# 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. from six import text_type as _text_type import argparse import sys import os.path as osp import paddlex.utils.logging as logging 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( "--version", "-v", action="store_true", default=False, help="get version of PaddleX") parser.add_argument( "--export_inference", "-e", action="store_true", default=False, help="export inference model for C++/Python deployment") parser.add_argument( "--export_onnx", "-eo", action="store_true", default=False, help="export onnx model for deployment") parser.add_argument( "--data_conversion", "-dc", action="store_true", default=False, help="convert the dataset to the standard format") parser.add_argument( "--source", "-se", type=_text_type, default=None, help="define dataset format before the conversion") parser.add_argument( "--to", "-to", type=_text_type, default=None, help="define dataset format after the conversion") parser.add_argument( "--pics", "-p", type=_text_type, default=None, help="define pictures directory path") parser.add_argument( "--annotations", "-a", type=_text_type, default=None, help="define annotations directory path") parser.add_argument( "--fixed_input_shape", "-fs", default=None, help="export inference model with fixed input shape:[w,h]") parser.add_argument( "--split_dataset", "-sd", action="store_true", default=False, help="split dataset with the split value") parser.add_argument( "--format", "-f", default=None, help="define dataset format(ImageNet/COCO/VOC/Seg)") parser.add_argument( "--dataset_dir", "-dd", type=_text_type, default=None, help="define the path of dataset to be splited") parser.add_argument( "--val_value", "-vv", default=None, help="define the value of validation dataset(E.g 0.2)") parser.add_argument( "--test_value", "-tv", default=None, help="define the value of test dataset(E.g 0.1)") return parser def main(): import os os.environ['CUDA_VISIBLE_DEVICES'] = "" import paddlex as pdx if len(sys.argv) < 2: print("Use command 'paddlex -h` to print the help information\n") return parser = arg_parser() args = parser.parse_args() if args.version: print("PaddleX-{}".format(pdx.__version__)) print("Repo: https://github.com/PaddlePaddle/PaddleX.git") print("Email: paddlex@baidu.com") return if args.export_inference: assert args.model_dir is not None, "--model_dir should be defined while exporting inference model" assert args.save_dir is not None, "--save_dir should be defined to save inference model" fixed_input_shape = None if args.fixed_input_shape is not None: fixed_input_shape = eval(args.fixed_input_shape) assert len( fixed_input_shape ) == 2, "len of fixed input shape must == 2, such as [224,224]" else: fixed_input_shape = None model = pdx.load_model(args.model_dir, fixed_input_shape) model.export_inference_model(args.save_dir) if args.export_onnx: assert args.model_dir is not None, "--model_dir should be defined while exporting onnx model" assert args.save_dir is not None, "--save_dir should be defined to create onnx 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) logging.error( "paddlex --export_inference --model_dir model_path --save_dir infer_model" ) pdx.convertor.export_onnx_model(model, args.save_dir) if args.data_conversion: assert args.source is not None, "--source should be defined while converting dataset" assert args.to is not None, "--to should be defined to confirm the taregt dataset format" assert args.pics is not None, "--pics should be defined to confirm the pictures path" assert args.annotations is not None, "--annotations should be defined to confirm the annotations path" assert args.save_dir is not None, "--save_dir should be defined to store taregt dataset" if args.source == 'labelme' and args.to == 'ImageNet': logging.error( "The labelme dataset can not convert to the ImageNet dataset.", exit=False) if args.source == 'jingling' and args.to == 'PascalVOC': logging.error( "The jingling dataset can not convert to the PascalVOC dataset.", exit=False) pdx.tools.convert.dataset_conversion(args.source, args.to, args.pics, args.annotations, args.save_dir) if args.split_dataset: assert args.dataset_dir is not None, "--dataset_dir should be defined while spliting dataset" assert args.form is not None, "--form should be defined while spliting dataset" assert args.val_value is not None, "--val_value should be defined while spliting dataset" dataset_dir = args.dataset_dir dataset_format = args.format.lower() val_value = float(args.val_value) test_value = float(args.test_value if args.test_value is not None else 0) save_dir = dataset_dir if not dataset_format in ["coco", "imagenet", "voc", "seg"]: logging.error( "The dataset format is not correct defined.(support COCO/ImageNet/VOC/Seg)" ) if not osp.exists(dataset_dir): logging.error("The path of dataset to be splited doesn't exist.") if val_value <= 0 or val_value >= 1 or test_value < 0 or test_value >= 1 or val_value + test_value >= 1: logging.error("The value of split is not correct.") pdx.tools.split.dataset_split(dataset_dir, dataset_format, val_value, test_value, save_dir) if __name__ == "__main__": main()