amd
/

ONNX
PyTorch
English
RyzenAI
super resolution
SISR
File size: 1,048 Bytes
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import argparse
parser = argparse.ArgumentParser(description='SESR')

# ipu test or cpu, you need to provide onnx path 
parser.add_argument('--ipu', action='store_true',
                    help='use ipu')
parser.add_argument('--onnx_path', type=str, default='SESR_int8.onnx',
                    help='onnx path')
parser.add_argument('--provider_config', type=str, default=None,
                    help='provider config path')
# Data specifications, you can use default
parser.add_argument('--dir_data', type=str, default='dataset/',
                    help='dataset directory')
parser.add_argument('--data_test', type=str, default='Set5',
                    help='test dataset name')
parser.add_argument('--n_threads', type=int, default=6,
                    help='number of threads for data loading')
parser.add_argument('--scale', type=str, default='2',
                    help='super resolution scale')
args = parser.parse_args()
args.scale = list(map(lambda x: int(x), args.scale.split('+')))
args.data_test = args.data_test.split('+')