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ultralytics 8.0.50 AMP check and YOLOv5u YAMLs (#1263)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Co-authored-by: Yonghye Kwon <developer.0hye@gmail.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
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This commit is contained in:
Glenn Jocher
2023-03-06 11:39:26 +01:00
committed by GitHub
parent 3861e6c82a
commit f0d8e4718b
29 changed files with 440 additions and 83 deletions
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17
tests/test_python.py
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@ -49,6 +49,8 @@ def test_predict_dir():
def test_predict_img():
model = YOLO(MODEL)
seg_model = YOLO('yolov8n-seg.pt')
cls_model = YOLO('yolov8n-cls.pt')
im = cv2.imread(str(SOURCE))
assert len(model(source=Image.open(SOURCE), save=True, verbose=True)) == 1 # PIL
assert len(model(source=im, save=True, save_txt=True)) == 1 # ndarray
@ -64,6 +66,18 @@ def test_predict_img():
np.zeros((320, 640, 3))] # numpy
assert len(model(batch)) == len(batch) # multiple sources in a batch
# Test tensor inference
im = cv2.imread(str(SOURCE)) # OpenCV
t = cv2.resize(im, (32, 32))
t = torch.from_numpy(t.transpose((2, 0, 1)))
t = torch.stack([t, t, t, t])
results = model(t)
assert len(results) == t.shape[0]
results = seg_model(t)
assert len(results) == t.shape[0]
results = cls_model(t)
assert len(results) == t.shape[0]
def test_predict_grey_and_4ch():
model = YOLO(MODEL)
@ -199,3 +213,6 @@ def test_result():
res = model(SOURCE)
res[0].plot()
print(res[0].path)
test_predict_img()