PyTorch model evaluation - `per_keypoint_evaluation` and `comparisonbodyparts` by n-poulsen · Pull Request #2810 · DeepLabCut/DeepLabCut
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This pull request implements the per_keypoint_evaluation and comparisonbodyparts parameters for PyTorch pose estimation models.
Updates
- New
per_keypoint_evaluationargument fordeeplabcut.pose_estimation_pytorch.apis.evaluation.evaluate_networkto compute the errors (RMSE and mAP) based on a subset of bodyparts, as done fortensorflowmodels - New
comparisonbodypartsargument fordeeplabcut.pose_estimation_pytorch.apis.evaluation.evaluate_networkto compute RMSE per-bodypart and store the results in a CSV file, as done fortensorflowmodels - Inclusion of unique bodypart RMSE in the "main" RMSE computation to match the
tensorflowRMSE computation - Additional tests to verify that RMSE computation is correct
- Updates the functional PyTorch tests to compute per-bodypart RMSE
- Update
docs/pytorch/user_guide.mdso that methods where parameters still need to be implemented are labeled orange and not green - Update
docs/pytorch/user_guide.mdto reflect thatcomparisonbodypartsandper_keypoint_evaluationcan now be used with PyTorch models
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Beside the two comments regarding documentation - this looks good to me!
n-poulsen
deleted the
niels/evaluate_network_comparison
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