Finalize keypoint detection #174
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SolomonLake
commented
Dec 6, 2023
| @@ -35,6 +35,7 @@ | |||
| "object-detection": "yolov5v2s", | |||
| "instance-segmentation": "yolact", | |||
| "classification": "vit", | |||
| "keypoint-detection": "yolov8n", | |||
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most changes are keypoints-detection -> keypoint-detection, but this was a necessary addition to make sure model manager accepts type.
PawelPeczek-Roboflow
approved these changes
Dec 7, 2023
PawelPeczek-Roboflow
approved these changes
Dec 7, 2023
| num_classes = get_num_classes_from_model_prediction_shape( | ||
| len_prediction=output_shape[2], keypoints_shape=keypoints_shape | ||
| ) | ||
| try: |
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if num_classes != self.num_classes:
raise ValueError()| assert keypoints_count == 17 | ||
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| def test_superset_keypoints_count_with_two_classes(): |
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Suggestion:
Return type: -> None:
given-when-then
# given
keypoints_metadata = ...
# when
keypoints_count = superset_keypoints_count(keypoints_metadata)
# then
assert keypoints_count == 13, "Keypoints of object 1 form a superset of all classes"Would be also good to cover the behaviour when classes do not overlap
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Added, going to merge after build succeeds as changes were straightforward.
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Actually, maybe I need another review? merging is blocked
PawelPeczek-Roboflow
approved these changes
Dec 11, 2023
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Description
Updates keypoint detection to match with what is being sent from dataset/weights routes. Also adds validation for num_classes.
Type of change
Please delete options that are not relevant.
How has this change been tested, please provide a testcase or example of how you tested the change?
Tested running local inference server for one keypoints detection model and one OD model.
Any specific deployment considerations
None.
Docs