zjc
/
yolov5
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

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

Avoid potential issues with deterministic ops. 

[ ] - verify for identical mAP to master
This commit is contained in:
Glenn Jocher 2022-06-18 13:54:55 +02:00 committed by GitHub
parent d6051382f1
commit 669f707d62
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
val.py
View File

@ -77,7 +77,7 @@ def process_batch(detections, labels, iouv):
Returns:
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])
correct_class = labels[:, 0:1] == detections[:, 5]
for i in range(len(iouv)):
@ -90,7 +90,7 @@ def process_batch(detections, labels, iouv):
# matches = matches[matches[:, 2].argsort()[::-1]]
matches = matches[np.unique(matches[:, 0], return_index=True)[1]]
correct[matches[:, 1].astype(int), i] = True
return correct
return torch.tensor(correct, dtype=torch.bool, device=iouv.device)
@torch.no_grad()