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scale_img() update

This commit is contained in:
Glenn Jocher 2020-04-07 12:51:52 -07:00
parent 1a3c77df95
commit 68f58f4dec
1 changed files with 8 additions and 6 deletions
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14
utils/torch_utils.py
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@ -115,14 +115,16 @@ def load_classifier(name='resnet101', n=2):
return model
def scale_img(img, r=1.0): # img(16,3,256,416), r=ratio
# scales a batch of pytorch images while retaining same input shape (cropped or grey-padded)
def scale_img(img, ratio=1.0, same_shape=True): # img(16,3,256,416), r=ratio
# scales img(bs,3,y,x) by ratio
h, w = img.shape[2:]
s = (int(h * r), int(w * r)) # new size
p = h - s[0], w - s[1] # pad/crop pixels
s = (int(h * ratio), int(w * ratio)) # new size
img = F.interpolate(img, size=s, mode='bilinear', align_corners=False) # resize
return F.pad(img, [0, p[1], 0, p[0]], value=0.5) if r < 1.0 else img[:, :, :p[0], :p[1]] # pad/crop
# cv2.imwrite('scaled.jpg', np.array(img[0].permute((1, 2, 0)) * 255.0))
if not same_shape: # pad/crop img
p = h - s[0], w - s[1]
p = [int(math.fmod(x, 64)) for x in p] # pad to 64 grid size
img = F.pad(img, [0, p[1], 0, p[0]], value=0.447) # value = imagenet mean
return img
class ModelEMA: