# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import sys import os import argparse import deploy def arg_parser(): parser = argparse.ArgumentParser() parser.add_argument( "--model_dir", "-m", type=str, default=None, help="path to openvino model .xml file") parser.add_argument( "--img", "-i", type=str, default=None, help="path to an image files") parser.add_argument( "--img_list", "-l", type=str, default=None, help="Path to a imglist") parser.add_argument( "--cfg_file", "-c", type=str, default=None, help="Path to PaddelX model yml file") parser.add_argument( "--thread_num", "-t", type=int, default=1, help="Path to PaddelX model yml file") parser.add_argument( "--input_shape", "-ip", type=str, default=None, help=" image input shape of model [NCHW] like [1,3,224,244] ") return parser def main(): parser = arg_parser() args = parser.parse_args() model_nb = args.model_dir model_yaml = args.cfg_file thread_num = args.thread_num input_shape = args.input_shape input_shape = input_shape[1:-1].split(",", 3) shape = list(map(int, input_shape)) #model init predictor = deploy.Predictor(model_nb, model_yaml, thread_num, shape) #predict if (args.img_list != None): f = open(args.img_list) lines = f.readlines() for im_path in lines: print(im_path) predictor.predict(im_path.strip('\n')) f.close() else: im_path = args.img predictor.predict(im_path) if __name__ == "__main__": main()