`process_batch()` as numpy arrays (#8254)

Avoid potential issues with deterministic ops. 

[ ] - verify for identical mAP to master
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Glenn Jocher 2022-06-18 13:54:55 +02:00 committed by GitHub
parent d6051382f1
commit 669f707d62
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1 changed files with 2 additions and 2 deletions

4
val.py
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@ -77,7 +77,7 @@ def process_batch(detections, labels, iouv):
Returns: Returns:
correct (Array[N, 10]), for 10 IoU levels correct (Array[N, 10]), for 10 IoU levels
""" """
correct = torch.zeros(detections.shape[0], iouv.shape[0], dtype=torch.bool, device=iouv.device) correct = np.zeros((detections.shape[0], iouv.shape[0])).astype(bool)
iou = box_iou(labels[:, 1:], detections[:, :4]) iou = box_iou(labels[:, 1:], detections[:, :4])
correct_class = labels[:, 0:1] == detections[:, 5] correct_class = labels[:, 0:1] == detections[:, 5]
for i in range(len(iouv)): for i in range(len(iouv)):
@ -90,7 +90,7 @@ def process_batch(detections, labels, iouv):
# matches = matches[matches[:, 2].argsort()[::-1]] # matches = matches[matches[:, 2].argsort()[::-1]]
matches = matches[np.unique(matches[:, 0], return_index=True)[1]] matches = matches[np.unique(matches[:, 0], return_index=True)[1]]
correct[matches[:, 1].astype(int), i] = True correct[matches[:, 1].astype(int), i] = True
return correct return torch.tensor(correct, dtype=torch.bool, device=iouv.device)
@torch.no_grad() @torch.no_grad()