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@gkioxari
in this line, it ignore the 0-index. i think if use the pascal_voc_2012 for training, the class list shoud be ('jumping', 'phoning', 'playinginstrument', 'reading', 'ridingbike', 'ridinghorse', 'running', 'takingphoto', 'usingcomputer', 'walking', 'other').
So num_classes in this line is 11. if it ignores the 0-index, which means ignore 'jumping' class when applying mean subtraction and stds division. I think the column 0 in variable targets means the class_id: 0 for jumping, 1 for phoning ... 10 means other. Does 0 also means backgroud ? I find both background and jumping will use 0 for class-index in the column 0 of variable targets. Is that right?
I find this line creates an zero array, the colomn 0 of the variable targets means either groundtruth label is 0, or IOU is below threshold. so after this methon returns, we can not tell what does 0 means. should I change it from
targets = np.zeros((rois.shape[0], 5), dtype=np.float32) to
targets = np.zeros((rois.shape[0], 5), dtype=np.float32)
targets[:,0] = -1
Do I miss something important?
Would you give some explanations in details ? Thank you very much~
The text was updated successfully, but these errors were encountered:
@gkioxari
in this line, it ignore the 0-index. i think if use the pascal_voc_2012 for training, the class list shoud be ('jumping', 'phoning', 'playinginstrument', 'reading', 'ridingbike', 'ridinghorse', 'running', 'takingphoto', 'usingcomputer', 'walking', 'other').
So num_classes in this line is 11. if it ignores the 0-index, which means ignore 'jumping' class when applying mean subtraction and stds division. I think the column 0 in variable targets means the class_id: 0 for jumping, 1 for phoning ... 10 means other. Does 0 also means backgroud ? I find both background and jumping will use 0 for class-index in the column 0 of variable targets. Is that right?
I find this line creates an zero array, the colomn 0 of the variable targets means either groundtruth label is 0, or IOU is below threshold. so after this methon returns, we can not tell what does 0 means. should I change it from
targets = np.zeros((rois.shape[0], 5), dtype=np.float32) to
targets = np.zeros((rois.shape[0], 5), dtype=np.float32)
targets[:,0] = -1
Do I miss something important?
Would you give some explanations in details ? Thank you very much~
The text was updated successfully, but these errors were encountered: