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ultralytics 8.0.65 YOLOv8 Pose models (#1347)

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This commit is contained in:
Ayush Chaurasia
2023-04-06 03:55:32 +05:30
committed by GitHub
parent 9af3e69b1a
commit 1cb92d7f42
57 changed files with 1578 additions and 489 deletions
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7
ultralytics/yolo/v8/segment/val.py
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@ -65,7 +65,7 @@ class SegmentationValidator(DetectionValidator):
if npr == 0:
if nl:
self.stats.append((correct_masks, correct_bboxes, *torch.zeros(
self.stats.append((correct_bboxes, correct_masks, *torch.zeros(
(2, 0), device=self.device), cls.squeeze(-1)))
if self.args.plots:
self.confusion_matrix.process_batch(detections=None, labels=cls.squeeze(-1))
@ -103,7 +103,7 @@ class SegmentationValidator(DetectionValidator):
self.confusion_matrix.process_batch(predn, labelsn)
# Append correct_masks, correct_boxes, pconf, pcls, tcls
self.stats.append((correct_masks, correct_bboxes, pred[:, 4], pred[:, 5], cls.squeeze(-1)))
self.stats.append((correct_bboxes, correct_masks, pred[:, 4], pred[:, 5], cls.squeeze(-1)))
pred_masks = torch.as_tensor(pred_masks, dtype=torch.uint8)
if self.args.plots and self.batch_i < 3:
@ -220,8 +220,7 @@ class SegmentationValidator(DetectionValidator):
pred = anno.loadRes(str(pred_json)) # init predictions api (must pass string, not Path)
for i, eval in enumerate([COCOeval(anno, pred, 'bbox'), COCOeval(anno, pred, 'segm')]):
if self.is_coco:
eval.params.imgIds = [int(Path(x).stem)
for x in self.dataloader.dataset.im_files] # images to eval
eval.params.imgIds = [int(Path(x).stem) for x in self.dataloader.dataset.im_files] # im to eval
eval.evaluate()
eval.accumulate()
eval.summarize()