# 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 argparse import os import paddle from paddleseg.cvlibs import manager, Config from paddleseg.utils import get_sys_env, logger, get_image_list from core import predict from datasets import tusimple def parse_args(): parser = argparse.ArgumentParser(description='Model prediction') # params of prediction parser.add_argument( "--config", dest="cfg", help="The config file.", default=None, type=str) parser.add_argument( '--model_path', dest='model_path', help='The path of model for prediction', type=str, default=None) parser.add_argument( '--image_path', dest='image_path', help='The path of image, it can be a file or a directory including images', type=str, default=None) parser.add_argument( '--save_dir', dest='save_dir', help='The directory for saving the predicted results', type=str, default='./output/result') # custom color map parser.add_argument( '--custom_color', dest='custom_color', nargs='+', help='Save images with a custom color map. Default: None, use paddleseg\'s default color map.', type=int, default=None) return parser.parse_args() def get_test_config(cfg, args): test_config = cfg.test_config if args.custom_color: test_config['custom_color'] = args.custom_color return test_config def main(args): env_info = get_sys_env() place = 'gpu' if env_info['Paddle compiled with cuda'] and env_info[ 'GPUs used'] else 'cpu' paddle.set_device(place) if not args.cfg: raise RuntimeError('No configuration file specified.') cfg = Config(args.cfg) cfg.check_sync_info() val_dataset = cfg.val_dataset if not val_dataset: raise RuntimeError( 'The verification dataset is not specified in the configuration file.' ) msg = '\n---------------Config Information---------------\n' msg += str(cfg) msg += '------------------------------------------------' logger.info(msg) model = cfg.model image_list, image_dir = get_image_list(args.image_path) logger.info('Number of predict images = {}'.format(len(image_list))) test_config = get_test_config(cfg, args) predict( model, model_path=args.model_path, val_dataset=val_dataset, image_list=image_list, image_dir=image_dir, save_dir=args.save_dir, **test_config) if __name__ == '__main__': args = parse_args() main(args)