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The metadata for this dataset is missing the keypoint connection rules: https://detectron2.readthedocs.io/en/latest/tutorials/datasets.html#metadata-for-datasets should be something like: KEYPOINT_CONNECTION_RULES = [
# face
("left_ear", "left_eye", (102, 204, 255)),
("right_ear", "right_eye", (51, 153, 255)),
("left_eye", "nose", (102, 0, 204)),
("nose", "right_eye", (51, 102, 255)),
# upper-body
("left_shoulder", "right_shoulder", (255, 128, 0)),
("left_shoulder", "left_elbow", (153, 255, 204)),
("right_shoulder", "right_elbow", (128, 229, 255)),
("left_elbow", "left_wrist", (153, 255, 153)),
("right_elbow", "right_wrist", (102, 255, 224)),
# lower-body
("left_hip", "right_hip", (255, 102, 0)),
("left_hip", "left_knee", (255, 255, 77)),
("right_hip", "right_knee", (153, 255, 204)),
("left_knee", "left_ankle", (191, 255, 128)),
("right_knee", "right_ankle", (255, 195, 77)),
] |
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Thanks, that works! |
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Hi I have successfully trained my own custom model and was using it to run inference on some images, The model appears to work pretty well and I have no issues with the display of the bounding box and the keypoint annotations itself. However I was expecting that the keypoints would be connected into a skeleton structure instead of just showing up as points. I have previously defined the connections when annotating using COCO annotator. Here is my code.
I have tried both the "draw_instance_predictions" and "draw_and_connect_keypoints" functions but both yielded similar results.
(See image below for expectation vs reality)
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