{"language": "Python", "id": 32, "repo_owner": "mikel-brostrom", "repo_name": "yolo_tracking", "head_branch": "centroid-asso-support", "workflow_name": "CI CPU testing", "workflow_filename": "ci.yml", "workflow_path": ".github/workflows/ci.yml", "contributor": "mikel-brostrom", "sha_fail": "03669a5d72130c57575bedd657b82c601f08a982", "sha_success": "0948605abb9d6d962450f1bbf9a0b9c96c429b29", "workflow": "# name of the workflow, what it is doing (optional)\nname: CI CPU testing\n\n# events that trigger the workflow (required)\non:\n push:\n branches: [master, CIdebug]\n pull_request:\n # pull request where master is target\n branches: [master]\n\nenv:\n # Directory of PyPi package to be tested\n PACKAGE_DIR: boxmot\n # Minimum acceptable test coverage\n # Increase as you add more tests to increase coverage\n COVERAGE_FAIL_UNDER: 29\n\n# the workflow that gets triggerd\njobs:\n build:\n runs-on: ${{ matrix.os }}\n strategy:\n fail-fast: false\n matrix:\n os: [ubuntu-latest] # skip windows-latest for\n python-version: ['3.8', '3.9', '3.10']\n #model: ['yolov8n', 'yolo_nas_s', yolox_n] # yolo models to test\n #tracking-methods: ['deepocsort', 'ocsort', 'botsort', 'strongsort', 'bytetrack'] # tracking methods to test\n\n # Timeout: https://stackoverflow.com/a/59076067/4521646\n timeout-minutes: 50\n steps:\n\n - uses: actions/checkout@v4 # Check out the repository\n - uses: actions/setup-python@v5 # Prepare environment with python 3.9\n with:\n python-version: ${{ matrix.python-version }}\n cache: 'pip' # caching pip dependencies\n - name: Install requirements\n shell: bash # for Windows compatibility\n run: |\n python -m pip install --upgrade pip setuptools wheel\n pip install -e . pytest pytest-cov --extra-index-url https://download.pytorch.org/whl/cpu\n python --version\n pip --version\n pip list\n\n - name: Tests all tracking options\n shell: bash # for Windows compatibility\n env:\n IMG: ./assets/MOT17-mini/train/MOT17-05-FRCNN/img1/000001.jpg\n run: |\n # deepocsort fro all supported yolo models\n python examples/track.py --tracking-method deepocsort --source $IMG --imgsz 320\n python examples/track.py --yolo-model yolo_nas_s --tracking-method deepocsort --source $IMG --imgsz 320\n # python examples/track.py --yolo-model yolox_n --tracking-method deepocsort --source $IMG --imgsz 320\n\n # hybridsort\n python examples/track.py --tracking-method hybridsort --source $IMG --imgsz 320\n\n # botsort\n python examples/track.py --tracking-method botsort --source $IMG --imgsz 320\n\n # strongsort\n python examples/track.py --tracking-method strongsort --source $IMG --imgsz 320\n\n # ocsort\n python examples/track.py --tracking-method ocsort --source $IMG --imgsz 320\n\n # bytetrack\n python examples/track.py --tracking-method bytetrack --source $IMG --imgsz 320\n\n - name: Pytest tests # after tracking options as this does not download models\n shell: bash # for Windows compatibility\n run: |\n\n # needed in TFLite export\n wget https://github.com/PINTO0309/onnx2tf/releases/download/1.16.31/flatc.tar.gz\n tar -zxvf flatc.tar.gz\n sudo chmod +x flatc\n sudo mv flatc /usr/bin/\n\n pytest --cov=$PACKAGE_DIR --cov-report=html -v tests\n coverage report --fail-under=$COVERAGE_FAIL_UNDER\n\n - name: Tests exported reid models\n env:\n IMG: ./assets/MOT17-mini/train/MOT17-05-FRCNN/img1/000001.jpg\n shell: bash # for Windows compatibility\n run: |\n\n # test exported reid model\n python examples/track.py --reid-model examples/weights/osnet_x0_25_msmt17.torchscript --source $IMG --imgsz 320\n python examples/track.py --reid-model examples/weights/osnet_x0_25_msmt17.onnx --source $IMG --imgsz 320\n #python examples/track.py --reid-model examples/weights/osnet_x0_25_msmt17_saved_model/osnet_x0_25_msmt17_float16.tflite --source $IMG --imgsz 320\n python examples/track.py --reid-model examples/weights/osnet_x0_25_msmt17_openvino_model --source $IMG --imgsz 320\n\n - name: Test tracking with seg models\n env:\n IMG: ./assets/MOT17-mini/train/MOT17-05-FRCNN/img1/000001.jpg\n shell: bash # for Windows compatibility\n run: |\n # tracking with SEG models\n python examples/track.py --tracking-method deepocsort --yolo-model yolov8n-seg.pt --source $IMG\n\n - name: Test tracking with pose models\n env:\n IMG: ./assets/MOT17-mini/train/MOT17-05-FRCNN/img1/000001.jpg\n shell: bash # for Windows compatibility\n run: |\n # tracking with POSE models\n python3 examples/track.py --yolo-model weights/yolov8n.pt --source $IMG --imgsz 320\n\n - name: Test validation on MOT17 subset\n shell: bash # for Windows compatibility\n run: |\n # validation on a few MOT17 imges\n python examples/val.py --tracking-method deepocsort --yolo-model yolov8n.pt --benchmark MOT17-mini --imgsz 320 --conf 0.2\n\n - name: Test evolution on MOT17 subset\n shell: bash # for Windows compatibility\n run: |\n # evolve a for a single set of parameters\n python examples/evolve.py --objectives HOTA,MOTA,IDF1 --benchmark MOT17-mini --n-trials 1 --imgsz 320 --conf 0.2\n", "logs": [{"step_name": "build (ubuntu-latest, 3.8)/6_Pytest tests.txt", "log": "##[group]Run # needed in TFLite export\n\u001b[36;1m\u001b[0m\n\u001b[36;1m# needed in TFLite export\u001b[0m\n\u001b[36;1mwget https://github.com/PINTO0309/onnx2tf/releases/download/1.16.31/flatc.tar.gz\u001b[0m\n\u001b[36;1mtar -zxvf flatc.tar.gz\u001b[0m\n\u001b[36;1msudo chmod +x flatc\u001b[0m\n\u001b[36;1msudo mv flatc /usr/bin/\u001b[0m\n\u001b[36;1m\u001b[0m\n\u001b[36;1mpytest --cov=$PACKAGE_DIR --cov-report=html -v tests\u001b[0m\n\u001b[36;1mcoverage report --fail-under=$COVERAGE_FAIL_UNDER\u001b[0m\nshell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}\nenv:\n PACKAGE_DIR: boxmot\n COVERAGE_FAIL_UNDER: 29\n pythonLocation: /opt/hostedtoolcache/Python/3.8.18/x64\n PKG_CONFIG_PATH: /opt/hostedtoolcache/Python/3.8.18/x64/lib/pkgconfig\n Python_ROOT_DIR: /opt/hostedtoolcache/Python/3.8.18/x64\n Python2_ROOT_DIR: /opt/hostedtoolcache/Python/3.8.18/x64\n 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\u2018flatc.tar.gz\u2019 saved [1382707/1382707]\n\nflatc\n============================= test session starts ==============================\nplatform linux -- Python 3.8.18, pytest-7.4.4, pluggy-1.3.0 -- /opt/hostedtoolcache/Python/3.8.18/x64/bin/python\ncachedir: .pytest_cache\nrootdir: /home/runner/work/yolo_tracking/yolo_tracking\nplugins: hydra-core-1.3.2, cov-4.1.0\ncollecting ... collected 14 items\n\ntests/test_exports.py::test_export_torchscript PASSED [ 7%]\ntests/test_exports.py::test_export_onnx PASSED [ 14%]\ntests/test_exports.py::test_export_openvino PASSED [ 21%]\ntests/test_python.py::test_strongsort_instantiation PASSED [ 28%]\ntests/test_python.py::test_botsort_instantiation PASSED [ 35%]\ntests/test_python.py::test_deepocsort_instantiation PASSED [ 42%]\ntests/test_python.py::test_ocsort_instantiation PASSED [ 50%]\ntests/test_python.py::test_bytetrack_instantiation PASSED [ 57%]\ntests/test_python.py::test_deepocsort_output FAILED [ 64%]\ntests/test_python.py::test_ocsort_output PASSED [ 71%]\ntests/test_python.py::test_botsort_output PASSED [ 78%]\ntests/test_python.py::test_bytetrack_output PASSED [ 85%]\ntests/test_python.py::test_strongsort_output PASSED [ 92%]\ntests/test_python.py::test_gsi PASSED [100%]\n\n=================================== FAILURES ===================================\n____________________________ test_deepocsort_output ____________________________\n\n def test_deepocsort_output():\n tracker_conf = get_tracker_config('deepocsort')\n tracker = create_tracker(\n tracker_type='deepocsort',\n tracker_config=tracker_conf,\n reid_weights=WEIGHTS / 'mobilenetv2_x1_4_dukemtmcreid.pt',\n device='cpu',\n half=False,\n per_class=False\n )\n rgb = np.random.randint(255, size=(640, 640, 3), dtype=np.uint8)\n det = np.array([[144, 212, 578, 480, 0.82, 0],\n [425, 281, 576, 472, 0.56, 65]])\n output = tracker.update(det, rgb)\n # Works since frame count is less than min hits (1 <= 2)\n assert output.shape == (2, 8) # two inputs should give two outputs\n output = np.flip(np.delete(output, [4, 7], axis=1), axis=0)\n assert_allclose(det, output, atol=1, rtol=7e-3, verbose=True)\n \n # Instantiate new tracker and ensure minimum number of hits works\n tracker = create_tracker(\n tracker_type='deepocsort',\n tracker_config=tracker_conf,\n reid_weights=WEIGHTS / 'mobilenetv2_x1_4_dukemtmcreid.pt',\n device='cpu',\n half=False,\n per_class=False\n )\n tracker.min_hits = 2\n output = tracker.update(np.empty((0, 6)), rgb)\n assert output.size == 0\n output = tracker.update(np.empty((0, 6)), rgb)\n assert output.size == 0\n output = tracker.update(det, rgb)\n assert output.size == 0\n> output = tracker.update(det, rgb)\n\ntests/test_python.py:86: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \nboxmot/trackers/deepocsort/deep_ocsort.py:434: in update\n matched, unmatched_dets, unmatched_trks = associate(\nboxmot/utils/association.py:146: in associate\n iou_matrix = run_asso_func(asso_func, detections, trackers, w, h)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nfunc = \nargs = (array([[1.44e+02, 2.12e+02, 5.78e+02, 4.80e+02, 8.20e-01],\n [4.25e+02, 2.81e+02, 5.76e+02, 4.72e+02, 5.60e-01]]), array([[144., 212., 578., 480., 0.],\n [425., 281., 576., 472., 0.]]), 640, 640)\n\n def run_asso_func(func, *args):\n \"\"\"\n Wrapper function that checks the inputs to the association functions\n and then call either one of the iou association functions or centroid.\n \n Parameters:\n func: The batch function to call (either *iou*_batch or centroid_batch).\n *args: Variable length argument list, containing either bounding boxes and optionally size parameters.\n \"\"\"\n if func not in [iou_batch, giou_batch, diou_batch, ciou_batch, centroid_batch]:\n raise ValueError(\"Invalid function specified. Must be either '(g,d,c, )iou_batch' or 'centroid_batch'.\")\n \n if func is (iou_batch or giou_batch or diou_batch or ciou_batch):\n if len(args) != 4 or not all(isinstance(arg, (list, np.ndarray)) for arg in args[0:2]):\n raise ValueError(\"Invalid arguments for iou_batch. Expected two bounding boxes.\")\n return func(*args)\n elif func is centroid_batch:\n if len(args) != 4 or not all(isinstance(arg, (list, np.ndarray)) for arg in args[:2]) or not all(isinstance(arg, (int)) for arg in args[2:]):\n raise ValueError(\"Invalid arguments for centroid_batch. Expected two bounding boxes and two size parameters.\")\n return func(*args)\n else:\n> raise ValueError(\"No such association method\")\nE ValueError: No such association method\n\nboxmot/utils/iou.py:212: ValueError\n----------------------------- Captured stderr call -----------------------------\nDownloading...\nFrom: https://drive.google.com/uc?id=12uD5FeVqLg9-AFDju2L7SQxjmPb4zpBN\nTo: /home/runner/work/yolo_tracking/yolo_tracking/examples/weights/mobilenetv2_x1_4_dukemtmcreid.pt\n\n 0%| | 0.00/22.4M [00:00 output = tracker.update(det, rgb)\n\ntests/test_python.py:86: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \nboxmot/trackers/deepocsort/deep_ocsort.py:434: in update\n matched, unmatched_dets, unmatched_trks = associate(\nboxmot/utils/association.py:146: in associate\n iou_matrix = run_asso_func(asso_func, detections, trackers, w, h)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nfunc = \nargs = (array([[1.44e+02, 2.12e+02, 5.78e+02, 4.80e+02, 8.20e-01],\n [4.25e+02, 2.81e+02, 5.76e+02, 4.72e+02, 5.60e-01]]), array([[144., 212., 578., 480., 0.],\n [425., 281., 576., 472., 0.]]), 640, 640)\n\n def run_asso_func(func, *args):\n \"\"\"\n Wrapper function that checks the inputs to the association functions\n and then call either one of the iou association functions or centroid.\n \n Parameters:\n func: The batch function to call (either *iou*_batch or centroid_batch).\n *args: Variable length argument list, containing either bounding boxes and optionally size parameters.\n \"\"\"\n if func not in [iou_batch, giou_batch, diou_batch, ciou_batch, centroid_batch]:\n raise ValueError(\"Invalid function specified. Must be either '(g,d,c, )iou_batch' or 'centroid_batch'.\")\n \n if func is (iou_batch or giou_batch or diou_batch or ciou_batch):\n if len(args) != 4 or not all(isinstance(arg, (list, np.ndarray)) for arg in args[0:2]):\n raise ValueError(\"Invalid arguments for iou_batch. Expected two bounding boxes.\")\n return func(*args)\n elif func is centroid_batch:\n if len(args) != 4 or not all(isinstance(arg, (list, np.ndarray)) for arg in args[:2]) or not all(isinstance(arg, (int)) for arg in args[2:]):\n raise ValueError(\"Invalid arguments for centroid_batch. Expected two bounding boxes and two size parameters.\")\n return func(*args)\n else:\n> raise ValueError(\"No such association method\")\nE ValueError: No such association method\n\nboxmot/utils/iou.py:212: ValueError\n----------------------------- Captured stderr call -----------------------------\nDownloading...\nFrom: https://drive.google.com/uc?id=12uD5FeVqLg9-AFDju2L7SQxjmPb4zpBN\nTo: /home/runner/work/yolo_tracking/yolo_tracking/examples/weights/mobilenetv2_x1_4_dukemtmcreid.pt\n\n 0%| | 0.00/22.4M [00:00 output = tracker.update(det, rgb)\n\ntests/test_python.py:86: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \nboxmot/trackers/deepocsort/deep_ocsort.py:434: in update\n matched, unmatched_dets, unmatched_trks = associate(\nboxmot/utils/association.py:146: in associate\n iou_matrix = run_asso_func(asso_func, detections, trackers, w, h)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nfunc = \nargs = (array([[1.44e+02, 2.12e+02, 5.78e+02, 4.80e+02, 8.20e-01],\n [4.25e+02, 2.81e+02, 5.76e+02, 4.72e+02, 5.60e-01]]), array([[144., 212., 578., 480., 0.],\n [425., 281., 576., 472., 0.]]), 640, 640)\n\n def run_asso_func(func, *args):\n \"\"\"\n Wrapper function that checks the inputs to the association functions\n and then call either one of the iou association functions or centroid.\n \n Parameters:\n func: The batch function to call (either *iou*_batch or centroid_batch).\n *args: Variable length argument list, containing either bounding boxes and optionally size parameters.\n \"\"\"\n if func not in [iou_batch, giou_batch, diou_batch, ciou_batch, centroid_batch]:\n raise ValueError(\"Invalid function specified. Must be either '(g,d,c, )iou_batch' or 'centroid_batch'.\")\n \n if func is (iou_batch or giou_batch or diou_batch or ciou_batch):\n if len(args) != 4 or not all(isinstance(arg, (list, np.ndarray)) for arg in args[0:2]):\n raise ValueError(\"Invalid arguments for iou_batch. Expected two bounding boxes.\")\n return func(*args)\n elif func is centroid_batch:\n if len(args) != 4 or not all(isinstance(arg, (list, np.ndarray)) for arg in args[:2]) or not all(isinstance(arg, (int)) for arg in args[2:]):\n raise ValueError(\"Invalid arguments for centroid_batch. Expected two bounding boxes and two size parameters.\")\n return func(*args)\n else:\n> raise ValueError(\"No such association method\")\nE ValueError: No such association method\n\nboxmot/utils/iou.py:212: ValueError\n----------------------------- Captured stderr call -----------------------------\nDownloading...\nFrom: https://drive.google.com/uc?id=12uD5FeVqLg9-AFDju2L7SQxjmPb4zpBN\nTo: /home/runner/work/yolo_tracking/yolo_tracking/examples/weights/mobilenetv2_x1_4_dukemtmcreid.pt\n\n 0%| | 0.00/22.4M [00:00