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- import argparse
- from PAPC.train import train
-
- parser = argparse.ArgumentParser(description='PAPC Initialization')
- parser.add_argument('--model_name', type=str, default='pointnet_basic', help='The name of model, such as pointnet, pointnet2 and so on')
- parser.add_argument('--mode', type=str, default='clas', help='"clas", "seg" or "detect"')
- parser.add_argument('--max_point', type=int, default=1024, help='How many points in a sample during training')
- parser.add_argument('--num_classes', type=int, default=16, help='How many classes in classification during training')
- parser.add_argument('--num_parts', type=int, default=50, help='How many classes in segmentation during training')
- parser.add_argument('--learning_rate', type=float, default=0.001, help='Learning rate')
- parser.add_argument('--weight_decay', type=float, default=0.001, help='Weight decay')
- parser.add_argument('--epoch_num', type=int, default=10, help='epoch for training')
- parser.add_argument('--batchsize', type=int, default=32, help='Mini batch size of one gpu or cpu')
- parser.add_argument('--info_iter', type=int, default=40, help='How many iters to info measurement during training')
- parser.add_argument('--save_iter', type=int, default=2, help='How many iters to save a model snapshot once during training')
- parser.add_argument('--path', type=str, default='./dataset/', help='The directory for finding dataset')
-
- args = parser.parse_args()
-
- if __name__ == '__main__':
- train(args.model_name,
- args.mode,
- args.max_point,
- args.num_classes,
- args.num_parts,
- args.learning_rate,
- args.weight_decay,
- args.epoch_num,
- args.batchsize,
- args.info_iter,
- args.save_iter,
- args.path)
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