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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-12-13 12:27:52 -08:00
parent 1bb738c83f
commit 074a9250d8
1 changed files with 6 additions and 2 deletions
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8
utils/datasets.py
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@ -320,7 +320,7 @@ class LoadImagesAndLabels(Dataset): # for training/testing
extract_bounding_boxes = False extract_bounding_boxes = False
create_datasubset = False create_datasubset = False
pbar = tqdm(self.label_files, desc='Caching labels') pbar = tqdm(self.label_files, desc='Caching labels')
nm, nf, ne, ns = 0, 0, 0, 0 # number missing, number found, number empty, number datasubset nm, nf, ne, ns, nd = 0, 0, 0, 0, 0 # number missing, found, empty, datasubset, duplicate
for i, file in enumerate(pbar): for i, file in enumerate(pbar):
try: try:
with open(file, 'r') as f: with open(file, 'r') as f:
@ -333,6 +333,9 @@ class LoadImagesAndLabels(Dataset): # for training/testing
assert l.shape[1] == 5, '> 5 label columns: %s' % file assert l.shape[1] == 5, '> 5 label columns: %s' % file
assert (l >= 0).all(), 'negative labels: %s' % file assert (l >= 0).all(), 'negative labels: %s' % file
assert (l[:, 1:] <= 1).all(), 'non-normalized or out of bounds coordinate labels: %s' % file assert (l[:, 1:] <= 1).all(), 'non-normalized or out of bounds coordinate labels: %s' % file
if np.unique(l, axis=0).shape[0] < l.shape[0]: # duplicate rows
nd += 1 # print('WARNING: duplicate rows in %s' % self.label_files[i]) # duplicate rows
self.labels[i] = l self.labels[i] = l
nf += 1 # file found nf += 1 # file found
@ -370,7 +373,8 @@ class LoadImagesAndLabels(Dataset): # for training/testing
ne += 1 # print('empty labels for image %s' % self.img_files[i]) # file empty ne += 1 # print('empty labels for image %s' % self.img_files[i]) # file empty
# os.system("rm '%s' '%s'" % (self.img_files[i], self.label_files[i])) # remove # os.system("rm '%s' '%s'" % (self.img_files[i], self.label_files[i])) # remove
pbar.desc = 'Caching labels (%g found, %g missing, %g empty for %g images)' % (nf, nm, ne, n) pbar.desc = 'Caching labels (%g found, %g missing, %g empty, %g duplicate, for %g images)' % (
nf, nm, ne, nd, n)
assert nf > 0, 'No labels found. Recommend correcting image and label paths.' assert nf > 0, 'No labels found. Recommend correcting image and label paths.'
# Cache images into memory for faster training (WARNING: Large datasets may exceed system RAM) # Cache images into memory for faster training (WARNING: Large datasets may exceed system RAM)