# 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 __future__ import absolute_import from __future__ import division from __future__ import print_function import os import sys # add python path of PadleDetection to sys.path parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2))) sys.path.insert(0, parent_path) # ignore warning log import warnings warnings.filterwarnings('ignore') import glob import paddle from ppdet.core.workspace import load_config, merge_config from ppdet.engine import Trainer from ppdet.utils.check import check_gpu, check_npu, check_xpu, check_version, check_config from ppdet.utils.cli import ArgsParser, merge_args from ppdet.slim import build_slim_model from ppdet.utils.logger import setup_logger logger = setup_logger('train') def parse_args(): parser = ArgsParser() parser.add_argument( "--infer_dir", type=str, default=None, help="Directory for images to perform inference on.") parser.add_argument( "--infer_img", type=str, default=None, help="Image path, has higher priority over --infer_dir") parser.add_argument( "--output_dir", type=str, default="output", help="Directory for storing the output visualization files.") parser.add_argument( "--draw_threshold", type=float, default=0.5, help="Threshold to reserve the result for visualization.") parser.add_argument( "--slim_config", default=None, type=str, help="Configuration file of slim method.") parser.add_argument( "--use_vdl", type=bool, default=False, help="Whether to record the data to VisualDL.") parser.add_argument( '--vdl_log_dir', type=str, default="vdl_log_dir/image", help='VisualDL logging directory for image.') parser.add_argument( "--save_results", type=bool, default=False, help="Whether to save inference results to output_dir.") parser.add_argument( "--slice_infer", action='store_true', help="Whether to slice the image and merge the inference results for small object detection." ) parser.add_argument( '--slice_size', nargs='+', type=int, default=[640, 640], help="Height of the sliced image.") parser.add_argument( "--overlap_ratio", nargs='+', type=float, default=[0.25, 0.25], help="Overlap height ratio of the sliced image.") parser.add_argument( "--combine_method", type=str, default='nms', help="Combine method of the sliced images' detection results, choose in ['nms', 'nmm', 'concat']." ) parser.add_argument( "--match_threshold", type=float, default=0.6, help="Combine method matching threshold.") parser.add_argument( "--match_metric", type=str, default='iou', help="Combine method matching metric, choose in ['iou', 'ios'].") args = parser.parse_args() return args def get_test_images(infer_dir, infer_img): """ Get image path list in TEST mode """ assert infer_img is not None or infer_dir is not None, \ "--infer_img or --infer_dir should be set" assert infer_img is None or os.path.isfile(infer_img), \ "{} is not a file".format(infer_img) assert infer_dir is None or os.path.isdir(infer_dir), \ "{} is not a directory".format(infer_dir) # infer_img has a higher priority if infer_img and os.path.isfile(infer_img): return [infer_img] images = set() infer_dir = os.path.abspath(infer_dir) assert os.path.isdir(infer_dir), \ "infer_dir {} is not a directory".format(infer_dir) exts = ['jpg', 'jpeg', 'png', 'bmp'] exts += [ext.upper() for ext in exts] for ext in exts: images.update(glob.glob('{}/*.{}'.format(infer_dir, ext))) images = list(images) assert len(images) > 0, "no image found in {}".format(infer_dir) logger.info("Found {} inference images in total.".format(len(images))) return images def run(FLAGS, cfg): # build trainer trainer = Trainer(cfg, mode='test') # load weights trainer.load_weights(cfg.weights) # get inference images images = get_test_images(FLAGS.infer_dir, FLAGS.infer_img) # inference if FLAGS.slice_infer: trainer.slice_predict( images, slice_size=FLAGS.slice_size, overlap_ratio=FLAGS.overlap_ratio, combine_method=FLAGS.combine_method, match_threshold=FLAGS.match_threshold, match_metric=FLAGS.match_metric, draw_threshold=FLAGS.draw_threshold, output_dir=FLAGS.output_dir, save_results=FLAGS.save_results) else: trainer.predict( images, draw_threshold=FLAGS.draw_threshold, output_dir=FLAGS.output_dir, save_results=FLAGS.save_results) def main(): FLAGS = parse_args() cfg = load_config(FLAGS.config) merge_args(cfg, FLAGS) merge_config(FLAGS.opt) # disable npu in config by default if 'use_npu' not in cfg: cfg.use_npu = False # disable xpu in config by default if 'use_xpu' not in cfg: cfg.use_xpu = False if cfg.use_gpu: place = paddle.set_device('gpu') elif cfg.use_npu: place = paddle.set_device('npu') elif cfg.use_xpu: place = paddle.set_device('xpu') else: place = paddle.set_device('cpu') if FLAGS.slim_config: cfg = build_slim_model(cfg, FLAGS.slim_config, mode='test') check_config(cfg) check_gpu(cfg.use_gpu) check_npu(cfg.use_npu) check_xpu(cfg.use_xpu) check_version() run(FLAGS, cfg) if __name__ == '__main__': main()