PaddleRS/tools/coco_tools/json_ImgSta.py

# Copyright (c) 2022 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.
"""
@File Description:
# 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
python ./coco_tools/json_ImgSta.py \
    --json_path=./annotations/instances_val2017.json \
    --csv_path=./img_sta/images.csv \
    --png_shape_path=./img_sta/images_shape.png \
    --png_shapeRate_path=./img_sta/images_shapeRate.png
"""

import json
import argparse
import os.path

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt


def check_dir(check_path, show=True):
    if os.path.isdir(check_path):
        check_directory = check_path
    else:
        check_directory = os.path.dirname(check_path)
    if len(check_directory) > 0 and not os.path.exists(check_directory):
        os.makedirs(check_directory)
        if show:
            print('make dir:', check_directory)


def js_img_sta(js_path, csv_path, png_shape_path, png_shapeRate_path,
               image_keyname):
    print('json read...\n')
    with open(js_path, 'r') as load_f:
        data = json.load(load_f)

    df_img = pd.DataFrame(data[image_keyname])

    if png_shape_path is not None:
        check_dir(png_shape_path)
        sns.jointplot(y='height', x='width', data=df_img, kind='hex')
        plt.savefig(png_shape_path)
        plt.close()
        print('png save to', png_shape_path)
    if png_shapeRate_path is not None:
        check_dir(png_shapeRate_path)
        df_img['shape_rate'] = (df_img['width'] / df_img['height']).round(1)
        df_img['shape_rate'].value_counts().sort_index().plot(
            kind='bar', title='images shape rate')
        plt.savefig(png_shapeRate_path)
        plt.close()
        print('png save to', png_shapeRate_path)

    if csv_path is not None:
        check_dir(csv_path)
        df_img.to_csv(csv_path)
        print('csv save to', csv_path)


def get_args():
    parser = argparse.ArgumentParser(
        description='Json Images Infomation Statistic')

    # Parameters
    parser.add_argument(
        '--json_path',
        type=str,
        help='json path to statistic images information')
    parser.add_argument(
        '--csv_path',
        type=str,
        default=None,
        help='csv path to save statistic images information, default None, do not save'
    )
    parser.add_argument(
        '--png_shape_path',
        type=str,
        default=None,
        help='png path to save statistic images shape information, default None, do not save'
    )
    parser.add_argument(
        '--png_shapeRate_path',
        type=str,
        default=None,
        help='png path to save statistic images shape rate information, default None, do not save'
    )
    parser.add_argument(
        '--image_keyname',
        type=str,
        default='images',
        help='image key name in json, default images')
    parser.add_argument(
        '--Args_show',
        type=str,
        default='True',
        help='Args_show(default: True), if True, show args info')

    args = parser.parse_args()

    if args.Args_show.lower() == 'true':
        print('Args'.center(100, '-'))
        for k, v in vars(args).items():
            print('%s = %s' % (k, v))
        print()
    return args


if __name__ == '__main__':
    args = get_args()
    js_img_sta(args.json_path, args.csv_path, args.png_shape_path,
               args.png_shapeRate_path, args.image_keyname)