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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-08-06 01:27:27 +02:00
parent 77bde15239
commit 7462a95873
1 changed files with 3 additions and 3 deletions
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6
utils/datasets.py
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@ -93,7 +93,7 @@ class LoadImages: # for inference
# Read image # Read image
self.count += 1 self.count += 1
img0 = cv2.imread(path) # BGR img0 = cv2.imread(path) # BGR
assert img0 is not None, 'File Not Found ' + path assert img0 is not None, 'Image Not Found ' + path
print('image %g/%g %s: ' % (self.count, self.nF, path), end='') print('image %g/%g %s: ' % (self.count, self.nF, path), end='')
# Padded resize # Padded resize
@ -279,13 +279,13 @@ class LoadImagesAndLabels(Dataset): # for training/testing
img = self.imgs[index] img = self.imgs[index]
if img is None: if img is None:
img = cv2.imread(img_path) # BGR img = cv2.imread(img_path) # BGR
assert img is not None, 'File Not Found ' + img_path assert img is not None, 'Image Not Found ' + img_path
r = self.img_size / max(img.shape) # size ratio r = self.img_size / max(img.shape) # size ratio
if self.augment and r < 1: # if training (NOT testing), downsize to inference shape if self.augment and r < 1: # if training (NOT testing), downsize to inference shape
h, w, _ = img.shape h, w, _ = img.shape
img = cv2.resize(img, (int(w * r), int(h * r)), interpolation=cv2.INTER_LINEAR) # INTER_LINEAR fastest img = cv2.resize(img, (int(w * r), int(h * r)), interpolation=cv2.INTER_LINEAR) # INTER_LINEAR fastest
if self.n < 5000: # cache into memory if image count < 5000 if index < 5000: # cache first 5000 images into memory (~5GB)
self.imgs[index] = img self.imgs[index] = img
# Augment colorspace # Augment colorspace