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100 lines
3.8 KiB
100 lines
3.8 KiB
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. |
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# |
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# Licensed under the Apache License, Version 2.0 (the "License"); |
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# you may not use this file except in compliance with the License. |
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# You may obtain a copy of the License at |
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# |
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# http://www.apache.org/licenses/LICENSE-2.0 |
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# |
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# Unless required by applicable law or agreed to in writing, software |
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# distributed under the License is distributed on an "AS IS" BASIS, |
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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# See the License for the specific language governing permissions and |
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# limitations under the License. |
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''' |
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@File Description: |
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# 统计json文件images信息，生成统计结果csv，同时生成图像shape、图像shape比例的二维分布图 |
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python ./coco_tools/json_ImgSta.py \ |
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--json_path=./annotations/instances_val2017.json \ |
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--csv_path=./img_sta/images.csv \ |
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--png_shape_path=./img_sta/images_shape.png \ |
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--png_shapeRate_path=./img_sta/images_shapeRate.png |
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''' |
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import json |
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import argparse |
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import os.path |
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import pandas as pd |
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import seaborn as sns |
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import matplotlib.pyplot as plt |
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def check_dir(check_path,show=True): |
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if os.path.isdir(check_path): |
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check_directory = check_path |
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else: |
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check_directory = os.path.dirname(check_path) |
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if not os.path.exists(check_directory): |
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os.makedirs(check_directory) |
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if show: |
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print('make dir:',check_directory) |
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def js_img_sta(js_path, csv_path, png_shape_path, png_shapeRate_path, image_keyname): |
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print('json read...\n') |
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with open(js_path, 'r') as load_f: |
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data = json.load(load_f) |
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df_img = pd.DataFrame(data[image_keyname]) |
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if png_shape_path is not None: |
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check_dir(png_shape_path) |
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sns.jointplot('height', 'width', data=df_img, kind='hex') |
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plt.savefig(png_shape_path) |
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plt.close() |
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print('png save to', png_shape_path) |
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if png_shapeRate_path is not None: |
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check_dir(png_shapeRate_path) |
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df_img['shape_rate'] = (df_img['width'] / df_img['height']).round(1) |
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df_img['shape_rate'].value_counts().sort_index().plot(kind='bar', title='images shape rate') |
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plt.savefig(png_shapeRate_path) |
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plt.close() |
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print('png save to', png_shapeRate_path) |
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if csv_path is not None: |
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check_dir(csv_path) |
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df_img.to_csv(csv_path) |
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print('csv save to', csv_path) |
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def get_args(): |
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parser = argparse.ArgumentParser(description='Json Images Infomation Statistic') |
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# parameters |
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parser.add_argument('--json_path', type=str, |
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help='json path to statistic images information') |
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parser.add_argument('--csv_path', type=str, default=None, |
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help='csv path to save statistic images information, default None, do not save') |
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parser.add_argument('--png_shape_path', type=str, default=None, |
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help='png path to save statistic images shape information, default None, do not save') |
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parser.add_argument('--png_shapeRate_path', type=str, default=None, |
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help='png path to save statistic images shape rate information, default None, do not save') |
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parser.add_argument('--image_keyname', type=str, default='images', |
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help='image key name in json, default images') |
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parser.add_argument('-Args_show', '--Args_show', type=bool, default=True, |
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help='Args_show(default: True), if True, show args info') |
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args = parser.parse_args() |
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if args.Args_show: |
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print('Args'.center(100, '-')) |
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for k, v in vars(args).items(): |
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print('%s = %s' % (k, v)) |
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print() |
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return args |
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if __name__ == '__main__': |
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args = get_args() |
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js_img_sta(args.json_path, args.csv_path, args.png_shape_path, args.png_shapeRate_path, args.image_keyname) |
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