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Updated filename attributes for YOLOv5 Hub results (#2708)

Proposed fix for 'Model predict with forward will fail if PIL image does not have filename attribute' #2702
5.0
Glenn Jocher GitHub 3 years ago
parent
commit
74276d5189
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1 changed files with 5 additions and 5 deletions
  1. +5
    -5
      models/common.py

+ 5
- 5
models/common.py View File

@@ -254,12 +254,12 @@ class autoShape(nn.Module):
n, imgs = (len(imgs), imgs) if isinstance(imgs, list) else (1, [imgs]) # number of images, list of images
shape0, shape1, files = [], [], [] # image and inference shapes, filenames
for i, im in enumerate(imgs):
f = f'image{i}' # filename
if isinstance(im, str): # filename or uri
im, f = Image.open(requests.get(im, stream=True).raw if im.startswith('http') else im), im # open
im.filename = f # for uri
files.append(Path(im.filename).with_suffix('.jpg').name if isinstance(im, Image.Image) else f'image{i}.jpg')
if not isinstance(im, np.ndarray):
im = np.asarray(im) # to numpy
im, f = np.asarray(Image.open(requests.get(im, stream=True).raw if im.startswith('http') else im)), im
elif isinstance(im, Image.Image): # PIL Image
im, f = np.asarray(im), getattr(im, 'filename', f)
files.append(Path(f).with_suffix('.jpg').name)
if im.shape[0] < 5: # image in CHW
im = im.transpose((1, 2, 0)) # reverse dataloader .transpose(2, 0, 1)
im = im[:, :, :3] if im.ndim == 3 else np.tile(im[:, :, None], 3) # enforce 3ch input

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