# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve. # #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. """ Contains common utility functions. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import sys import distutils.util import numpy as np import six from collections import deque from paddle.fluid import core import argparse import functools from config import * def print_arguments(args): """Print argparse's arguments. Usage: .. code-block:: python parser = argparse.ArgumentParser() parser.add_argument("name", default="Jonh", type=str, help="User name.") args = parser.parse_args() print_arguments(args) :param args: Input argparse.Namespace for printing. :type args: argparse.Namespace """ print("----------- Configuration Arguments -----------") for arg, value in sorted(six.iteritems(vars(args))): print("%s: %s" % (arg, value)) print("------------------------------------------------") def add_arguments(argname, type, default, help, argparser, **kwargs): """Add argparse's argument. Usage: .. code-block:: python parser = argparse.ArgumentParser() add_argument("name", str, "Jonh", "User name.", parser) args = parser.parse_args() """ type = distutils.util.strtobool if type == bool else type argparser.add_argument( "--" + argname, default=default, type=type, help=help + ' Default: %(default)s.', **kwargs) class SmoothedValue(object): """Track a series of values and provide access to smoothed values over a window or the global series average. """ def __init__(self): self.loss_sum = 0.0 self.iter_cnt = 0 def add_value(self, value): self.loss_sum += np.mean(value) self.iter_cnt += 1 def get_mean_value(self): return self.loss_sum / self.iter_cnt def parse_args(): """return all args """ parser = argparse.ArgumentParser(description=__doc__) add_arg = functools.partial(add_arguments, argparser=parser) # yapf: disable # ENV add_arg('parallel', bool, True, "Whether use parallel.") add_arg('use_gpu', bool, True, "Whether use GPU.") add_arg('model_cfg_path', str, 'config/yolov3.cfg', "YOLO model config file path.") add_arg('model_save_dir', str, 'checkpoints', "The path to save model.") add_arg('pretrain', str, 'weights/darknet53', "The pretrain model path.") add_arg('weights', str, 'weights/yolov3', "The weights path.") add_arg('dataset', str, 'coco2017', "Dataset: coco2014, coco2017.") add_arg('class_num', int, 80, "Class number.") add_arg('data_dir', str, 'dataset/coco', "The data root path.") add_arg('use_pyreader', bool, True, "Use pyreader.") add_arg('use_profile', bool, False, "Whether use profiler.") add_arg('start_iter', int, 0, "Start iteration.") add_arg('use_multiprocess', bool, True, "add multiprocess.") #SOLVER add_arg('batch_size', int, 64, "Learning rate.") add_arg('learning_rate', float, 0.001, "Learning rate.") add_arg('max_iter', int, 500200, "Iter number.") add_arg('snapshot_iter', int, 2000, "Save model every snapshot stride.") add_arg('label_smooth', bool, True, "Use label smooth in class label.") add_arg('no_mixup_iter', int, 40000, "Disable mixup in last N iter.") # TRAIN TEST INFER add_arg('input_size', int, 608, "Image input size of YOLOv3.") add_arg('random_shape', bool, True, "Resize to random shape for train reader.") add_arg('valid_thresh', float, 0.005, "Valid confidence score for NMS.") add_arg('nms_thresh', float, 0.45, "NMS threshold.") add_arg('nms_topk', int, 400, "The number of boxes to perform NMS.") add_arg('nms_posk', int, 100, "The number of boxes of NMS output.") add_arg('debug', bool, False, "Debug mode") # SINGLE EVAL AND DRAW add_arg('image_path', str, 'image', "The image path used to inference and visualize.") add_arg('image_name', str, None, "The single image used to inference and visualize. None to inference all images in image_path") add_arg('draw_thresh', float, 0.5, "Confidence score threshold to draw prediction box in image in debug mode") # yapf: enable args = parser.parse_args() file_name = sys.argv[0] merge_cfg_from_args(args) return args