rm some file

deploy/raspberry/python/convertor.py

-import os
-from six import text_type as _text_type
-import argparse
-import sys
-from utils import logging 
-import paddlex as pdx
-
-def arg_parser():
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "--model_dir",
-        "-m",
-        type=_text_type,
-        default=None,
-        help="define model directory path")
-    parser.add_argument(
-        "--save_dir",
-        "-s",
-        type=_text_type,
-        default=None,
-        help="path to save inference model")
-    parser.add_argument(
-        "--fixed_input_shape",
-        "-fs",
-        default=None,
-        help="export openvino model with  input shape:[h,w]")
-    return parser
-
-
-    
-
-
-def export_openvino_model(model, args):
-    if model.model_type == "detector" or model.__class__.__name__ == "FastSCNN":
-        logging.error(
-            "Only image classifier models and semantic segmentation models(except FastSCNN) are supported to export to openvino")
-    try:
-        import x2paddle
-        if x2paddle.__version__ < '0.7.4':
-            logging.error("You need to upgrade x2paddle >= 0.7.4")
-    except:
-        logging.error(
-            "You need to install x2paddle first, pip install x2paddle>=0.7.4")
-        
-    from x2paddle.op_mapper.paddle_op_mapper import PaddleOpMapper
-    mapper = PaddleOpMapper()
-    mapper.convert(model.test_prog, args.save_dir)
-
-    import mo.main as mo
-    from mo.utils.cli_parser import get_onnx_cli_parser
-    onnx_parser = get_onnx_cli_parser()
-    onnx_parser.add_argument("--model_dir",type=_text_type)
-    onnx_parser.add_argument("--save_dir",type=_text_type)
-    onnx_parser.add_argument("--fixed_input_shape")
-    onnx_input = os.path.join(args.save_dir, 'x2paddle_model.onnx')
-    onnx_parser.set_defaults(input_model=onnx_input)
-    onnx_parser.set_defaults(output_dir=args.save_dir)
-    shape = '[1,3,'
-    shape =  shape + args.fixed_input_shape[1:]
-    onnx_parser.set_defaults(input_shape = shape)
-    mo.main(onnx_parser,'onnx')
-
-
-def main():
-    parser = arg_parser()
-    args = parser.parse_args()
-    assert args.model_dir is not None, "--model_dir should be defined while exporting openvino model"
-    assert args.save_dir is not None, "--save_dir should be defined to create openvino model"
-    model = pdx.load_model(args.model_dir)
-    if model.status == "Normal" or model.status == "Prune":
-        logging.error(
-            "Only support inference model, try to export model first as below,",
-            exit=False)
-    export_openvino_model(model, args)
-
-if  __name__ == "__main__":
-    main()
-
-