Bienqq
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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-06-21 10:24:06 +02:00
parent 7d7d7a6332
commit a7e21b4315
1 changed files with 2 additions and 2 deletions
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train.py
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@ -208,7 +208,7 @@ def train(
# Multi-Scale training # Multi-Scale training
if multi_scale: if multi_scale:
if ((i + 1) / accumulate + nb * epoch) % 10 == 0: #  adjust (67% - 150%) every 10 batches if (i + 1 + nb * epoch) / accumulate % 10 == 0: #  adjust (67% - 150%) every 10 batches
img_size = random.choice(range(img_size_min, img_size_max + 1)) * 32 img_size = random.choice(range(img_size_min, img_size_max + 1)) * 32
print('img_size = %g' % img_size) print('img_size = %g' % img_size)
scale_factor = img_size / max(imgs.shape[-2:]) scale_factor = img_size / max(imgs.shape[-2:])
@ -318,7 +318,7 @@ if __name__ == '__main__':
parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)') parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
parser.add_argument('--resume', action='store_true', help='resume training flag') parser.add_argument('--resume', action='store_true', help='resume training flag')
parser.add_argument('--transfer', action='store_true', help='transfer learning flag') parser.add_argument('--transfer', action='store_true', help='transfer learning flag')
parser.add_argument('--num-workers', type=int, default=4, help='number of Pytorch DataLoader workers') parser.add_argument('--num-workers', type=int, default=0, help='number of Pytorch DataLoader workers')
parser.add_argument('--dist-url', default='tcp://127.0.0.1:9999', type=str, help='distributed training init method') parser.add_argument('--dist-url', default='tcp://127.0.0.1:9999', type=str, help='distributed training init method')
parser.add_argument('--rank', default=0, type=int, help='distributed training node rank') parser.add_argument('--rank', default=0, type=int, help='distributed training node rank')
parser.add_argument('--world-size', default=1, type=int, help='number of nodes for distributed training') parser.add_argument('--world-size', default=1, type=int, help='number of nodes for distributed training')