# 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 paddle.fluid as fluid from paddle.fluid.dygraph.parallel import ParallelEnv from paddleseg.datasets import DATASETS import paddleseg.transforms as T from paddleseg.cvlibs import manager from paddleseg.utils import get_environ_info from paddleseg.core import infer def parse_args(): parser = argparse.ArgumentParser(description='Model training') # params of model parser.add_argument( '--model_name', dest='model_name', help='Model type for testing, which is one of {}'.format( str(list(manager.MODELS.components_dict.keys()))), type=str, default='UNet') # params of infer parser.add_argument( '--dataset', dest='dataset', help="The dataset you want to test, which is one of {}".format( str(list(DATASETS.keys()))), type=str, default='OpticDiscSeg') parser.add_argument( '--dataset_root', dest='dataset_root', help="dataset root directory", type=str, default=None) # params of prediction parser.add_argument( "--input_size", dest="input_size", help="The image size for net inputs.", nargs=2, default=[512, 512], type=int) parser.add_argument( '--batch_size', dest='batch_size', help='Mini batch size', type=int, default=2) parser.add_argument( '--model_dir', dest='model_dir', help='The path of model for evaluation', type=str, default=None) parser.add_argument( '--save_dir', dest='save_dir', help='The directory for saving the inference results', type=str, default='./output/result') return parser.parse_args() def main(args): env_info = get_environ_info() places = fluid.CUDAPlace(ParallelEnv().dev_id) \ if env_info['Paddle compiled with cuda'] and env_info['GPUs used'] \ else fluid.CPUPlace() if args.dataset not in DATASETS: raise Exception('`--dataset` is invalid. it should be one of {}'.format( str(list(DATASETS.keys())))) dataset = DATASETS[args.dataset] with fluid.dygraph.guard(places): test_transforms = T.Compose([T.Resize(args.input_size), T.Normalize()]) test_dataset = dataset( dataset_root=args.dataset_root, transforms=test_transforms, mode='test') model = manager.MODELS[args.model_name]( num_classes=test_dataset.num_classes) infer( model, model_dir=args.model_dir, test_dataset=test_dataset, save_dir=args.save_dir) if __name__ == '__main__': args = parse_args() main(args)