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# 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 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('height', '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',
'--Args_show',
type=bool,
default=True,
help='Args_show(default: True), if True, show args info')
args = parser.parse_args()
if args.Args_show:
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)