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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-04-27 17:57:07 +02:00
parent 469dede6d1
commit a9108a296b
1 changed files with 6 additions and 6 deletions
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train.py
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@ -64,9 +64,9 @@ def train(
torch.backends.cudnn.benchmark = True # unsuitable for multiscale torch.backends.cudnn.benchmark = True # unsuitable for multiscale
# Configure run # Configure run
data_cfg = parse_data_cfg(data_cfg) data_dict = parse_data_cfg(data_cfg)
train_path = data_cfg['train'] train_path = data_dict['train']
nc = int(data_cfg['classes']) # number of classes nc = int(data_dict['classes']) # number of classes
# Initialize model # Initialize model
model = Darknet(cfg, img_size).to(device) model = Darknet(cfg, img_size).to(device)
@ -276,12 +276,12 @@ def print_mutation(hyp, results):
if __name__ == '__main__': if __name__ == '__main__':
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument('--epochs', type=int, default=273, help='number of epochs') parser.add_argument('--epochs', type=int, default=273, help='number of epochs')
parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch') parser.add_argument('--batch-size', type=int, default=4, help='size of each image batch')
parser.add_argument('--accumulate', type=int, default=1, help='accumulate gradient x batches before optimizing') parser.add_argument('--accumulate', type=int, default=1, help='accumulate gradient x batches before optimizing')
parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path') parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
parser.add_argument('--data-cfg', type=str, default='data/coco.data', help='coco.data file path') parser.add_argument('--data-cfg', type=str, default='data/coco_10img.data', help='coco.data file path')
parser.add_argument('--multi-scale', action='store_true', help='random image sizes per batch 320 - 608') parser.add_argument('--multi-scale', action='store_true', help='random image sizes per batch 320 - 608')
parser.add_argument('--img-size', type=int, default=416, help='pixels') parser.add_argument('--img-size', type=int, default=320, help='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=2, help='number of Pytorch DataLoader workers') parser.add_argument('--num-workers', type=int, default=2, help='number of Pytorch DataLoader workers')