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Hi, first of all thank you for sharing your great job. I am trying to use a modified version of your code in order to train on a custom dataset with a different number of keypoints. After 5 epochs as you have done in your example. I have modified the code in order to use a different number of keypoints (6 keypoints): ClassDataset and the evaluation code (kpt_oks_sigmas for 6 keypoints).
I obtain a model that gets a good detection of the object (bounding box) but the keypoints are not well located. For example:
This images show that the detection is getting trained but the keypoints are not. Moreover at the evaluation phase I always get values equal to zero:
IoU metric: keypoints
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets= 20 ] = 0.000
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets= 20 ] = 0.000
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets= 20 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = -1.000
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 20 ] = 0.000
Average Recall (AR) @[ IoU=0.50 | area= all | maxDets= 20 ] = 0.000
Average Recall (AR) @[ IoU=0.75 | area= all | maxDets= 20 ] = 0.000
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.000
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = -1.000
I have revised the dataset and it seems well annotated, so I don't know where the errors are. Any idea? Thank you in advance.
The text was updated successfully, but these errors were encountered:
Hi, first of all thank you for sharing your great job. I am trying to use a modified version of your code in order to train on a custom dataset with a different number of keypoints. After 5 epochs as you have done in your example. I have modified the code in order to use a different number of keypoints (6 keypoints): ClassDataset and the evaluation code (kpt_oks_sigmas for 6 keypoints).
I obtain a model that gets a good detection of the object (bounding box) but the keypoints are not well located. For example:
This images show that the detection is getting trained but the keypoints are not. Moreover at the evaluation phase I always get values equal to zero:
IoU metric: keypoints
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets= 20 ] = 0.000
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets= 20 ] = 0.000
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets= 20 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.000
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = -1.000
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 20 ] = 0.000
Average Recall (AR) @[ IoU=0.50 | area= all | maxDets= 20 ] = 0.000
Average Recall (AR) @[ IoU=0.75 | area= all | maxDets= 20 ] = 0.000
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.000
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = -1.000
I have revised the dataset and it seems well annotated, so I don't know where the errors are. Any idea? Thank you in advance.
The text was updated successfully, but these errors were encountered: