updates
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6
train.py
6
train.py
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@ -307,11 +307,11 @@ def print_mutation(hyp, results):
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if __name__ == '__main__':
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser = argparse.ArgumentParser()
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parser.add_argument('--epochs', type=int, default=68, help='number of epochs')
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parser.add_argument('--epochs', type=int, default=68, help='number of epochs')
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parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch')
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parser.add_argument('--batch-size', type=int, default=8, help='size of each image batch')
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parser.add_argument('--accumulate', type=int, default=4, help='accumulate gradient x batches before optimizing')
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parser.add_argument('--accumulate', type=int, default=8, help='accumulate gradient x batches before optimizing')
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parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
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parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
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parser.add_argument('--data-cfg', type=str, default='data/coco_64img.data', help='coco.data file path')
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parser.add_argument('--data-cfg', type=str, default='data/coco_64img.data', help='coco.data file path')
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parser.add_argument('--multi-scale', action='store_false', help='random image sizes per batch 320 - 608')
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parser.add_argument('--multi-scale', action='store_true', help='random image sizes per batch 320 - 608')
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parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
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parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
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parser.add_argument('--resume', action='store_true', help='resume training flag')
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parser.add_argument('--resume', action='store_true', help='resume training flag')
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parser.add_argument('--transfer', action='store_true', help='transfer learning flag')
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parser.add_argument('--transfer', action='store_true', help='transfer learning flag')
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