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Failing CUDA tests fixes (#4682)

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Glenn Jocher 2023-09-01 13:29:08 +02:00 committed by GitHub
parent 263bfd1e93
commit 2bc6e647c7
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4 changed files with 6 additions and 6 deletions
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2
tests/test_cuda.py
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@ -71,7 +71,7 @@ def test_predict_sam():
predictor = SAMPredictor(overrides=overrides)
# Set image
predictor.set_image('ultralytics/assets/zidane.jpg') # set with image file
predictor.set_image(ASSETS / 'zidane.jpg') # set with image file
# predictor(bboxes=[439, 437, 524, 709])
# predictor(points=[900, 370], labels=[1])

6
tests/test_python.py
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@ -140,11 +140,11 @@ def test_track_stream():
# Test Global Motion Compensation (GMC) methods
for gmc in 'orb', 'sift', 'ecc':
with open(ROOT / 'cfg/trackers/botsort.yaml') as f:
with open(ROOT / 'cfg/trackers/botsort.yaml', encoding='utf-8') as f:
data = yaml.safe_load(f)
tracker = TMP / f'botsort-{gmc}.yaml'
data['gmc_method'] = gmc
with open(tracker, 'w') as f:
with open(tracker, 'w', encoding='utf-8') as f:
yaml.safe_dump(data, f)
model.track('https://ultralytics.com/assets/decelera_portrait_min.mov', imgsz=160, tracker=tracker)
@ -166,7 +166,7 @@ def test_train_pretrained():
def test_export_torchscript():
f = YOLO(MODEL).export(format='torchscript', optimize=True)
f = YOLO(MODEL).export(format='torchscript', optimize=False)
YOLO(f)(SOURCE) # exported model inference

2
ultralytics/models/fastsam/predict.py
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@ -22,7 +22,7 @@ class FastSAMPredictor(DetectionPredictor):
max_det=self.args.max_det,
nc=len(self.model.names),
classes=self.args.classes)
full_box = torch.zeros(p[0].shape[1])
full_box = torch.zeros(p[0].shape[1], device=p[0].device)
full_box[2], full_box[3], full_box[4], full_box[6:] = img.shape[3], img.shape[2], 1.0, 1.0
full_box = full_box.view(1, -1)
critical_iou_index = bbox_iou(full_box[0][:4], p[0][:, :4], iou_thres=0.9, image_shape=img.shape[2:])

2
ultralytics/utils/__init__.py
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@ -311,7 +311,7 @@ def yaml_save(file='data.yaml', data=None, header=''):
data[k] = str(v)
# Dump data to file in YAML format
with open(file, 'w') as f:
with open(file, 'w', errors='ignore', encoding='utf-8') as f:
if header:
f.write(header)
yaml.safe_dump(data, f, sort_keys=False, allow_unicode=True)