes_listeners, config.evaluate.small_test @@ -345,8 +288,8 @@ def run_calculate_aq(config: DictConfig) -> None: apply_compressor=False, ) left_score = compute_haaqi( - processed_signal=enhanced_signal[:, 0], - reference_signal=left_reference, + processed_signal=enhanced_signal[:44100, 0], + reference_signal=left_reference[:44100], processed_sample_rate=config.remix_sample_rate, reference_sample_rate=config.sample_rate, audiogram=listener.audiogram_left, @@ -363,8 +306,8 @@ def run_calculate_aq(config: DictConfig) -> None: apply_compressor=False, ) right_score = compute_haaqi( - processed_signal=enhanced_signal[:, 1], - reference_signal=right_reference, + processed_signal=enhanced_signal[:44100, 1], + reference_signal=right_reference[:44100], processed_sample_rate=config.remix_sample_rate, reference_sample_rate=config.sample_rate, audiogram=listener.audiogram_right, @@ -374,12 +317,14 @@ def run_calculate_aq(config: DictConfig) -> None: # Save scores results_file.add_result( - scene=scene_id, - song=song_name, - listener_id=listener.id, - left_score=left_score, - right_score=right_score, - score=float(np.mean([left_score, right_score])), + { + "scene": scene_id, + "song": song_name, + "listener": listener.id, + "left_score": left_score, + "right_score": right_score, + "score": float(np.mean([left_score, right_score])), + } ) logger.info("Done!") diff --git a/tests/utils/test_results_support.py b/tests/utils/test_results_support.py new file mode 100644 index 000000000..6722bd9b5 --- /dev/null +++ b/tests/utils/test_results_support.py @@ -0,0 +1,50 @@ +"""test for results support module""" +# pylint: disable=import-error +from pathlib import Path + +import pytest + +from clarity.utils.results_support import ResultsFile + +# Define some sample data for testing +sample_header = ["Name", "Score"] +sample_data = [{"Name": "Alice", "Score": 95}, {"Name": "Bob", "Score": 88}] + + +@pytest.fixture(name="results_file") +def fixture_results_file(tmpdir): + # Create a temporary directory and a temporary CSV file for testing + file_name = Path(tmpdir, "test_results.csv") + return ResultsFile(file_name, sample_header) + + +def test_add_result(results_file): + # Test adding a result to the CSV file + results_file.add_result({"Name": "Charlie", "Score": 75}) + + # Read the CSV file and check if the added data is present + with open(results_file.file_name, encoding="utf-8") as csv_file: + lines = csv_file.readlines() + assert len(lines) == 2 # There should be 2 lines (header + 1 data row) + assert "Charlie,75\n" in lines # Check if the added data is present + + +def test_header_written(results_file): + # Test if the header row is written when the ResultsFile is created + with open(results_file.file_name, encoding="utf-8") as csv_file: + lines = csv_file.readlines() + assert len(lines) == 1 # There should be 1 line (only header) + assert lines[0].strip() == "Name,Score" # Check the header content + + +def test_missing_column(results_file): + # Test adding a result with a missing column + with pytest.raises(KeyError): + results_file.add_result({"Name": "Eve"}) + + +def test_nonexistent_file(tmp_path): + # Test creating a ResultsFile with a non-existent file + file_name = Path(tmp_path) / "nonexistent.csv" + with pytest.raises(FileNotFoundError): + ResultsFile(file_name, sample_header, append_results=True) From 8fd0d29efa29d32be481227a84902a2c50a0944c Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 21:06:10 +0100 Subject: [PATCH 38/85] test for generates at mic dataset Signed-off-by: Gerardo Roa Dabike --- .../generates_at_mic_musdb18.py | 5 + .../test_generates_at_mic_musdb18.py | 166 ++++++++++++++++++ 2 files changed, 171 insertions(+) create mode 100644 tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py diff --git a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py index 4cbc488e9..1b04c15d4 100644 --- a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py +++ b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py @@ -115,6 +115,11 @@ def find_precreated_samples(source_dir: str | Path) -> list[str]: if isinstance(source_dir, str): source_dir = Path(source_dir) + if not source_dir.exists(): + raise FileNotFoundError( + f"Source directory does not exist: {source_dir.as_posix()}" + ) + return [f.name for f in source_dir.glob("*/*")] diff --git a/tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py b/tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py new file mode 100644 index 000000000..38a664587 --- /dev/null +++ b/tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py @@ -0,0 +1,166 @@ +"""Test the generate dataset script for the ICASSP 2024 CAD recipe.""" +# pylint:: disable=import-error +from pathlib import Path + +import numpy as np +import pytest +from scipy.io import wavfile +from scipy.signal import lfilter + +from recipes.cad_icassp_2024.generate_dataset.generates_at_mic_musdb18 import ( + apply_hrtf, + find_precreated_samples, + load_hrtf_signals, + normalise_lufs_level, +) + +# Create a mock object for the pyln.Meter class + + +@pytest.fixture(name="temp_dir_with_samples") +def fixture_temp_dir_with_samples(tmp_path): + source_dir = Path(tmp_path) + sample_dirs = ["sample_dir1", "sample_dir2"] + for sample_dir in sample_dirs: + sample_dir_path = Path(source_dir) / "train" / sample_dir + sample_dir_path.mkdir(exist_ok=True, parents=True) + sample_files = ["sample1.wav", "sample2.wav"] + for sample_file in sample_files: + with open(sample_dir_path / sample_file, "w", encoding="utf-8") as f: + f.write("Sample content") + return source_dir + + +def test_apply_hrtf_valid_signal(): + # Test the function with a valid signal and HRTF + signal = np.array([[1, 2], [3, 4], [5, 6]], dtype=np.float64) + hrtf_left = np.array([[0.5, 0.3], [0.2, 0.1]], dtype=np.float64) + hrtf_right = np.array([[0.2, 0.1], [0.5, 0.3]], dtype=np.float64) + + result = apply_hrtf(signal, hrtf_left, hrtf_right) + + # Verify the result for each channel + expected_left_ear = lfilter(hrtf_left[:, 0], 1, signal[:, 0]) + lfilter( + hrtf_right[:, 0], 1, signal[:, 1] + ) + expected_right_ear = lfilter(hrtf_left[:, 1], 1, signal[:, 0]) + lfilter( + hrtf_right[:, 1], 1, signal[:, 1] + ) + + expected_result = np.stack([expected_left_ear, expected_right_ear], axis=1) + + np.testing.assert_allclose(result, expected_result, rtol=1e-3, atol=1e-6) + + +def test_apply_hrtf_zero_signal(): + # Test the function with a zero signal and HRTF + signal = np.zeros((3, 2), dtype=np.float64) + hrtf_left = np.array([[0.5, 0.3], [0.2, 0.1]], dtype=np.float64) + hrtf_right = np.array([[0.2, 0.1], [0.5, 0.3]], dtype=np.float64) + + result = apply_hrtf(signal, hrtf_left, hrtf_right) + + # The result should also be all zeros + expected_result = np.zeros((3, 2), dtype=np.float64) + + np.testing.assert_allclose(result, expected_result, rtol=1e-3, atol=1e-6) + + +def test_load_hrtf_signals(tmp_path): + # Create temporary files for testing + np.random.seed(2024) + hrtf_path = Path(tmp_path) / "hrtf_directory" + hrtf_path.mkdir(exist_ok=True, parents=True) + + hp = { + "mic": "mic_name", + "subject": "subject_name", + "left_angle": -30, + "right_angle": 45, + } + + left_file = hrtf_path / f"{hp['mic']}-{hp['subject']}-n{abs(hp['left_angle'])}.wav" + right_file = ( + hrtf_path / f"{hp['mic']}-{hp['subject']}-p{abs(hp['right_angle'])}.wav" + ) + + left_signal = np.random.rand(44100) + right_signal = np.random.rand(44100) + + wavfile.write(left_file, 44100, left_signal) + wavfile.write(right_file, 44100, right_signal) + + # Call the function + left_result, right_result = load_hrtf_signals(str(hrtf_path), hp) + + # Verify that the function returns the expected signals + assert np.sum(left_result) == pytest.approx(np.sum(left_signal)) + assert np.sum(right_result) == pytest.approx(np.sum(right_signal)) + + +def test_normalise_lufs_level_same_loudness(): + # Test when the signal and reference signal have the same loudness + np.random.seed(2024) + signal = np.random.rand(44100) + sample_rate = 44100.0 + + result = normalise_lufs_level(signal, signal, sample_rate) + + # Since the loudness is the same, the result should be the same as the input signal + assert np.sum(result) == pytest.approx(np.sum(signal)) + + +def test_normalise_lufs_level_reference_quieter(): + # Test when the reference signal is quieter than the signal + np.random.seed(2024) + signal = np.random.rand(44100) + reference_signal = np.random.rand(44100) / 0.2 + sample_rate = 44100.0 + + result = normalise_lufs_level(signal, reference_signal, sample_rate) + + # The result should be a normalized version of the signal so + # that it matches the reference loudness + expected_result = 109580.6307104611 + assert np.sum(result) == pytest.approx(expected_result) + + +def test_normalise_lufs_level_reference_louder(): + # Test when the reference signal is louder than the signal + np.random.seed(2024) + signal = np.random.rand(44100) + reference_signal = np.random.rand(44100) * 0.2 + sample_rate = 44100.0 + + result = normalise_lufs_level(signal, reference_signal, sample_rate) + + # The result should be a normalized version of the signal so + # that it matches the reference loudness + expected_result = 4383.225228418446 + assert np.sum(result) == pytest.approx(expected_result) + + +def test_find_precreated_samples(temp_dir_with_samples): + # Get the list of precreated samples from the temporary directory + source_dir = temp_dir_with_samples + precreated_samples = find_precreated_samples(source_dir) + + # Check if the expected sample files are in the result + assert "sample_dir1" in precreated_samples + assert "sample_dir1" in precreated_samples + + +def test_find_precreated_samples_empty_directory(tmp_path): + # Test when the source directory is empty + source_dir = Path(tmp_path) + precreated_samples = find_precreated_samples(source_dir) + + # The result should be an empty list + assert precreated_samples == [] + + +def test_find_precreated_samples_nonexistent_directory(): + # Test when the source directory does not exist + source_dir = "nonexistent_directory" + with pytest.raises(FileNotFoundError): + find_precreated_samples(source_dir) From 5c578426bf292ffd0a4cbc30b639914d799dc8cc Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 12 Sep 2023 21:19:15 +0100 Subject: [PATCH 39/85] test for generates at mic dataset Signed-off-by: Gerardo Roa Dabike --- .../generate_dataset/generates_at_mic_musdb18.py | 4 +--- .../generate_dataset/test_generates_at_mic_musdb18.py | 7 ------- 2 files changed, 1 insertion(+), 10 deletions(-) diff --git a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py index 1b04c15d4..381f049da 100644 --- a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py +++ b/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py @@ -116,9 +116,7 @@ def find_precreated_samples(source_dir: str | Path) -> list[str]: source_dir = Path(source_dir) if not source_dir.exists(): - raise FileNotFoundError( - f"Source directory does not exist: {source_dir.as_posix()}" - ) + return [] return [f.name for f in source_dir.glob("*/*")] diff --git a/tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py b/tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py index 38a664587..bf9147f1f 100644 --- a/tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py +++ b/tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py @@ -157,10 +157,3 @@ def test_find_precreated_samples_empty_directory(tmp_path): # The result should be an empty list assert precreated_samples == [] - - -def test_find_precreated_samples_nonexistent_directory(): - # Test when the source directory does not exist - source_dir = "nonexistent_directory" - with pytest.raises(FileNotFoundError): - find_precreated_samples(source_dir) From 1af34c930878f6bcf31a3f6d8d50e2fe43c75e09 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 10:50:32 +0100 Subject: [PATCH 40/85] add generate train scenes Signed-off-by: Gerardo Roa Dabike --- .../generate_dataset/config.yaml | 10 +- .../generate_dataset/generate_train_scenes.py | 116 ++++++++++++++++++ 2 files changed, 125 insertions(+), 1 deletion(-) create mode 100644 recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py diff --git a/recipes/cad_icassp_2024/generate_dataset/config.yaml b/recipes/cad_icassp_2024/generate_dataset/config.yaml index 0e1f04ff0..947715efa 100644 --- a/recipes/cad_icassp_2024/generate_dataset/config.yaml +++ b/recipes/cad_icassp_2024/generate_dataset/config.yaml @@ -5,12 +5,20 @@ path: hrtf_dir: ${path.root}/audio/hrtf scene_file: ${path.metadata_dir}/scenes.train.json music_file: ${path.metadata_dir}/musdb18.train.json - head_positions_file: ${path.metadata_dir}/head_positions.json + head_loudspeaker_positions_file: ${path.metadata_dir}/head_loudspeaker_positions.json + tracklist_file: ./musdb18_tracklist.csv + gains_file: ${path.metadata_dir}/gains.json output_music_dir: ${path.root}/audio/at_mic_music # at microphone musdb18 dataset output_music_file: ${path.metadata_dir}/at_mic_music.train.json sample_rate: 44100 +scene: + number_scenes_per_song: 4 + +scene_listener: + number_listeners_per_scene: 2 + hydra: run: dir: . diff --git a/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py b/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py new file mode 100644 index 000000000..33dac1618 --- /dev/null +++ b/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py @@ -0,0 +1,116 @@ +"""Module to generate the scenes and scene-listeners metadata files for training""" +from __future__ import annotations + +# pylint: disable=import-error +import json +from pathlib import Path + +import hydra +import numpy as np +from omegaconf import DictConfig + +from recipes.cad_icassp_2024.baseline.evaluate import set_song_seed + + +def choose_samples(source: list, size: int) -> list: + """Choose a number of samples from a list + Args: + source: List of samples to choose from + size: Number of samples to choose + Returns: + List of chosen samples + """ + if len(source) == 0: + return [] + if len(source) <= size: + return source + return np.random.choice(source, size) + + +def generate_scenes(cfg: DictConfig) -> None: + """ + Generate the scenes metadata file for training + Args: + cfg: Hydra config + """ + + with open(cfg.path.gains_file, encoding="utf-8") as f: + gains = list(json.load(f).keys()) + + with open(cfg.path.head_loudspeaker_positions_file, encoding="utf-8") as f: + head_loudspeaker_positions = list(json.load(f).keys()) + + scenes_metadata = {} + scene_id = 10001 + + music_path = Path(cfg.path.metadata_dir) / "musdb18.train.json" + with open(music_path, encoding="utf-8") as f: + tracks_list = [item["Track Name"] for item in json.load(f)] + + for track_name in tracks_list: + set_song_seed(track_name) + + gains_to_choose = gains.copy() + hlp_to_choose = head_loudspeaker_positions.copy() + + for _ in range(cfg.scene.number_scenes_per_song): + g = choose_samples(gains_to_choose, 1)[0] + hlp = choose_samples(hlp_to_choose, 1)[0] + + # remove the chosen gain and head loudspeaker position from the list + # so we choose a different one next time + gains_to_choose.remove(g) + hlp_to_choose.remove(hlp) + + scenes_metadata[f"scene_{scene_id:04d}"] = { + "music": track_name, + "gain": g, + "head_loudspeaker_positions": hlp, + } + scene_id += 1 + + output_file = Path(cfg.path.metadata_dir) / "scenes.train.json" + output_file.parent.mkdir(parents=True, exist_ok=True) + with open(output_file, "w", encoding="utf-8") as f: + json.dump(scenes_metadata, f, indent=4) + + +def generate_scene_listener(cfg: DictConfig) -> None: + """Generates the scene-listeners metadata file for training + + Args: + cfg: Hydra config + """ + scenes_path = Path(cfg.path.metadata_dir) / "scenes.train.json" + with open(scenes_path, encoding="utf-8") as f: + scenes = list(json.load(f).keys()) + + listeners_path = Path(cfg.path.metadata_dir) / "listeners.train.json" + with open(listeners_path, encoding="utf-8") as f: + listeners = list(json.load(f).keys()) + + scene_listeners = {} + + set_song_seed("icassp2024") + + for scene in scenes: + scene_listeners[scene] = list( + choose_samples(listeners, cfg.scene_listener.number_listeners_per_scene) + ) + + output_file = Path(cfg.path.metadata_dir) / "scene_listeners.train.json" + output_file.parent.mkdir(parents=True, exist_ok=True) + with open(output_file, "w", encoding="utf-8") as f: + json.dump(scene_listeners, f, indent=4) + + +@hydra.main(config_path="", config_name="config") +def run(cfg: DictConfig) -> None: + """Module generates the scenes and scene-listeners metadata files for training.""" + generate_scenes(cfg) + generate_scene_listener(cfg) + + +# pylint: disable = no-value-for-parameter +if __name__ == "__main__": + run() From 6bf5aa96405e6b3f6c0499b5e0202c84b069fb44 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 10:50:58 +0100 Subject: [PATCH 41/85] rename generate train data Signed-off-by: Gerardo Roa Dabike --- .../{generates_at_mic_musdb18.py => generate_at_mic_musdb18.py} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename recipes/cad_icassp_2024/generate_dataset/{generates_at_mic_musdb18.py => generate_at_mic_musdb18.py} (100%) diff --git a/recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py b/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py similarity index 100% rename from recipes/cad_icassp_2024/generate_dataset/generates_at_mic_musdb18.py rename to recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py From 1acbe7b5da9be48221e4fc8f9ae2ec37023a9cc7 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 10:52:29 +0100 Subject: [PATCH 42/85] teats for generates modules Signed-off-by: Gerardo Roa Dabike --- ...b18.py => test_generate_at_mic_musdb18.py} | 2 +- .../test_generate_train_scenes.py | 155 ++++++++++++++++++ 2 files changed, 156 insertions(+), 1 deletion(-) rename tests/recipes/cad_icassp_2024/generate_dataset/{test_generates_at_mic_musdb18.py => test_generate_at_mic_musdb18.py} (98%) create mode 100644 tests/recipes/cad_icassp_2024/generate_dataset/test_generate_train_scenes.py diff --git a/tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py b/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_at_mic_musdb18.py similarity index 98% rename from tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py rename to tests/recipes/cad_icassp_2024/generate_dataset/test_generate_at_mic_musdb18.py index bf9147f1f..b898b5bab 100644 --- a/tests/recipes/cad_icassp_2024/generate_dataset/test_generates_at_mic_musdb18.py +++ b/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_at_mic_musdb18.py @@ -7,7 +7,7 @@ from scipy.io import wavfile from scipy.signal import lfilter -from recipes.cad_icassp_2024.generate_dataset.generates_at_mic_musdb18 import ( +from recipes.cad_icassp_2024.generate_dataset.generate_at_mic_musdb18 import ( apply_hrtf, find_precreated_samples, load_hrtf_signals, diff --git a/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_train_scenes.py b/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_train_scenes.py new file mode 100644 index 000000000..41a778db8 --- /dev/null +++ b/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_train_scenes.py @@ -0,0 +1,155 @@ +"""Test the generate scenes script for the ICASSP 2024 CAD recipe.""" +# pylint:: disable=import-error +import json + +from omegaconf import DictConfig + +from recipes.cad_icassp_2024.generate_dataset.generate_train_scenes import ( + choose_samples, + generate_scene_listener, + generate_scenes, +) + + +def test_choose_samples(): + # Test with a source list containing integers + source = [1, 2, 3, 4, 5] + number = 3 + samples = choose_samples(source, number) + + # Check if the number of samples returned is equal to the specified number + assert len(samples) == number + + # Check if all samples are in the source list + assert all(sample in source for sample in samples) + + # Test with an empty source list + source = [] + number = 3 + samples = choose_samples(source, number) + + # Check if an empty list is returned when the source list is empty + assert len(samples) == 0 + + # Test with a source list containing a single element + source = [42] + number = 3 + samples = choose_samples(source, number) + + # Check if the returned list contains the single element + assert len(samples) == 1 + assert samples[0] == 42 + + +def test_generate_scenes(tmp_path): + # Define a mock configuration dictionary + tmp = tmp_path.as_posix() + cfg = DictConfig( + { + "path": { + "gains_file": f"{tmp}/fake_gains_file.json", + "head_loudspeaker_positions_file": f"{tmp}/fake_positions_file.json", + "metadata_dir": tmp, + }, + "scene": { + "number_scenes_per_song": 2, # Adjust as needed + }, + } + ) + + # Create fake gains and head loudspeaker positions files + gains_data = {"gain1": 1, "gain2": 2, "gain3": 3} + positions_data = {"position1": [1, 2, 3], "position2": [4, 5, 6]} + + with open(tmp_path / cfg.path.gains_file, "w", encoding="utf-8") as gains_file: + json.dump(gains_data, gains_file) + + with open( + tmp_path / cfg.path.head_loudspeaker_positions_file, "w", encoding="utf-8" + ) as positions_file: + json.dump(positions_data, positions_file) + + # Create a fake music metadata file + music_data = [{"Track Name": "track1"}, {"Track Name": "track2"}] + + music_path = tmp_path / "musdb18.train.json" + music_path.parent.mkdir(exist_ok=True, parents=True) + with open(music_path, "w", encoding="utf-8") as music_file: + json.dump(music_data, music_file) + + # Run the function + generate_scenes(cfg) + + # Verify the results + scenes_file = tmp_path / "scenes.train.json" + assert scenes_file.exists() + + with open(scenes_file, encoding="utf-8") as scenes_file: + scenes_data = json.load(scenes_file) + + # Check if the number of scenes is correct + assert len(scenes_data) == 4 + + # Check if the scenes are correctly generated + assert scenes_data["scene_10001"]["music"] == "track1" + assert scenes_data["scene_10001"]["gain"] == "gain1" + assert scenes_data["scene_10001"]["head_loudspeaker_positions"] == "position1" + assert scenes_data["scene_10002"]["music"] == "track1" + assert scenes_data["scene_10002"]["gain"] == "gain2" + assert scenes_data["scene_10002"]["head_loudspeaker_positions"] == "position2" + assert scenes_data["scene_10003"]["music"] == "track2" + assert scenes_data["scene_10003"]["gain"] == "gain2" + assert scenes_data["scene_10003"]["head_loudspeaker_positions"] == "position1" + assert scenes_data["scene_10004"]["music"] == "track2" + assert scenes_data["scene_10004"]["gain"] == "gain1" + assert scenes_data["scene_10004"]["head_loudspeaker_positions"] == "position2" + + +def test_generate_scene_listener(tmp_path): + # Define a mock configuration dictionary + cfg = DictConfig( + { + "path": { + "metadata_dir": tmp_path.as_posix(), + }, + "scene_listener": { + "number_listeners_per_scene": 2, # Adjust as needed + }, + } + ) + + # Create a fake scenes metadata file + scenes_data = { + "scene1": {}, + "scene2": {}, + "scene3": {}, + } + scenes_file = tmp_path / "scenes.train.json" + with open(scenes_file, "w", encoding="utf-8") as f: + json.dump(scenes_data, f) + + # Create a fake listeners metadata file + listeners_data = { + "listener1": {}, + "listener2": {}, + "listener3": {}, + } + listeners_file = tmp_path / "listeners.train.json" + with open(listeners_file, "w", encoding="utf-8") as f: + json.dump(listeners_data, f) + + # Run the function + generate_scene_listener(cfg) + + # Verify the results + scene_listeners_file = tmp_path / "scene_listeners.train.json" + assert scene_listeners_file.exists() + + with open(scene_listeners_file, encoding="utf-8") as f: + scene_listeners_data = json.load(f) + + # Check if the number of scene-listeners is correct + assert len(scene_listeners_data) == 3 + assert len(scene_listeners_data["scene1"]) == 2 + assert len(scene_listeners_data["scene2"]) == 2 + assert len(scene_listeners_data["scene3"]) == 2 From a8743c1e4f7ab6480aff0b5c58516756605650ef Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 11:32:44 +0100 Subject: [PATCH 43/85] generates scenes Signed-off-by: Gerardo Roa Dabike --- .../generate_dataset/generate_train_scenes.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py b/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py index 33dac1618..546728a32 100644 --- a/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py +++ b/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py @@ -69,10 +69,10 @@ def generate_scenes(cfg: DictConfig) -> None: } scene_id += 1 - output_file = Path(cfg.path.metadata_dir) / "scenes.train.json" - output_file.parent.mkdir(parents=True, exist_ok=True) - with open(output_file, "w", encoding="utf-8") as f: - json.dump(scenes_metadata, f, indent=4) + output_file = Path(cfg.path.metadata_dir) / "scenes.train.json" + output_file.parent.mkdir(parents=True, exist_ok=True) + with open(output_file, "w", encoding="utf-8") as f: + json.dump(scenes_metadata, f, indent=4) def generate_scene_listener(cfg: DictConfig) -> None: From d457e9027cc5e20d793f88390a3473e83b5cba01 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 15:33:48 +0100 Subject: [PATCH 44/85] soft clip False Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/recipes/cad_icassp_2024/baseline/config.yaml b/recipes/cad_icassp_2024/baseline/config.yaml index 615d4c12c..08ba99c0d 100644 --- a/recipes/cad_icassp_2024/baseline/config.yaml +++ b/recipes/cad_icassp_2024/baseline/config.yaml @@ -25,7 +25,7 @@ compressor: release: 1000 rms_buffer_size: 0.064 -soft_clip: True +soft_clip: False separator: model: demucs # demucs or openunmix From e003325633fc6b058f527de1bf95fad2877aafe1 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 15:46:26 +0100 Subject: [PATCH 45/85] random choice replace = False Signed-off-by: Gerardo Roa Dabike --- .../generate_dataset/generate_train_scenes.py | 2 +- .../generate_dataset/test_generate_train_scenes.py | 14 +++++++------- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py b/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py index 546728a32..2667e287c 100644 --- a/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py +++ b/recipes/cad_icassp_2024/generate_dataset/generate_train_scenes.py @@ -24,7 +24,7 @@ def choose_samples(source: list, size: int) -> list: return [] if len(source) <= size: return source - return np.random.choice(source, size) + return np.random.choice(source, size, replace=False) def generate_scenes(cfg: DictConfig) -> None: diff --git a/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_train_scenes.py b/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_train_scenes.py index 41a778db8..287fe7709 100644 --- a/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_train_scenes.py +++ b/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_train_scenes.py @@ -92,17 +92,17 @@ def test_generate_scenes(tmp_path): # Check if the scenes are correctly generated assert scenes_data["scene_10001"]["music"] == "track1" - assert scenes_data["scene_10001"]["gain"] == "gain1" - assert scenes_data["scene_10001"]["head_loudspeaker_positions"] == "position1" + assert scenes_data["scene_10001"]["gain"] == "gain2" + assert scenes_data["scene_10001"]["head_loudspeaker_positions"] == "position2" assert scenes_data["scene_10002"]["music"] == "track1" - assert scenes_data["scene_10002"]["gain"] == "gain2" - assert scenes_data["scene_10002"]["head_loudspeaker_positions"] == "position2" + assert scenes_data["scene_10002"]["gain"] == "gain1" + assert scenes_data["scene_10002"]["head_loudspeaker_positions"] == "position1" assert scenes_data["scene_10003"]["music"] == "track2" - assert scenes_data["scene_10003"]["gain"] == "gain2" - assert scenes_data["scene_10003"]["head_loudspeaker_positions"] == "position1" + assert scenes_data["scene_10003"]["gain"] == "gain3" + assert scenes_data["scene_10003"]["head_loudspeaker_positions"] == "position2" assert scenes_data["scene_10004"]["music"] == "track2" assert scenes_data["scene_10004"]["gain"] == "gain1" - assert scenes_data["scene_10004"]["head_loudspeaker_positions"] == "position2" + assert scenes_data["scene_10004"]["head_loudspeaker_positions"] == "position1" def test_generate_scene_listener(tmp_path): From c8a80b447a0e73b26df2c14ff8b3eddd6312a0de Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 16:06:31 +0100 Subject: [PATCH 46/85] head_position to head_loudspeaker_position Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/enhance.py | 2 +- recipes/cad_icassp_2024/baseline/evaluate.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/enhance.py b/recipes/cad_icassp_2024/baseline/enhance.py index 9f962fd64..ad29d61b6 100644 --- a/recipes/cad_icassp_2024/baseline/enhance.py +++ b/recipes/cad_icassp_2024/baseline/enhance.py @@ -249,7 +249,7 @@ def enhance(config: DictConfig) -> None: scene_id, listener_id = scene_listener_pair scene = scenes[scene_id] - song_name = f"{scene['music']}-{scene['head_position']}" + song_name = f"{scene['music']}-{scene['head_loudspeaker_position']}" logger.info( f"[{idx:03d}/{num_scenes:03d}] " diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index 61aef84fc..40af8ea88 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -242,7 +242,7 @@ def run_calculate_aq(config: DictConfig) -> None: scene_id, listener_id = scene_listener_pair scene = scenes[scene_id] - song_name = f"{scene['music']}-{scene['head_position']}" + song_name = f"{scene['music']}-{scene['head_loudspeaker_position']}" logger.info( f"[{idx:03d}/{num_scenes:03d}] " From e5e20e66161d6582df6755becfb8cf5fd1a491ca Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 16:09:55 +0100 Subject: [PATCH 47/85] head_position to head_loudspeaker_position Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/enhance.py | 2 +- recipes/cad_icassp_2024/baseline/evaluate.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/enhance.py b/recipes/cad_icassp_2024/baseline/enhance.py index ad29d61b6..7ecf9b073 100644 --- a/recipes/cad_icassp_2024/baseline/enhance.py +++ b/recipes/cad_icassp_2024/baseline/enhance.py @@ -249,7 +249,7 @@ def enhance(config: DictConfig) -> None: scene_id, listener_id = scene_listener_pair scene = scenes[scene_id] - song_name = f"{scene['music']}-{scene['head_loudspeaker_position']}" + song_name = f"{scene['music']}-{scene['head_loudspeaker_positions']}" logger.info( f"[{idx:03d}/{num_scenes:03d}] " diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index 40af8ea88..121baa540 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -242,7 +242,7 @@ def run_calculate_aq(config: DictConfig) -> None: scene_id, listener_id = scene_listener_pair scene = scenes[scene_id] - song_name = f"{scene['music']}-{scene['head_loudspeaker_position']}" + song_name = f"{scene['music']}-{scene['head_loudspeaker_positions']}" logger.info( f"[{idx:03d}/{num_scenes:03d}] " From 95ca9a54931c363ae8eb0b42e9a2fe68c343a6f0 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 16:29:57 +0100 Subject: [PATCH 48/85] default to valid in config Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/config.yaml | 8 ++++---- recipes/cad_icassp_2024/baseline/evaluate.py | 4 ++-- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/config.yaml b/recipes/cad_icassp_2024/baseline/config.yaml index 08ba99c0d..9edb187f3 100644 --- a/recipes/cad_icassp_2024/baseline/config.yaml +++ b/recipes/cad_icassp_2024/baseline/config.yaml @@ -4,10 +4,10 @@ path: music_dir: ${path.root}/audio/at_mic_music gains_file: ${path.metadata_dir}/gains.json head_positions_file: ${path.metadata_dir}/head_positions.json - listeners_file: ${path.metadata_dir}/listeners.train.json - music_file: ${path.metadata_dir}/at_mic_music.train.json - scenes_file: ${path.metadata_dir}/scenes.train.json - scene_listeners_file: ${path.metadata_dir}/scene_listeners.train.json + listeners_file: ${path.metadata_dir}/listeners.valid.json + music_file: ${path.metadata_dir}/at_mic_music.valid.json + scenes_file: ${path.metadata_dir}/scenes.valid.json + scene_listeners_file: ${path.metadata_dir}/scene_listeners.valid.json exp_folder: ./exp # folder to store enhanced signals and final results sample_rate: 44100 diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index 121baa540..097b52912 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -155,9 +155,9 @@ def make_scene_listener_list(scenes_listeners: dict, small_test: bool = False) - for listener in scenes_listeners[scene] ] - # Can define a standard 'small_test' with just 1/50 of the data + # Can define a standard 'small_test' with just 1/15 of the data if small_test: - scene_listener_pairs = scene_listener_pairs[::50] + scene_listener_pairs = scene_listener_pairs[::15] return scene_listener_pairs From 5fbd656eb7b23e6a587d3f75ef3c5b2bc3768d29 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 16:39:22 +0100 Subject: [PATCH 49/85] start processing count from 1 and not 0 Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/enhance.py | 2 +- recipes/cad_icassp_2024/baseline/evaluate.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/enhance.py b/recipes/cad_icassp_2024/baseline/enhance.py index 7ecf9b073..04f878717 100644 --- a/recipes/cad_icassp_2024/baseline/enhance.py +++ b/recipes/cad_icassp_2024/baseline/enhance.py @@ -245,7 +245,7 @@ def enhance(config: DictConfig) -> None: # and process each stem for the listener previous_song = "" num_scenes = len(scene_listener_pairs) - for idx, scene_listener_pair in enumerate(scene_listener_pairs): + for idx, scene_listener_pair in enumerate(scene_listener_pairs, 1): scene_id, listener_id = scene_listener_pair scene = scenes[scene_id] diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index 097b52912..5ff2027dd 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -238,7 +238,7 @@ def run_calculate_aq(config: DictConfig) -> None: config.evaluate.batch :: config.evaluate.batch_size ] num_scenes = len(scene_listener_pairs) - for idx, scene_listener_pair in enumerate(scene_listener_pairs): + for idx, scene_listener_pair in enumerate(scene_listener_pairs, 1): scene_id, listener_id = scene_listener_pair scene = scenes[scene_id] From a724597aef88b969934ae62e1cba322fd937e5a2 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 17:48:46 +0100 Subject: [PATCH 50/85] renaming file to scene_id-listener Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/enhance.py | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/enhance.py b/recipes/cad_icassp_2024/baseline/enhance.py index 04f878717..89c0652ea 100644 --- a/recipes/cad_icassp_2024/baseline/enhance.py +++ b/recipes/cad_icassp_2024/baseline/enhance.py @@ -253,7 +253,7 @@ def enhance(config: DictConfig) -> None: logger.info( f"[{idx:03d}/{num_scenes:03d}] " - f"Processing {song_name} for listener {listener_id}" + f"Processing {scene_id}: {song_name} for listener {listener_id}" ) # Get the listener's audiogram listener = listener_dict[listener_id] @@ -292,12 +292,7 @@ def enhance(config: DictConfig) -> None: apply_compressor=config.apply_compressor, ) - filename = Path( - enhanced_folder - / f"{listener.id}" - / f"{song_name}" - / f"{scene_id}_{listener.id}_remix.flac" - ) + filename = Path(enhanced_folder) / f"{scene_id}_{listener.id}_remix.flac" filename.parent.mkdir(parents=True, exist_ok=True) save_flac_signal( From 7826d749bc67152198336ae59907a22b38a46f2b Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 19:04:16 +0100 Subject: [PATCH 51/85] evaluate Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/evaluate.py | 40 +++++++++----------- 1 file changed, 17 insertions(+), 23 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index 5ff2027dd..0b1d570c2 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -246,7 +246,7 @@ def run_calculate_aq(config: DictConfig) -> None: logger.info( f"[{idx:03d}/{num_scenes:03d}] " - f"Evaluating {song_name} for listener {listener_id}" + f"Evaluating {scene_id} for listener {listener_id}" ) # Load reference signals @@ -269,17 +269,10 @@ def run_calculate_aq(config: DictConfig) -> None: # Load enhanced signal enhanced_signal, _ = read_flac_signal( - Path( - enhanced_folder - / f"{listener.id}" - / f"{song_name}" - / f"{scene_id}_{listener.id}_remix.flac" - ) + Path(enhanced_folder) / f"{scene_id}_{listener.id}_remix.flac" ) - # Compute the scores - # First, we apply NAL-R to the reference signal - # Compute the score for left channel + # Apply hearing aid to reference signals left_reference = apply_ha( enhancer=enhancer, compressor=None, @@ -287,9 +280,18 @@ def run_calculate_aq(config: DictConfig) -> None: audiogram=listener.audiogram_left, apply_compressor=False, ) + right_reference = apply_ha( + enhancer=enhancer, + compressor=None, + signal=reference_mixture[:, 1], + audiogram=listener.audiogram_right, + apply_compressor=False, + ) + + # Compute the scores left_score = compute_haaqi( - processed_signal=enhanced_signal[:44100, 0], - reference_signal=left_reference[:44100], + processed_signal=enhanced_signal[:, 0], + reference_signal=left_reference, processed_sample_rate=config.remix_sample_rate, reference_sample_rate=config.sample_rate, audiogram=listener.audiogram_left, @@ -297,22 +299,14 @@ def run_calculate_aq(config: DictConfig) -> None: level1=65 - 20 * np.log10(compute_rms(reference_mixture[:, 0])), ) - # Compute score for right channel - right_reference = apply_ha( - enhancer=enhancer, - compressor=None, - signal=reference_mixture[:, 1], - audiogram=listener.audiogram_right, - apply_compressor=False, - ) right_score = compute_haaqi( - processed_signal=enhanced_signal[:44100, 1], - reference_signal=right_reference[:44100], + processed_signal=enhanced_signal[:, 1], + reference_signal=right_reference, processed_sample_rate=config.remix_sample_rate, reference_sample_rate=config.sample_rate, audiogram=listener.audiogram_right, equalisation=2, - level1=65 - 20 * np.log10(compute_rms(right_reference)), + level1=65 - 20 * np.log10(compute_rms(reference_mixture[:, 1])), ) # Save scores From fa4ead0d4d49104906f81c8a8311e883d22ab0ce Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 19:15:12 +0100 Subject: [PATCH 52/85] add pyflac to requirement Signed-off-by: Gerardo Roa Dabike --- pyproject.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/pyproject.toml b/pyproject.toml index 5380d9f05..c7fb4a81a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -42,6 +42,7 @@ dependencies = [ "numpy>=1.21.6", "omegaconf>=2.1.1", "pandas>=1.3.5", + "pyflac", "pyloudnorm>=0.1.0", "pystoi", "pytorch-lightning", From 749f548b850cd5dde7fc6b34418d715486242db8 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 19:34:07 +0100 Subject: [PATCH 53/85] add equalisation param in cad1 evaluate Signed-off-by: Gerardo Roa Dabike --- recipes/cad1/task1/baseline/evaluate.py | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/recipes/cad1/task1/baseline/evaluate.py b/recipes/cad1/task1/baseline/evaluate.py index 469513bc6..7c41dd285 100644 --- a/recipes/cad1/task1/baseline/evaluate.py +++ b/recipes/cad1/task1/baseline/evaluate.py @@ -190,16 +190,20 @@ def _evaluate_song_listener( per_instrument_score[f"left_{instrument}"] = compute_haaqi( left_enhanced_signal, reference_signal[:, 0], - listener.audiogram_left, config.sample_rate, - 65 - 20 * np.log10(compute_rms(reference_signal[:, 0])), + config.sample_rate, + listener.audiogram_left, + equalisation=1, + level1=65 - 20 * np.log10(compute_rms(reference_signal[:, 0])), ) per_instrument_score[f"right_{instrument}"] = compute_haaqi( right_enhanced_signal, reference_signal[:, 1], - listener.audiogram_right, config.sample_rate, - 65 - 20 * np.log10(compute_rms(reference_signal[:, 1])), + config.sample_rate, + listener.audiogram_right, + equalisation=1, + level1=65 - 20 * np.log10(compute_rms(reference_signal[:, 1])), ) # Compute the combined score From d44b14f4d32f4a86f95e28201fd68c2c030a14a2 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 19:40:44 +0100 Subject: [PATCH 54/85] add recommendation from precommit Signed-off-by: Gerardo Roa Dabike --- notebooks/03_Running_the_CEC2_baseline_from_python.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/notebooks/03_Running_the_CEC2_baseline_from_python.ipynb b/notebooks/03_Running_the_CEC2_baseline_from_python.ipynb index 396b0b2f7..8d3d455cf 100644 --- a/notebooks/03_Running_the_CEC2_baseline_from_python.ipynb +++ b/notebooks/03_Running_the_CEC2_baseline_from_python.ipynb @@ -147,7 +147,7 @@ "from omegaconf import DictConfig, OmegaConf\n", "\n", "cfg = OmegaConf.load(\"clarity/recipes/cec2/baseline/config.yaml\")\n", - "assert type(cfg) == DictConfig" + "assert isinstance(cfg, DictConfig)" ] }, { From 90e081079332288924c3a05a6305361a563bcf49 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 19:42:13 +0100 Subject: [PATCH 55/85] correct call to compute haqqi Signed-off-by: Gerardo Roa Dabike --- recipes/cad1/task2/baseline/evaluate.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/recipes/cad1/task2/baseline/evaluate.py b/recipes/cad1/task2/baseline/evaluate.py index b4413ef9f..a434b3f30 100644 --- a/recipes/cad1/task2/baseline/evaluate.py +++ b/recipes/cad1/task2/baseline/evaluate.py @@ -196,14 +196,16 @@ def evaluate_scene( aq_score_l = compute_haaqi( processed_signal[0, :], ref_signal[0, :], - listener.audiogram_left, sample_rate, + sample_rate, + listener.audiogram_left, ) aq_score_r = compute_haaqi( processed_signal[1, :], ref_signal[1, :], - listener.audiogram_right, sample_rate, + sample_rate, + listener.audiogram_right, ) return aq_score_l, aq_score_r From b809dfa49f2cda1963662dea86f71c391a309045 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 19:56:49 +0100 Subject: [PATCH 56/85] fix test in CAD1 Signed-off-by: Gerardo Roa Dabike --- .../cad1/task1/baseline/test_evaluate.py | 19 ++++++++++--------- 1 file changed, 10 insertions(+), 9 deletions(-) diff --git a/tests/recipes/cad1/task1/baseline/test_evaluate.py b/tests/recipes/cad1/task1/baseline/test_evaluate.py index 5b8a06120..544094eb4 100644 --- a/tests/recipes/cad1/task1/baseline/test_evaluate.py +++ b/tests/recipes/cad1/task1/baseline/test_evaluate.py @@ -1,6 +1,7 @@ """Tests for the evaluation module""" from pathlib import Path +# pylint: disable=import-error import numpy as np import pytest from omegaconf import DictConfig @@ -101,14 +102,14 @@ def test_make_song_listener_list(): } }, { - "left_drums": 0.205517835, - "right_drums": 0.270553157, - "left_bass": 0.207187220, - "right_bass": 0.205454381, - "left_other": 0.237097711, - "right_other": 0.227505708, - "left_vocals": 0.227105999, - "right_vocals": 0.272616615, + "left_drums": 0.14229422779265366, + "right_drums": 0.15044965630960655, + "left_bass": 0.1333774836344767, + "right_bass": 0.14541827476097585, + "left_other": 0.16310480582621734, + "right_other": 0.15427835764875864, + "left_vocals": 0.12291980372806624, + "right_vocals": 0.1368378217706031, }, ) ], @@ -182,7 +183,7 @@ def test_evaluate_song_listener( # Combined score assert isinstance(combined_score, float) assert combined_score == pytest.approx( - 0.231629828, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance + 0.14358505393391977, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance ) # Per instrument score From 62ac4f33c5bd07da158492ddddfbda6cb0953fc5 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 20:05:43 +0100 Subject: [PATCH 57/85] change test smearing to obtained value Signed-off-by: Gerardo Roa Dabike --- tests/evaluator/msbg/test_smearing.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/tests/evaluator/msbg/test_smearing.py b/tests/evaluator/msbg/test_smearing.py index 0ae93ae0b..246fec6bd 100644 --- a/tests/evaluator/msbg/test_smearing.py +++ b/tests/evaluator/msbg/test_smearing.py @@ -1,4 +1,6 @@ """Tests for smearing module""" + +# pylint: disable=import-error import numpy as np import pytest @@ -38,8 +40,10 @@ def test_smear3(): smear_mat = make_smear_mat3(rl=R_LOWER, ru=R_UPPER, sample_rate=SAMPLE_RATE) output_signal = smear3(smear_mat, input_signal) assert output_signal.shape == (10240,) + # Old value were 5066.986397433977 + # but started to raise error assert np.sum(np.abs(output_signal)) == pytest.approx( - 5066.986397433977, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance + 5047.791163861037, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance ) @@ -64,6 +68,8 @@ def test_smear_valid_input(): input_signal ) assert output_signal.shape == (10240,) + # Old value were 5066.986397433977 + # but started to raise error assert np.sum(np.abs(output_signal)) == pytest.approx( - 5066.986397433977, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance + 5047.791163861037, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance ) From c9cc4935b0ed9591b3fe1c77e84f329aebe6b3ed Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 20:07:46 +0100 Subject: [PATCH 58/85] reverse las change Signed-off-by: Gerardo Roa Dabike --- tests/evaluator/msbg/test_smearing.py | 10 ++-------- 1 file changed, 2 insertions(+), 8 deletions(-) diff --git a/tests/evaluator/msbg/test_smearing.py b/tests/evaluator/msbg/test_smearing.py index 246fec6bd..0ae93ae0b 100644 --- a/tests/evaluator/msbg/test_smearing.py +++ b/tests/evaluator/msbg/test_smearing.py @@ -1,6 +1,4 @@ """Tests for smearing module""" - -# pylint: disable=import-error import numpy as np import pytest @@ -40,10 +38,8 @@ def test_smear3(): smear_mat = make_smear_mat3(rl=R_LOWER, ru=R_UPPER, sample_rate=SAMPLE_RATE) output_signal = smear3(smear_mat, input_signal) assert output_signal.shape == (10240,) - # Old value were 5066.986397433977 - # but started to raise error assert np.sum(np.abs(output_signal)) == pytest.approx( - 5047.791163861037, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance + 5066.986397433977, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance ) @@ -68,8 +64,6 @@ def test_smear_valid_input(): input_signal ) assert output_signal.shape == (10240,) - # Old value were 5066.986397433977 - # but started to raise error assert np.sum(np.abs(output_signal)) == pytest.approx( - 5047.791163861037, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance + 5066.986397433977, rel=pytest.rel_tolerance, abs=pytest.abs_tolerance ) From b11f69dc59d16a0f3011e276e376ced6314b5ee0 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 13 Sep 2023 22:32:39 +0100 Subject: [PATCH 59/85] add scores Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/recipes/cad_icassp_2024/baseline/README.md b/recipes/cad_icassp_2024/baseline/README.md index 704086ff3..cbb192c13 100644 --- a/recipes/cad_icassp_2024/baseline/README.md +++ b/recipes/cad_icassp_2024/baseline/README.md @@ -161,7 +161,10 @@ Please note: you will not get identical HAAQI scores for the same signals if the (in the given recipe, the random seed for each signal is set as the last eight digits of the song md5). As there are random noises generated within HAAQI, but the differences should be sufficiently small. -The score for the baseline is XXXX HAAQI overall. +The average validation score for the baseline is: + +* Demucs = 0.2154 HAAQI +* Open-Unmix = 0.2104 HAAQI ## References From a7e7a39f31d059506b9e826ae005f64641b8f79f Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Thu, 14 Sep 2023 19:59:38 +0100 Subject: [PATCH 60/85] Update exact check in tutorial as requested by precommit Signed-off-by: Gerardo Roa Dabike --- notebooks/03_Running_the_CEC2_baseline_from_python.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/notebooks/03_Running_the_CEC2_baseline_from_python.ipynb b/notebooks/03_Running_the_CEC2_baseline_from_python.ipynb index 396b0b2f7..8d3d455cf 100644 --- a/notebooks/03_Running_the_CEC2_baseline_from_python.ipynb +++ b/notebooks/03_Running_the_CEC2_baseline_from_python.ipynb @@ -147,7 +147,7 @@ "from omegaconf import DictConfig, OmegaConf\n", "\n", "cfg = OmegaConf.load(\"clarity/recipes/cec2/baseline/config.yaml\")\n", - "assert type(cfg) == DictConfig" + "assert isinstance(cfg, DictConfig)" ] }, { From c138aa08afdea8e5b80e1a2bd3b2ea2cf5a5bb3e Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 11:52:49 +0100 Subject: [PATCH 61/85] Add haaqi sample rate param Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/config.yaml | 1 + 1 file changed, 1 insertion(+) diff --git a/recipes/cad_icassp_2024/baseline/config.yaml b/recipes/cad_icassp_2024/baseline/config.yaml index 9edb187f3..a6e250782 100644 --- a/recipes/cad_icassp_2024/baseline/config.yaml +++ b/recipes/cad_icassp_2024/baseline/config.yaml @@ -12,6 +12,7 @@ path: sample_rate: 44100 remix_sample_rate: 32000 +HAAQI_sample_rate: 24000 nalr: nfir: 220 From b5dc6ea7ed370bf7b58f355545d7423418a5d6c1 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 11:56:27 +0100 Subject: [PATCH 62/85] resample signal before calling HAAQI Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/evaluate.py | 30 ++++++++++++++------ 1 file changed, 21 insertions(+), 9 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/evaluate.py b/recipes/cad_icassp_2024/baseline/evaluate.py index 0b1d570c2..75b4e5787 100644 --- a/recipes/cad_icassp_2024/baseline/evaluate.py +++ b/recipes/cad_icassp_2024/baseline/evaluate.py @@ -21,7 +21,7 @@ from clarity.utils.file_io import read_signal from clarity.utils.flac_encoder import read_flac_signal from clarity.utils.results_support import ResultsFile -from clarity.utils.signal_processing import compute_rms +from clarity.utils.signal_processing import compute_rms, resample logger = logging.getLogger(__name__) @@ -290,20 +290,32 @@ def run_calculate_aq(config: DictConfig) -> None: # Compute the scores left_score = compute_haaqi( - processed_signal=enhanced_signal[:, 0], - reference_signal=left_reference, - processed_sample_rate=config.remix_sample_rate, - reference_sample_rate=config.sample_rate, + processed_signal=resample( + enhanced_signal[:, 0], + config.remix_sample_rate, + config.HAAQI_sample_rate, + ), + reference_signal=resample( + left_reference, config.sample_rate, config.HAAQI_sample_rate + ), + processed_sample_rate=config.HAAQI_sample_rate, + reference_sample_rate=config.HAAQI_sample_rate, audiogram=listener.audiogram_left, equalisation=2, level1=65 - 20 * np.log10(compute_rms(reference_mixture[:, 0])), ) right_score = compute_haaqi( - processed_signal=enhanced_signal[:, 1], - reference_signal=right_reference, - processed_sample_rate=config.remix_sample_rate, - reference_sample_rate=config.sample_rate, + processed_signal=resample( + enhanced_signal[:, 1], + config.remix_sample_rate, + config.HAAQI_sample_rate, + ), + reference_signal=resample( + right_reference, config.sample_rate, config.HAAQI_sample_rate + ), + processed_sample_rate=config.HAAQI_sample_rate, + reference_sample_rate=config.HAAQI_sample_rate, audiogram=listener.audiogram_right, equalisation=2, level1=65 - 20 * np.log10(compute_rms(reference_mixture[:, 1])), From aa8d2220d2f05895cd99153ea84aa8e94f4f9f3a Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 14:07:28 +0100 Subject: [PATCH 63/85] correct baseline scores Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/README.md b/recipes/cad_icassp_2024/baseline/README.md index cbb192c13..945c1bb84 100644 --- a/recipes/cad_icassp_2024/baseline/README.md +++ b/recipes/cad_icassp_2024/baseline/README.md @@ -163,8 +163,8 @@ As there are random noises generated within HAAQI, but the differences should be The average validation score for the baseline is: -* Demucs = 0.2154 HAAQI -* Open-Unmix = 0.2104 HAAQI +* Demucs = 0.6496 HAAQI +* Open-Unmix = 0.5822 HAAQI ## References From 04a7e82c00b6422635e8d7bf100cefe965b2d6ba Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 16:12:44 +0100 Subject: [PATCH 64/85] pin numpy version < 1.25 Signed-off-by: Gerardo Roa Dabike --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 5380d9f05..329affc60 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -39,7 +39,7 @@ dependencies = [ "librosa>=0.8.1", "matplotlib", "numba>=0.57.0rc", - "numpy>=1.21.6", + "numpy>=1.21.6 <1.25.0", "omegaconf>=2.1.1", "pandas>=1.3.5", "pyloudnorm>=0.1.0", From a16e293c44d0d74649dcb8570a5a463817376e69 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 16:15:09 +0100 Subject: [PATCH 65/85] pin numpy version < 1.25 Signed-off-by: Gerardo Roa Dabike --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 329affc60..4f4fe59d4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -39,7 +39,7 @@ dependencies = [ "librosa>=0.8.1", "matplotlib", "numba>=0.57.0rc", - "numpy>=1.21.6 <1.25.0", + "numpy>=1.21.6,<1.25.0", "omegaconf>=2.1.1", "pandas>=1.3.5", "pyloudnorm>=0.1.0", From 4058090a560cc4d930f5462769abd657958faa83 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 16:33:02 +0100 Subject: [PATCH 66/85] numpy version Signed-off-by: Gerardo Roa Dabike --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index c7fb4a81a..06ea661a4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -39,7 +39,7 @@ dependencies = [ "librosa>=0.8.1", "matplotlib", "numba>=0.57.0rc", - "numpy>=1.21.6", + "numpy>=1.21.6,<1.25.0", "omegaconf>=2.1.1", "pandas>=1.3.5", "pyflac", From 8169b720c8c334866b7145d498b8a21d017b8509 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 17:14:19 +0100 Subject: [PATCH 67/85] source separation util tests Signed-off-by: Gerardo Roa Dabike --- tests/utils/test_source_separation_support.py | 105 +++++++++++++++++- 1 file changed, 103 insertions(+), 2 deletions(-) diff --git a/tests/utils/test_source_separation_support.py b/tests/utils/test_source_separation_support.py index 0916afbaf..60591a4b1 100644 --- a/tests/utils/test_source_separation_support.py +++ b/tests/utils/test_source_separation_support.py @@ -3,6 +3,7 @@ from pathlib import Path import numpy as np +import pytest import torch from clarity.utils.source_separation_support import get_device, separate_sources @@ -36,19 +37,102 @@ def forward(self, x): length = 1 sample_rate = 16000 sources = ["vocals", "drums", "bass", "other"] - mix = np.random.randn(batch_size, num_channels, length * sample_rate) + # Create a dummy model + model = DummyModel(sources) + expected_results = np.load( + RESOURCES / "test_source_separation_support.test_separate_sources.npy", + allow_pickle=True, + ) device = torch.device("cpu") + mix = np.random.randn(batch_size, num_channels, length * sample_rate) + # Call separate_sources + output = separate_sources(model, mix, sample_rate, device=device) + + # Check that the output has the correct shape + assert output.shape == expected_results.shape + np.testing.assert_array_almost_equal(output, expected_results) + + +def test_separate_sources_no_batch(): + """Test that the separate_sources function returns the expected output""" + np.random.seed(123456789) + + # Create a dummy model + class DummyModel(torch.nn.Module): # pylint: disable=too-few-public-methods + """Dummy source separation model""" + + def __init__(self, sources): + """dummy init""" + super().__init__() + self.sources = sources + + def forward(self, x): + """dummy forward""" + return torch.Tensor( + np.random.uniform(size=(x.shape[0], len(self.sources), *x.shape[1:])) + ) + + # Set up some dummy input data + + num_channels = 1 + length = 1 + sample_rate = 16000 + sources = ["vocals", "drums", "bass", "other"] # Create a dummy model model = DummyModel(sources) + expected_results = np.load( + RESOURCES / "test_source_separation_support.test_separate_sources.npy", + allow_pickle=True, + ) + device = torch.device("cpu") + mix = np.random.randn(num_channels, length * sample_rate) # Call separate_sources output = separate_sources(model, mix, sample_rate, device=device) + # Check that the output has the correct shape + assert output.shape == expected_results.shape + np.testing.assert_array_almost_equal(output, expected_results) + + +def test_separate_sources_extra_dim(): + """Test that the separate_sources function returns the expected output""" + np.random.seed(123456789) + + # Create a dummy model + class DummyModel(torch.nn.Module): # pylint: disable=too-few-public-methods + """Dummy source separation model""" + + def __init__(self, sources): + """dummy init""" + super().__init__() + self.sources = sources + + def forward(self, x): + """dummy forward""" + return torch.Tensor( + np.random.uniform(size=(x.shape[0], len(self.sources), *x.shape[1:])) + ) + + # Set up some dummy input data + + num_channels = 2 + length = 1 + sample_rate = 16000 + sources = ["vocals", "drums", "bass", "other"] + # Create a dummy model + model = DummyModel(sources) expected_results = np.load( - RESOURCES / "test_source_separation_support.test_separate_sources.npy", + RESOURCES / "test_source_separation_support.test_separate_sources_stereo.npy", allow_pickle=True, ) + device = torch.device("cpu") + + mix = np.random.randn(1, num_channels, length * sample_rate) + # Call separate_sources + output = separate_sources(model, mix, sample_rate, device=device) + # Check that the output has the correct shape assert output.shape == expected_results.shape np.testing.assert_array_almost_equal(output, expected_results) @@ -64,3 +148,20 @@ def test_get_device(): else torch.device("cpu") ) assert device_type == "cuda" if torch.cuda.is_available() else "cpu" + + +def test_get_device_cpu(): + """Test the correct device selection given the inputs""" + # Test default case (no argument passed) + device, device_type = get_device("cpu") + assert device == torch.device("cpu") + assert device_type == "cpu" + + +def tests_get_device_wrong(): + """Test the wrong device selection given the inputs""" + # Test default case (no argument passed) + with pytest.raises(ValueError): + device, device_type = get_device("wrong") + assert device == torch.device("cpu") + assert device_type == "cpu" From eba339c135ba5e2df8ebd98381668f0f8e3f054d Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 17:24:25 +0100 Subject: [PATCH 68/85] source separation util tests Signed-off-by: Gerardo Roa Dabike --- ...on_support.test_separate_sources_stereo.npy | Bin 0 -> 512128 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 tests/resources/utils/test_source_separation_support.test_separate_sources_stereo.npy diff --git a/tests/resources/utils/test_source_separation_support.test_separate_sources_stereo.npy 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 @@ -88,7 +89,7 @@ pip install -e git+https://github.com/claritychallenge/clarity.git@main Current challenge -- [The ICASSP 2024 Cadenza CHallenge](./recipes/cad_icassp_2024) +- [The ICASSP 2024 Cadenza Challenge](./recipes/cad_icassp_2024) Previous challenges From 5b236d0f1460700d37b1d4cf3db1642c8b08d8f2 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 20 Sep 2023 08:53:49 +0100 Subject: [PATCH 81/85] correct challenge version in Readme Signed-off-by: Gerardo Roa Dabike --- README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/README.md b/README.md index 43f5934d6..abee1d0b4 100644 --- a/README.md +++ b/README.md @@ -22,7 +22,6 @@ [![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.3.4&color=orange)](https://pypi.org/project/pyclarity/0.3.4/) [![PyPI](https://img.shields.io/static/v1?label=ICASSP%202023%20Challenge%20-%20pypi&message=v0.2.1&color=orange)](https://pypi.org/project/pyclarity/0.2.1/) [![PyPI](https://img.shields.io/static/v1?label=CEC2%20Challenge%20-%20pypi&message=v0.1.1&color=orange)](https://pypi.org/project/pyclarity/0.1.1/) - [![ORDA](https://img.shields.io/badge/ORDA--DOI-10.15131%2Fshef.data.23230694.v.1-lightgrey)](https://figshare.shef.ac.uk/articles/software/clarity/23230694/1)

From 58779d0dc1a544e8d64d97eb87bb43a47eb3bbd3 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 20 Sep 2023 08:54:05 +0100 Subject: [PATCH 82/85] correct challenge version in Readme Signed-off-by: Gerardo Roa Dabike --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index abee1d0b4..43f5934d6 100644 --- a/README.md +++ b/README.md @@ -22,6 +22,7 @@ [![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.3.4&color=orange)](https://pypi.org/project/pyclarity/0.3.4/) [![PyPI](https://img.shields.io/static/v1?label=ICASSP%202023%20Challenge%20-%20pypi&message=v0.2.1&color=orange)](https://pypi.org/project/pyclarity/0.2.1/) [![PyPI](https://img.shields.io/static/v1?label=CEC2%20Challenge%20-%20pypi&message=v0.1.1&color=orange)](https://pypi.org/project/pyclarity/0.1.1/) + [![ORDA](https://img.shields.io/badge/ORDA--DOI-10.15131%2Fshef.data.23230694.v.1-lightgrey)](https://figshare.shef.ac.uk/articles/software/clarity/23230694/1)

From b54e15972aa240f5c608e820d63efb0f5b409569 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 20 Sep 2023 11:52:24 +0100 Subject: [PATCH 83/85] search precreated only in train Signed-off-by: Gerardo Roa Dabike --- .../cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py b/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py index 3b31ddfd3..88b9eb51f 100644 --- a/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py +++ b/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py @@ -118,7 +118,7 @@ def find_precreated_samples(source_dir: str | Path) -> list[str]: if not source_dir.exists(): return [] - return [f.name for f in source_dir.glob("*/*")] + return [f.name for f in source_dir.glob("train/*")] @hydra.main(config_path="", config_name="config") From 2c1fc945761b4fe6801fe535a38d44eb67fb7a2a Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 20 Sep 2023 12:08:15 +0100 Subject: [PATCH 84/85] ensure the pre-created completed all tracks Signed-off-by: Gerardo Roa Dabike --- .../generate_dataset/generate_at_mic_musdb18.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py b/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py index 88b9eb51f..e98ced488 100644 --- a/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py +++ b/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py @@ -118,7 +118,12 @@ def find_precreated_samples(source_dir: str | Path) -> list[str]: if not source_dir.exists(): return [] - return [f.name for f in source_dir.glob("train/*")] + previous_tracks = [] + for song_path in source_dir.glob("train/*"): + if len(list(song_path.glob("*"))) >= 5: + previous_tracks.append(song_path.name) + + return previous_tracks @hydra.main(config_path="", config_name="config") From 32f86ba41a669b48a2488ec5d839da55aae35841 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 20 Sep 2023 12:51:58 +0100 Subject: [PATCH 85/85] test pre-created Signed-off-by: Gerardo Roa Dabike --- .../test_generate_at_mic_musdb18.py | 17 +++++++++++++---- 1 file changed, 13 insertions(+), 4 deletions(-) diff --git a/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_at_mic_musdb18.py b/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_at_mic_musdb18.py index b898b5bab..215b115cd 100644 --- a/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_at_mic_musdb18.py +++ b/tests/recipes/cad_icassp_2024/generate_dataset/test_generate_at_mic_musdb18.py @@ -20,11 +20,20 @@ @pytest.fixture(name="temp_dir_with_samples") def fixture_temp_dir_with_samples(tmp_path): source_dir = Path(tmp_path) - sample_dirs = ["sample_dir1", "sample_dir2"] - for sample_dir in sample_dirs: + sample_dirs = { + "sample_dir1": [ + "sample1.wav", + "sample2.wav", + "sample3.wav", + "sample4.wav", + "sample5.wav", + ], + "sample_dir2": ["sample1.wav"], + } + + for sample_dir, sample_files in sample_dirs.items(): sample_dir_path = Path(source_dir) / "train" / sample_dir sample_dir_path.mkdir(exist_ok=True, parents=True) - sample_files = ["sample1.wav", "sample2.wav"] for sample_file in sample_files: with open(sample_dir_path / sample_file, "w", encoding="utf-8") as f: f.write("Sample content") @@ -147,7 +156,7 @@ def test_find_precreated_samples(temp_dir_with_samples): # Check if the expected sample files are in the result assert "sample_dir1" in precreated_samples - assert "sample_dir1" in precreated_samples + assert "sample_dir2" not in precreated_samples def test_find_precreated_samples_empty_directory(tmp_path):

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z*(b9>$q$8()=yZY?-phr( z$A*Z0tjT6WKGh2|`yCXdQ?3hZB|G?RD3c`@ZD0>-i`azEd)eq?KJ1avf9&a^|JXCl z!K~fjB3nG6n5E0f3Q}$JnPFs%@ML>7i;9sHKCIX)sApYe2BLpXi?_(LUE^AXL_UMd z5L03MACDLH1#J{gZ%Yv#i1lZQhRN*6t!h>|B#Rm5t{051YYIX7ds*t3LS{EVjX4hV z5q_?XV_ufNEcN+rraK^wah(+_UvX8qcF~H}WbJ0&dhX0>>Kq~elp|X`!kTF(&S&0# zlG)JkLY8}@PIzXM#By{Vi{Ad)#VY!uS*3XGqeu_|bQIW~|Rti49z6%j0YuPZ)BM-~aVB7i(Se8rzGhFG(n$AvU zzg~9=uBp|+R1-V)E;f+O^Iz$tRq<4`O7^AjC3iB5kvu1O=^q!Js{c<|(do&OF6|YX zhwHGF!!HPXE*i7M)!#&KJis6f9dV)X+W^*;t;&+p zK8a#?-xWgts}cr0>=9O)T^3pRlnRet_KD1&e-&=7yC$qMgK)$^g?*VnQ&^rS5|XZN z6?VpGicBhth2c-H3L9$Q3eykOh~DbUvGJ{G!odO;!Ct%{J3mWS`U0wiiMb)d z`v;nW=jC-y|H@=VY8~^0ej~3sG+%lwx-oK!Ffq`{X*HJ@ig^zfhCCc4%sc5Os2BYf z35!}pL&H-YAN6l>I=*+1{jhr%9Pgc9Bl_DuL*#DTDoU0ik-Y0>k+gJ;Xz{uvk#YER ukw*UsP9eqOBDcMRLxmkui Date: Fri, 15 Sep 2023 17:34:26 +0100 Subject: [PATCH 69/85] test result support Signed-off-by: Gerardo Roa Dabike --- tests/utils/test_results_support.py | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/tests/utils/test_results_support.py b/tests/utils/test_results_support.py index 6722bd9b5..507de0206 100644 --- a/tests/utils/test_results_support.py +++ b/tests/utils/test_results_support.py @@ -18,6 +18,13 @@ def fixture_results_file(tmpdir): return ResultsFile(file_name, sample_header) +def test_create_file_str(tmpdir): + # Create a temporary directory and a temporary CSV file for testing + file_name = f"{tmpdir}/test_results.csv" + result_file = ResultsFile(file_name, sample_header) + assert result_file.file_name.as_posix() == file_name + + def test_add_result(results_file): # Test adding a result to the CSV file results_file.add_result({"Name": "Charlie", "Score": 75}) From 950c69f064baa03af341ed0718d2a9143d99f18c Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 17:42:16 +0100 Subject: [PATCH 70/85] test source separation Signed-off-by: Gerardo Roa Dabike --- tests/utils/test_signal_processing.py | 28 +++++++++++++++++++ tests/utils/test_source_separation_support.py | 4 +-- 2 files changed, 29 insertions(+), 3 deletions(-) diff --git a/tests/utils/test_signal_processing.py b/tests/utils/test_signal_processing.py index 62a91946b..0b7942c99 100644 --- a/tests/utils/test_signal_processing.py +++ b/tests/utils/test_signal_processing.py @@ -1,8 +1,10 @@ """Test for utils.signal_processing module""" +# pylint: disable=import-error import numpy as np import pytest from clarity.utils.signal_processing import ( + clip_signal, compute_rms, denormalize_signals, normalize_signal, @@ -10,6 +12,32 @@ ) +def test_clip_signal_hard_clip(): + # Test hard clipping (default behavior) + input_signal = np.array([1.5, -0.5, 2.0, -2.5, 0.75]) + clipped_signal, n_clipped = clip_signal(input_signal) + assert np.all(clipped_signal == np.array([1.0, -0.5, 1.0, -1.0, 0.75])) + assert n_clipped == 3 + + +def test_clip_signal_soft_clip(): + # Test soft clipping + input_signal = np.array([1.5, -0.5, 2.0, -2.5, 0.75]) + clipped_signal, n_clipped = clip_signal(input_signal, soft_clip=True) + assert np.sum(clipped_signal) == pytest.approx( + np.sum([0.90514825, -0.46211716, 0.96402758, -0.9866143, 0.63514895]) + ) + assert n_clipped == 0 + + +def test_clip_signal_all_within_range(): + # Test when all values are already within the range + input_signal = np.array([-0.8, 0.2, -0.6, 0.9]) + clipped_signal, n_clipped = clip_signal(input_signal) + assert np.all(clipped_signal == input_signal) + assert n_clipped == 0 + + @pytest.mark.parametrize( "signal,normalised_result,row_means", ( # Simple input diff --git a/tests/utils/test_source_separation_support.py b/tests/utils/test_source_separation_support.py index 60591a4b1..30caeba86 100644 --- a/tests/utils/test_source_separation_support.py +++ b/tests/utils/test_source_separation_support.py @@ -74,8 +74,6 @@ def forward(self, x): ) # Set up some dummy input data - - num_channels = 1 length = 1 sample_rate = 16000 sources = ["vocals", "drums", "bass", "other"] @@ -87,7 +85,7 @@ def forward(self, x): ) device = torch.device("cpu") - mix = np.random.randn(num_channels, length * sample_rate) + mix = np.random.randn(length * sample_rate) # Call separate_sources output = separate_sources(model, mix, sample_rate, device=device) From 7dc037e87982e4b2493825d5b1ca81d6496189bc Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 17:57:09 +0100 Subject: [PATCH 71/85] the readme Signed-off-by: Gerardo Roa Dabike --- README.md | 12 +++++++----- clarity/utils/source_separation_support.py | 5 +---- tests/utils/test_source_separation_support.py | 4 +++- 3 files changed, 11 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 2d6eef2ad..d5f55d57d 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/claritychallenge/clarity/main.svg)](https://results.pre-commit.ci/latest/github/claritychallenge/clarity/main) [![Downloads](https://pepy.tech/badge/pyclarity)](https://pepy.tech/project/pyclarity) -[![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.3.3&color=orange)](https://pypi.org/project/pyclarity/0.3.3/) +[![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.4.0&color=orange)](https://pypi.org/project/pyclarity/0.4.0/) [![PyPI](https://img.shields.io/static/v1?label=ICASSP%202023%20Challenge%20-%20pypi&message=v0.2.1&color=orange)](https://pypi.org/project/pyclarity/0.2.1/) [![PyPI](https://img.shields.io/static/v1?label=CEC2%20Challenge%20-%20pypi&message=v0.1.1&color=orange)](https://pypi.org/project/pyclarity/0.1.1/) [![ORDA](https://img.shields.io/badge/ORDA--DOI-10.15131%2Fshef.data.23230694.v.1-lightgrey)](https://figshare.shef.ac.uk/articles/software/clarity/23230694/1) @@ -34,10 +34,11 @@ In this repository, you will find code to support all Clarity and Cadenza Challe ## Current Events -- The first Cadenza Challenge (CAD1) is now open. :fire::fire: +- The ICASSP 2024 Cadenza Challenge (CAD_ICASSP_2024) is now open. :fire::fire: - Join the [Cadenza Challenge Group](https://groups.google.com/g/cadenza-challenge) to keep up-to-date on developments. - Visit the Cadenenza Challenge [website](https://cadenzachallenge.org/) for more details. - - Evaluation tools and a baseline system are available in the [CAD1 recipes](./recipes/cad1) folder. :new: +- The first Cadenza Challenge (CAD1) is closed. + - Subjective Evaluation is underway. :new: - The 2nd Clarity Prediction Challenge (CPC2) is now open. :fire::fire: - Join the [Clarity Challenge Group](https://groups.google.com/g/clarity-challenge) to keep up-to-date on developments. - Visit the Clarity Challenge [website](https://claritychallenge.org/) for more details. @@ -86,11 +87,12 @@ pip install -e git+https://github.com/claritychallenge/clarity.git@main Current challenge -- [The 1st Cadenza Challenge (CAD1)](./recipes/cad1) -- [The 2nd Clarity Prediction Challenge (CPC2)](./recipes/cpc2) +- [The ICASSP 2024 Cadenza CHallenge](./recipes/cad_icassp_2024) Previous challenges +- [The 1st Cadenza Challenge (CAD1)](./recipes/cad1) +- [The 2nd Clarity Prediction Challenge (CPC2)](./recipes/cpc2) - [The ICASSP 2023 Enhancement Challenge](./recipes/icassp_2023) - [The 2nd Clarity Enhancement Challenge (CEC2)](./recipes/cec2) - [The 1st Clarity Prediction Challenge (CPC1)](./recipes/cpc1) diff --git a/clarity/utils/source_separation_support.py b/clarity/utils/source_separation_support.py index 5ecbe2041..0b4279fd7 100644 --- a/clarity/utils/source_separation_support.py +++ b/clarity/utils/source_separation_support.py @@ -37,10 +37,7 @@ def separate_sources( device = mix.device if device is None else torch.device(device) mix = torch.as_tensor(mix, device=device) - if mix.ndim == 1: - # one track and mono audio - mix = mix.unsqueeze(0) - elif mix.ndim == 2: + if mix.ndim == 2: # one track and stereo audio mix = mix.unsqueeze(0) diff --git a/tests/utils/test_source_separation_support.py b/tests/utils/test_source_separation_support.py index 30caeba86..60591a4b1 100644 --- a/tests/utils/test_source_separation_support.py +++ b/tests/utils/test_source_separation_support.py @@ -74,6 +74,8 @@ def forward(self, x): ) # Set up some dummy input data + + num_channels = 1 length = 1 sample_rate = 16000 sources = ["vocals", "drums", "bass", "other"] @@ -85,7 +87,7 @@ def forward(self, x): ) device = torch.device("cpu") - mix = np.random.randn(length * sample_rate) + mix = np.random.randn(num_channels, length * sample_rate) # Call separate_sources output = separate_sources(model, mix, sample_rate, device=device) From 92b444fda32de306f3a82c6d9b4692425373345c Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 18:09:26 +0100 Subject: [PATCH 72/85] test flac encoder Signed-off-by: Gerardo Roa Dabike --- tests/utils/test_flac_encoder.py | 76 ++++++++++++++++++++++++++++++++ 1 file changed, 76 insertions(+) create mode 100644 tests/utils/test_flac_encoder.py diff --git a/tests/utils/test_flac_encoder.py b/tests/utils/test_flac_encoder.py new file mode 100644 index 000000000..85aa1e8f0 --- /dev/null +++ b/tests/utils/test_flac_encoder.py @@ -0,0 +1,76 @@ +"""Tests for the FlacEncoder class.""" +# pylint: disable=import-error +from pathlib import Path +from tempfile import NamedTemporaryFile + +import numpy as np +import pytest + +from clarity.utils.flac_encoder import FlacEncoder, read_flac_signal + + +def test_encode_decode(): + """Test that the FlacEncoder can encode and decode a signal.""" + # create a random signal + np.random.seed(0) + + sample_rate = 8000 + signal = np.random.uniform(-1, 1, int(0.5 * sample_rate)) + signal_int16 = signal * 32768.0 + signal_int16 = np.clip(signal_int16, -32768, 32767).astype(np.int16) + + # write the encoded bytes to a temporary file + with NamedTemporaryFile(suffix=".flac", delete=False) as tmpfile: + encoder = FlacEncoder() + # encode + _ = encoder.encode( + signal_int16, sample_rate=sample_rate, output_file=tmpfile.name + ) + # decode + decoded_signal, decoded_sr = encoder.decode(Path(tmpfile.name)) + + # check that the decoded signal matches the original signal + assert np.sum(signal_int16) == pytest.approx( + np.sum(decoded_signal), + rel=pytest.rel_tolerance, + abs=pytest.abs_tolerance, + ) + + # check that the sample rate of the decoded signal is correct + assert decoded_sr == sample_rate + + +def test_read_flac_signal(tmp_path): + # Create a test FLAC file + np.random.seed(2023) + + filename = tmp_path / "test.flac" + + sample_rate = 16000 + signal = np.random.rand(1600) + scale_factor = np.max(np.abs(signal)) + + signal_scaled = signal / scale_factor + signal_scaled = signal_scaled * 32768.0 + signal_scaled = np.clip(signal_scaled, -32768.0, 32767.0) + signal_scaled = signal_scaled.astype(np.dtype("int16")) + + flac_encoder = FlacEncoder() + flac_encoder.encode(signal_scaled, sample_rate, filename) + + # Create a test scale factor file + scale_filename = tmp_path / "test.txt" + with open(scale_filename, "w", encoding="utf-8") as fp: + fp.write(str(scale_factor)) + + # Call the function and check the output + signal_out, sample_rate_out = read_flac_signal(filename) + + # As a result of the quantization, the signal is not exactly the same + # after encoding and decoding, so I'm changing the tolerance + # for this test + # np.sum(signal_out) = 2190.4271092907347 + # np.sum(signal) = 2190.494140495932 + + assert np.sum(signal_out) == pytest.approx(np.sum(signal), rel=1e-4, abs=1e-4) + assert sample_rate_out == sample_rate From 3660f2272277c10d0e0e72bf36d0d073c7d77621 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Fri, 15 Sep 2023 18:29:12 +0100 Subject: [PATCH 73/85] Update README.md Add ICASSP 2024 badge --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index d5f55d57d..d31c1e147 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,8 @@ [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/claritychallenge/clarity/main.svg)](https://results.pre-commit.ci/latest/github/claritychallenge/clarity/main) [![Downloads](https://pepy.tech/badge/pyclarity)](https://pepy.tech/project/pyclarity) -[![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.4.0&color=orange)](https://pypi.org/project/pyclarity/0.4.0/) +[![PyPI](https://img.shields.io/static/v1?label=ICASSP%202024%20Cadenza%20Challenge%20-%20pypi&message=v0.4.0&color=orange)](https://pypi.org/project/pyclarity/0.4.0/) +[![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.3.4&color=orange)](https://pypi.org/project/pyclarity/0.3.4/) [![PyPI](https://img.shields.io/static/v1?label=ICASSP%202023%20Challenge%20-%20pypi&message=v0.2.1&color=orange)](https://pypi.org/project/pyclarity/0.2.1/) [![PyPI](https://img.shields.io/static/v1?label=CEC2%20Challenge%20-%20pypi&message=v0.1.1&color=orange)](https://pypi.org/project/pyclarity/0.1.1/) [![ORDA](https://img.shields.io/badge/ORDA--DOI-10.15131%2Fshef.data.23230694.v.1-lightgrey)](https://figshare.shef.ac.uk/articles/software/clarity/23230694/1) From c50ffe15e9e8852032df5aa59f7bbde0263984d5 Mon Sep 17 00:00:00 2001 From: Jon Barker Date: Sun, 17 Sep 2023 18:41:39 +0100 Subject: [PATCH 74/85] Fixed smear3 to work with newer numpy versions --- clarity/evaluator/msbg/smearing.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/clarity/evaluator/msbg/smearing.py b/clarity/evaluator/msbg/smearing.py index 29c59500d..a3f72b287 100644 --- a/clarity/evaluator/msbg/smearing.py +++ b/clarity/evaluator/msbg/smearing.py @@ -124,10 +124,11 @@ def smear3(f_smear: ndarray, inbuffer: ndarray) -> ndarray: winwave = np.zeros(FFT_SIZE) winwave[0:FRAME_SIZE] = window * inwave.flatten() spectrum = np.fft.fft(winwave, FFT_SIZE) - power = spectrum[0:nyquist] * np.conj(spectrum[0:nyquist]) - mag = np.sqrt(power) + + mag = np.abs(spectrum[0:nyquist]) phasor = spectrum[0:nyquist] / (mag + (mag == 0)) - smeared = np.dot(f_smear, power) + + smeared = np.dot(f_smear, (mag**2).astype(complex)) spectrum[0:nyquist] = np.sqrt(smeared) * phasor spectrum[nyquist] = 0 spectrum[(nyquist + 1) : FFT_SIZE] = np.conj(spectrum[nyquist - 1 : 0 : -1]) From 752d2308fa60c0c99e527b8932b9b89726928767 Mon Sep 17 00:00:00 2001 From: Jon Barker Date: Sun, 17 Sep 2023 18:50:46 +0100 Subject: [PATCH 75/85] Removed the pyproject.toml constaint on numpy --- pyproject.toml | 201 +++++++++++++++++++------------------------------ 1 file changed, 78 insertions(+), 123 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 06ea661a4..1f9fa9d24 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,104 +1,92 @@ [build-system] -requires = [ - "setuptools >= 45", - "setuptools_scm[toml]>=6.2", - "wheel", - ] +requires = ["setuptools >= 45", "setuptools_scm[toml]>=6.2", "wheel"] build-backend = "setuptools.build_meta" [project] name = "pyclarity" description = "Tools for the Clarity Challenge" readme = "README.md" -license = {text = "MIT"} +license = { text = "MIT" } dynamic = ["version"] authors = [ - {name = "The PyClarity Team", email = "claritychallengecontact@gmail.com"}, + { name = "The PyClarity Team", email = "claritychallengecontact@gmail.com" }, ] classifiers = [ - "Intended Audience :: Developers", - "Intended Audience :: Education", - "Intended Audience :: Science/Research", - "License :: OSI Approved :: MIT License", - "Operating System :: OS Independent", - "Programming Language :: Python :: 3", - "Natural Language :: English", -] -keywords = [ - "hearing", - "signal processing", - "clarity challenge" -] + "Intended Audience :: Developers", + "Intended Audience :: Education", + "Intended Audience :: Science/Research", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", + "Programming Language :: Python :: 3", + "Natural Language :: English", +] +keywords = ["hearing", "signal processing", "clarity challenge"] requires-python = ">=3.8" dependencies = [ - "audioread>=2.1.9", - "gdown", - "hydra-core>=1.1.1", - "hydra-submitit-launcher>=1.1.6", - "importlib-metadata", - "librosa>=0.8.1", - "matplotlib", - "numba>=0.57.0rc", - "numpy>=1.21.6,<1.25.0", - "omegaconf>=2.1.1", - "pandas>=1.3.5", - "pyflac", - "pyloudnorm>=0.1.0", - "pystoi", - "pytorch-lightning", - "resampy", - "scikit-learn>=1.0.2", - "scipy>=1.7.3", - "SoundFile>=0.10.3.post1", - "soxr", - "torch>=2", - "torchaudio", - "tqdm>=4.62.3", - "typing_extensions", + "audioread>=2.1.9", + "gdown", + "hydra-core>=1.1.1", + "hydra-submitit-launcher>=1.1.6", + "importlib-metadata", + "librosa>=0.8.1", + "matplotlib", + "numba>=0.57.0rc", + "numpy>=1.21.6", + "omegaconf>=2.1.1", + "pandas>=1.3.5", + "pyflac", + "pyloudnorm>=0.1.0", + "pystoi", + "pytorch-lightning", + "resampy", + "scikit-learn>=1.0.2", + "scipy>=1.7.3", + "SoundFile>=0.10.3.post1", + "soxr", + "torch>=2", + "torchaudio", + "tqdm>=4.62.3", + "typing_extensions", ] [project.optional-dependencies] tests = [ - "coverage", - "isort", - "flake8", - "flake8-print", - "Flake8-pyproject", - "mypy", - "pre-commit", - "py", - "py-cpuinfo", - "pytest", - "pytest-cov", - "pytest-mock", - "pytest-mpl", - "pytest-regtest", - "pytest-skip-slow", - "pytest-xdist", - "yamllint", -] -docs =[ - "sphinx", - "myst_parser", - "pydata_sphinx_theme", - "sphinx_markdown_tables", - "sphinx_rtd_theme", - "sphinxcontrib-mermaid", - "sphinxcontrib-napoleon", + "coverage", + "isort", + "flake8", + "flake8-print", + "Flake8-pyproject", + "mypy", + "pre-commit", + "py", + "py-cpuinfo", + "pytest", + "pytest-cov", + "pytest-mock", + "pytest-mpl", + "pytest-regtest", + "pytest-skip-slow", + "pytest-xdist", + "yamllint", +] +docs = [ + "sphinx", + "myst_parser", + "pydata_sphinx_theme", + "sphinx_markdown_tables", + "sphinx_rtd_theme", + "sphinxcontrib-mermaid", + "sphinxcontrib-napoleon", ] dev = [ - "black", - "pre-commit", - "pycodestyle", - "pylint", - "pylint-pytest", - "yamllint", -] -pypi =[ - "build", - "wheel", - "setuptools_scm[toml]" -] + "black", + "pre-commit", + "pycodestyle", + "pylint", + "pylint-pytest", + "yamllint", +] +pypi = ["build", "wheel", "setuptools_scm[toml]"] [project.urls] Source = "https://github.com/claritychallenge/clarity" @@ -118,17 +106,8 @@ exclude = ["tests*"] namespaces = false [tool.setuptools.package-data] -clarity = [ - "*.json", - "*.mat", - "*.yaml" -] -recipes = [ - "*.csv", - "*.json", - "*.mat", - "*.yaml" -] +clarity = ["*.json", "*.mat", "*.yaml"] +recipes = ["*.csv", "*.json", "*.mat", "*.yaml"] [tool.setuptools_scm] @@ -140,21 +119,12 @@ git_describe_command = "git describe --tags" [tool.pytest.ini_options] minversion = "7.0" addopts = "--cov clarity" -testpaths = [ - "tests", -] -filterwarnings = [ - "ignore::UserWarning" -] +testpaths = ["tests"] +filterwarnings = ["ignore::UserWarning"] [tool.coverage.run] source = ["clarity"] -omit = [ - "*conftest.py", - "*tests*", - "**/__init__*", - "clarity/_version.py", -] +omit = ["*conftest.py", "*tests*", "**/__init__*", "clarity/_version.py"] [tool.black] line-length = 88 @@ -171,23 +141,11 @@ exclude = ''' ''' [flake8] -ignore =[ - "E203", - "E501", - "W503", -] +ignore = ["E203", "E501", "W503"] # docstring-convention = "" max-line-length = 88 max-complexity = 18 -select = [ - "B", - "C", - "E", - "F", - "W", - "T4", - "B9" -] +select = ["B", "C", "E", "F", "W", "T4", "B9"] [tool.ruff] exclude = [ @@ -221,7 +179,4 @@ fixable = ["A", "B", "C", "D", "E", "F", "R", "S", "W", "U"] [tool.mypy] ignore_missing_imports = true -exclude = [ - "docs/*", - "build/*" -] +exclude = ["docs/*", "build/*"] From 01b1660369dd2667d903f48180d5cf8319ff4517 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 19 Sep 2023 17:28:22 +0100 Subject: [PATCH 76/85] head_loudspeaker_position Signed-off-by: Gerardo Roa Dabike --- .../generate_dataset/generate_at_mic_musdb18.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py b/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py index 381f049da..3b31ddfd3 100644 --- a/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py +++ b/recipes/cad_icassp_2024/generate_dataset/generate_at_mic_musdb18.py @@ -145,14 +145,14 @@ def run(cfg: DictConfig) -> None: music_metadata = {m["Track Name"]: m for m in music_metadata} # Load the head positions metadata - with open(cfg.path.head_positions_file, encoding="utf-8") as f: + with open(cfg.path.head_loudspeaker_positions_file, encoding="utf-8") as f: head_positions_metadata = json.load(f) # From the scenes, get the samples names and parameters toprocess_samples = { - f"{v['music']}-{v['head_position']}": { + f"{v['music']}-{v['head_loudspeaker_positions']}": { "music": v["music"], - "head_position": v["head_position"], + "head_loudspeaker_positions": v["head_loudspeaker_positions"], } for _, v in scenes_metadata.items() } @@ -162,7 +162,7 @@ def run(cfg: DictConfig) -> None: for idx, sample in enumerate(toprocess_samples.items(), 1): sample_name, sample_detail = sample music = music_metadata[sample_detail["music"]] - head_position = sample_detail["head_position"] + head_position = sample_detail["head_loudspeaker_positions"] out_music[sample_name] = { "Track Name": sample_name, From e34d7672da102a4b676091a803c54c305261b41b Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 19 Sep 2023 17:30:52 +0100 Subject: [PATCH 77/85] head_loudspeaker_position Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/config.yaml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/config.yaml b/recipes/cad_icassp_2024/baseline/config.yaml index a6e250782..6038f16a0 100644 --- a/recipes/cad_icassp_2024/baseline/config.yaml +++ b/recipes/cad_icassp_2024/baseline/config.yaml @@ -4,10 +4,10 @@ path: music_dir: ${path.root}/audio/at_mic_music gains_file: ${path.metadata_dir}/gains.json head_positions_file: ${path.metadata_dir}/head_positions.json - listeners_file: ${path.metadata_dir}/listeners.valid.json - music_file: ${path.metadata_dir}/at_mic_music.valid.json - scenes_file: ${path.metadata_dir}/scenes.valid.json - scene_listeners_file: ${path.metadata_dir}/scene_listeners.valid.json + listeners_file: ${path.metadata_dir}/listeners.train.json + music_file: ${path.metadata_dir}/at_mic_music.train.json + scenes_file: ${path.metadata_dir}/scenes.train.json + scene_listeners_file: ${path.metadata_dir}/scene_listeners.train.json exp_folder: ./exp # folder to store enhanced signals and final results sample_rate: 44100 From 276c0c01031bd5a85cd783730474a02e45b8cb00 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 19 Sep 2023 17:31:31 +0100 Subject: [PATCH 78/85] no validation score Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/README.md | 5 ----- 1 file changed, 5 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/README.md b/recipes/cad_icassp_2024/baseline/README.md index 945c1bb84..2fbe5b947 100644 --- a/recipes/cad_icassp_2024/baseline/README.md +++ b/recipes/cad_icassp_2024/baseline/README.md @@ -161,11 +161,6 @@ Please note: you will not get identical HAAQI scores for the same signals if the (in the given recipe, the random seed for each signal is set as the last eight digits of the song md5). As there are random noises generated within HAAQI, but the differences should be sufficiently small. -The average validation score for the baseline is: - -* Demucs = 0.6496 HAAQI -* Open-Unmix = 0.5822 HAAQI - ## References * [1] Défossez, A. "Hybrid Spectrogram and Waveform Source Separation". Proceedings of the ISMIR 2021 Workshop on Music Source Separation. [doi:10.48550/arXiv.2111.03600](https://arxiv.org/abs/2111.03600) From d4893ab5e127a69a9f9881a070f2e21d182657b0 Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Tue, 19 Sep 2023 17:43:46 +0100 Subject: [PATCH 79/85] better readme Signed-off-by: Gerardo Roa Dabike --- recipes/cad_icassp_2024/baseline/README.md | 75 ++++++++++------------ 1 file changed, 34 insertions(+), 41 deletions(-) diff --git a/recipes/cad_icassp_2024/baseline/README.md b/recipes/cad_icassp_2024/baseline/README.md index 2fbe5b947..c5cd04c58 100644 --- a/recipes/cad_icassp_2024/baseline/README.md +++ b/recipes/cad_icassp_2024/baseline/README.md @@ -10,9 +10,8 @@ The ICASSP 2024 Cadenza Challenge dataset is based on the MUSDB18-HQ dataset. To download the data, please visit [Download data and software](https://cadenzachallenge.org/docs/icassp_2024/take_part/download) webpage. -The data is split into four packages: `cadenza_icassp2024_core.v1_0.tgz`, -`cadenza_icassp2024_augmentation_medleydb.tar.gz`, `cadenza_icassp2024_augmentation_bach10.tar.gz` -and `cadenza_icassp2024_augmentation_fma_small.tar.gz`. +The data is split into four packages: `cad_icassp_2024_core.v1.1.tgz`, +`cad_icassp_2024_train.v1.0.tgz`, and `cad_icassp_2024_medleydb.tgz`. Unpack packages under the same root directory using @@ -22,26 +21,15 @@ tar -xvzf ### 1.1 Necessary data -* **Core** contains the metadata and audio signal to generate the ICASSP 2024 dataset. +* **Core** contains the metadata and HRTFs signals to generate the ICASSP 2024 dataset. ```text cadenza_data ├───audio -| ├───hrtf (336 kB) -| | | BTE_fr-VP_E1-n22.5.wav -| | | BTE_fr-VP_E1-n30.0.wav -| | | ... -| | -| └───music -| └───train (20.2 GB) -| ├───A Classic Education - NightOwl -| | | bass.wav -| | | drums.wav -| | | other.wav -| | | vocals.wav -| | | mixture.wav -| | -| ├───... +| └───hrtf (336 kB) +| | BTE_fr-VP_E1-n22.5.wav +| | BTE_fr-VP_E1-n30.0.wav +| | ... | └───metadata (328 kB) | gains.json @@ -49,16 +37,32 @@ cadenza_data | listeners.train.json | listeners.valid.json | musdb18.train.json - | musdb18.valid.json | scene_listeners.train.json | scenes.train.json | ... ``` +* **train** contains the MUSDB18 train split signals to generate the ICASSP 2024 dataset. + +```text +cadenza_data +└───audio + └───music (22 GB) + └─── Train + ├─── A Classic Education - NightOwl + | | Bass.wav + | | Drums.wav + | | Other.wav + | | Vocals.wav + | | Mixture.wav + ├─── ... +``` + ### 1.2 Additional optional data -If you need additional music data for training your model, please restrict to the use of [MedleyDB](https://medleydb.weebly.com/) [[5](#references)] [[6](#references)], +If you need additional music data for training your model, please restrict to the use of +[MedleyDB](https://medleydb.weebly.com/) [[5](#references)] [[6](#references)], [BACH10](https://labsites.rochester.edu/air/resource.html) [7] and [FMA-small](https://github.com/mdeff/fma) [7]. **Keeping the augmentation data restricted to these datasets will ensure that the evaluation is fair for all participants**. @@ -73,33 +77,22 @@ cadenza_data └───Metadata ``` -* **BACH10** contains the BACH10 dataset [[7](#references)]. +* **BACH10** [[7](#references)]. -Tracks from the BACH10 dataset are not included in MUSDB18-HQ and can all be used as training augmentation data. - -```text -cadenza_data -└───audio - └───Bach10 (150 MB) - ├───01-AchGottundHerr - ├───... -``` +Bach10 dataset can be downloaded from +[Download data and software](https://cadenzachallenge.org/docs/icassp_2024/take_part/download#b1-download-the-packages) +on the Challenge website. * **FMA Small** contains the FMA small subset of the FMA dataset [[8](references)]. +FMA small dataset can be downloaded from +[Download data and software](https://cadenzachallenge.org/docs/icassp_2024/take_part/download#b1-download-the-packages) +on the Challenge website. + Tracks from the FMA small dataset are not included in the MUSDB18-HQ. This dataset does not provide independent stems but only the full mix. However, it can be used to train an unsupervised model to better initialise a supervised model. -```text -cadenza_data -└───audio - └───fma_small (8 GB) - ├───000 - ├───001 - ├───... -``` - ## 2. Baseline In the `baseline/` folder, we provide code for running the baseline enhancement system and performing the objective evaluation. @@ -113,7 +106,7 @@ the VDBO (vocals, drums, bass and others) stems for each song-listener pair. For each estimated stem, the baseline applies the gains and remix the signal. A simple NAL-R [2] fitting amplification is applied to the final remix -The basile offers 2 source separation options: +The baseline offers 2 source separation options: 1. [Hybrid Demucs](https://github.com/facebookresearch/demucs) [[1](#references)] distributed on [TorchAudio](https://pytorch.org/audio/main/tutorials/hybrid_demucs_tutorial.html) 2. [Open-Unmix](https://github.com/sigsep/open-unmix-pytorch) [[2](#references)] distributed through Pytorch hub. From acec8817f034ecf3c9d2da930f684590c5525fed Mon Sep 17 00:00:00 2001 From: Gerardo Roa Dabike Date: Wed, 20 Sep 2023 08:49:55 +0100 Subject: [PATCH 80/85] correct challenge version in Readme Signed-off-by: Gerardo Roa Dabike --- README.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index d31c1e147..43f5934d6 100644 --- a/README.md +++ b/README.md @@ -18,10 +18,11 @@ [![pre-commit.ci status](https://results.pre-commit.ci/badge/github/claritychallenge/clarity/main.svg)](https://results.pre-commit.ci/latest/github/claritychallenge/clarity/main) [![Downloads](https://pepy.tech/badge/pyclarity)](https://pepy.tech/project/pyclarity) -[![PyPI](https://img.shields.io/static/v1?label=ICASSP%202024%20Cadenza%20Challenge%20-%20pypi&message=v0.4.0&color=orange)](https://pypi.org/project/pyclarity/0.4.0/) +[![PyPI](https://img.shields.io/static/v1?label=ICASSP%202024%20Cadenza%20Challenge%20-%20pypi&message=v0.4.1&color=orange)](https://pypi.org/project/pyclarity/0.4.1/) [![PyPI](https://img.shields.io/static/v1?label=CAD1%20and%20CPC2%20Challenges%20-%20pypi&message=v0.3.4&color=orange)](https://pypi.org/project/pyclarity/0.3.4/) [![PyPI](https://img.shields.io/static/v1?label=ICASSP%202023%20Challenge%20-%20pypi&message=v0.2.1&color=orange)](https://pypi.org/project/pyclarity/0.2.1/) [![PyPI](https://img.shields.io/static/v1?label=CEC2%20Challenge%20-%20pypi&message=v0.1.1&color=orange)](https://pypi.org/project/pyclarity/0.1.1/) + [![ORDA](https://img.shields.io/badge/ORDA--DOI-10.15131%2Fshef.data.23230694.v.1-lightgrey)](https://figshare.shef.ac.uk/articles/software/clarity/23230694/1)