[WIP] Integration with DeepLabCut 3.0 - PyTorch Engine (#121)

Author: n-poulsen

.github/workflows/testing.yml

@@ -4,7 +4,6 @@ on:
   push:
     branches: [main]
   pull_request:
-    branches: [main]
 
 jobs:
   build:
@@ -13,33 +12,36 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-latest, macos-latest] #windows-latest
-        python-version: ["3.9", "3.10"] #3.11+ issues with TF 
-        exclude:
-          - os: macos-latest
-            python-version: "3.9"
+        os: [ubuntu-latest, macos-latest, windows-latest]
+        python-version: ["3.10", "3.11", "3.12"]
         include:
           - os: ubuntu-latest
             path: ~/.cache/pip
           - os: macos-latest
             path: ~/Library/Caches/pip
+          - os: windows-latest
+            path: ~\AppData\Local\pip\Cache
+        exclude:
+          - os: windows-latest
+            python-version: "3.11"
+          - os: windows-latest
+            python-version: "3.12"
 
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
 
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
+      - name: Install uv
+        uses: astral-sh/setup-uv@v6
         with:
+          enable-cache: true
+          version: "0.9.5"
           python-version: ${{ matrix.python-version }}
 
-      - name: Set up Python
-        uses: conda-incubator/setup-miniconda@v3
-        with:
-          channels: conda-forge,defaults
-          channel-priority: strict
-          python-version: ${{ matrix.python-version }}
-          
+      - name: Install the project
+        run: uv sync --all-extras --dev
+        shell: bash
+        
       - name: Install ffmpeg
         run: |
           if [ "$RUNNER_OS" == "Linux" ]; then
@@ -51,27 +53,9 @@ jobs:
             choco install ffmpeg
           fi
         shell: bash
-        
-      - name: Install PyTables through Conda
-        shell: bash -el {0}  # Important: activates the conda environment
-        run: |
-          conda install pytables==3.8.0 "numpy<2"
-          
-      - name: Install dependencies via Conda
-        shell: bash -el {0}
-        run: conda install -y "numpy>=1.26,<2.0"
-
-      - name: Install Poetry
-        run: pip install --upgrade pip wheel poetry
-
-      - name: Regenerate Poetry lock
-        run: poetry lock --no-cache
-
-      - name: Install project dependencies
-        run: poetry install --with dev
 
       - name: Run DLC Live Tests
-        run: poetry run dlc-live-test --nodisplay
+        run: uv run dlc-live-test --nodisplay
 
       - name: Run Functional Benchmark Test
-        run: poetry run pytest tests/test_benchmark_script.py
+        run: uv run pytest

.gitignore

@@ -3,13 +3,17 @@
 # Data related to benchmark!
 benchmarking/Data*
 benchmarking/results*
-
+dlclive/check_install/dlc-live-tmp*
 *test*
 **DS_Store*
 *vscode*
 
 **/__MACOSX/
 
+# Include tests directory (negate the *test* pattern for tests/)
+!tests/
+!tests/**
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]
@@ -18,6 +22,10 @@ __pycache__/
 # C extensions
 *.so
 
+# uv or poetry lock files
+poetry.lock
+uv.lock
+
 # Distribution / packaging
 .Python
 build/

README.md

@@ -12,6 +12,7 @@
 import glob
 
 from dlclive import benchmark_videos, download_benchmarking_data
+from dlclive.engine import Engine
 
 datafolder = os.path.join(
     pathlib.Path(__file__).parent.absolute(), "Data-DLC-live-benchmark"
@@ -36,8 +37,22 @@
 if not os.path.isdir(out_dir):
     os.mkdir(out_dir)
 
-for m in dog_models:
-    benchmark_videos(m, dog_video, output=out_dir, n_frames=n_frames, pixels=pixels)
-
-for m in mouse_models:
-    benchmark_videos(m, mouse_video, output=out_dir, n_frames=n_frames, pixels=pixels)
+for model_path in dog_models:
+    benchmark_videos(
+        model_path=model_path,
+        model_type="base" if Engine.from_model_path(model_path) == Engine.TENSORFLOW else "pytorch",
+        video_path=dog_video,
+        output=out_dir,
+        n_frames=n_frames,
+        pixels=pixels
+    )
+
+for model_path in mouse_models:
+    benchmark_videos(
+        model_path=model_path,
+        model_type="base" if Engine.from_model_path(model_path) == Engine.TENSORFLOW else "pytorch",
+        video_path=mouse_video,
+        output=out_dir,
+        n_frames=n_frames,
+        pixels=pixels
+    )

benchmarking/run_dlclive_benchmark.py

@@ -5,7 +5,13 @@
 Licensed under GNU Lesser General Public License v3.0
 """
 
-from dlclive.version import __version__, VERSION
+# Check which backends are installed and get available backends
+# (Emits a warning if neither TensorFlow nor PyTorch is installed)
+from dlclive.utils import get_available_backends
+_AVAILABLE_BACKENDS = get_available_backends()
+
+from dlclive.display import Display
 from dlclive.dlclive import DLCLive
-from dlclive.processor import Processor
-from dlclive.benchmark import benchmark, benchmark_videos, download_benchmarking_data
+from dlclive.processor.processor import Processor
+from dlclive.version import VERSION, __version__
+from dlclive.benchmark import benchmark_videos, download_benchmarking_data