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data_common.py
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#!/usr/bin/python3
# -*- coding: utf-8 -*-
# Author: xurongzhong#126.com wechat:pythontesting qq:37391319
# CreateDate: 2018-1-8
# data_common.py
import os
import shutil
import traceback
import time
from pathlib import Path
import glob
import hashlib
import re
import collections
import pandas
maps = {
1: ("白天-室内-正常光-非走动-720的7人间的中间位置", "白天-室内-正常光"),
2: ("白天-室内-正常光-非走动-路演区第4排(低)中间位置", "白天-室内-正常光"),
3: ("白天-室内-正常光-非走动-海翔通往荔园路的楼下通道门口", "白天-室内-正常光"),
4: ("白天-室内-正常光-非走动-701健身区域", "白天-室内-正常光"),
5: ("白天-室内-正常光-非走动-电梯间内", "白天-室内-正常光"),
6: ("白天-室内-正常光-走动-七楼楼道", "白天-室内-正常光"),
7: ("白天-室内-正常光-走动-717办公室", "白天-室内-正常光"),
8: ("白天-室内-正常光-动作-平躺", "白天-室内-正常光"),
9: ("白天-室内-正常光-动作-侧躺", "白天-室内-正常光"),
10: ("白天-室内-暗光-非走动-720办公室4人间关灯后", "白天-室内-暗光"),
11: ("白天-室内-逆光-非走动-路演区窗口逆光", "白天-室内-逆光"),
12: ("白天-室内-逆光-非走动-717办公室过道顶灯光", "白天-室内-逆光"),
13: ("白天-室内-逆光-非走动-厕所头顶灯光", "白天-室内-逆光"),
14: ("白天-室内-逆光-非走动-701健身区域", "白天-室内-逆光"),
15: ("白天-室内-逆光-走动-路演区窗口逆光", "白天-室内-逆光"),
16: ("白天-室内-逆光-走动-717办公室过道顶灯光", "白天-室内-逆光"),
17: ("白天-室内-逆光-走动-厕所头顶灯光", "白天-室内-逆光"),
18: ("白天-室外-正常光-非走动-海翔楼下空旷处(品骏快递)(背阴处正常光)",
"白天-室外-正常光"),
19: ("白天-室外-正常光-非走动-荔园路树荫下", "白天-室外-正常光"),
20: ("白天-室外-正常光-走动-海翔楼下空旷处(品骏快递)(背阴处正常光)",
"白天-室外-正常光"),
21: ("白天-室外-正常光-走动-荔园路树荫下", "白天-室外-正常光"),
22: ("白天-室外-逆光-非走动-海翔楼下空旷处 (品骏快递)(建议中午左右)(背对太阳)",
"白天-室外-逆光"),
23: ("白天-室外-逆光-非走动-荔园路树荫下(建议中午左右)(背对太阳)",
"白天-室外-逆光"),
24: ("白天-室外-逆光-非走动-(阴天)海翔通往荔园路的楼下通道门口(人物背对门口)",
"白天-室外-逆光"),
25: ("白天-室外-逆光-非走动-(阴天)手机朝上,背朝天空", "白天-室外-逆光"),
26: ("白天-室外-逆光-走动-海翔楼下空旷处(品骏快递)(建议中午左右)(背对太阳)",
"白天-室外-逆光"),
27: ("白天-室外-逆光-走动-荔园路树荫下(建议中午左右)(背对太阳)",
"白天-室外-逆光"),
28: ("白天-室外-逆光-走动-(阴天)手机朝上,背朝天空", "白天-室外-逆光"),
29: ("白天-室外-强光-非走动-海翔楼下空旷处(建议中午左右)(面对太阳)",
"白天-室外-强光"),
30: ("白天-室外-强光-非走动-荔园路树荫下(面对太阳)", "白天-室外-强光"),
31: ("白天-室外-强光-走动-海翔楼下空旷处(建议中午左右)(面对太阳)",
"白天-室外-强光"),
32: ("白天-室外-强光-走动-荔园路树荫下(面对太阳)", "白天-室外-强光"),
33: ("白天-室内-正常光-表情", "白天-室内-正常光-表情"),
34: ("白天-室内-正常光-不戴眼镜注册,戴近视眼镜认证", "白天-室内-正常光-脸"),
35: ("白天-室内-正常光-不戴眼镜注册,戴墨镜认证", "白天-室内-正常光-脸"),
36: ("白天-室内-正常光-戴近视眼镜注册,不戴眼镜认证", "白天-室内-正常光-脸"),
37: ("白天-室内-正常光-戴近视眼镜注册,戴墨镜认证", "白天-室内-正常光-脸"),
38: ("晚上-室内-正常光-夜晚路演区沙发位置", "晚上室内正常光"),
39: ("晚上-室内-正常光-七楼过道", "晚上室内正常光"),
40: ("晚上-室内-正常光-701健身区域", "晚上室内正常光"),
41: ("晚上-室内-正常光-平躺(路演区域沙发位置)", "晚上室内正常光"),
42: ("晚上-室内-正常光-侧躺(路演区域沙发位置)", "晚上室内正常光"),
43: ("晚上-室内-暗光-夜晚路演区沙发位置(19:00左右关灯)", "晚上室内暗光"),
44: ("晚上-室内-暗光-7楼710的客梯间(关灯后)", "晚上室内暗光"),
45: ("晚上-室内-暗光-720的4人间关灯后", "晚上室内暗光"),
46: ("晚上-室内-暗光-平躺(720的4人间关灯后)", "晚上室内暗光"),
47: ("晚上-室内-暗光-侧躺(720的4人间关灯后)", "晚上室内暗光"),
48: ("晚上-室外-暗光-海翔楼下空旷处(品骏快递)(人物背景无灯光)",
"晚上室外暗光"),
49: ("晚上-室外-暗光-海翔楼下上坡处路灯下(广州银行)", "晚上室外暗光"),
50: ("晚上-室外-强光-海翔楼下上坡处路灯下(广州银行)(面朝路灯)",
"晚上室外强光"),
}
def count(datas, values):
'''
生成统计的用例
'''
total_number = compare_number = live_number = success_number = \
test_number = 0
print(datas)
for row in datas:
print(row)
num, case_name, total, compare, live, success, test, r1, r2, r3 = row
if num in values:
total_number += total
compare_number += compare
live_number += live
success_number += success
test_number += test
return ["====", maps[values[0]][0], total_number, compare_number,
live_number, success_number, test_number,
percentage(compare_number, total_number),
percentage(live_number, total_number),
percentage(success_number, test_number)]
def file2html(name):
result = ''
for line in open(name):
result += line + "<br>"
return result
def percentage(number1, number2):
value = 0 if number2 == 0 else float(number1) / number2
value = 0 if not value else "{0:.5f}%".format(value * 100)
return value
def produce_xls(results, output, number, type_=0):
if type_ ==0:
tag = old_tag = None
values = []
title = ["用例编号", "测试用例", "重试总次数", "比对成功次数", "活体成功次数",
"成功次数", "测试次数", "比对通过率", "活体通过率", "用户通过率"]
else:
title = ["用例编号", "重试总次数", "比对成功次数", "活体成功次数",
"睁闭眼通过次数","成功次数", "测试次数", "比对通过率", "活体通过率",
"用户通过率", "睁闭眼通过率"]
datas = [title, ]
for i in range(1, number + 1):
total_number = compare_number = live_number = eye_number = \
success_number = test_number = 0
if type_ ==0:
old_tag = tag
tag = maps[i][1]
# 用例标签与上一用例不一致时,需要对前面用例进行汇总
if (old_tag is not None) and values and old_tag != tag:
datas.append(count(datas, values))
values = []
values.append(i)
# 没有数据的生成空表,有数据则统计
if i not in results:
if type_ ==0:
datas.append([i, maps[i][1], 0, 0, 0, 0, 0, 0, 0, 0, ])
else:
datas.append([i, 0, 0, 0, 0, 0, 0, 0, 0, 0,0])
else:
for row in results[i]:
if type_ == 0:
print(row)
total, compare, live, success, test = row
else:
total, compare, live, eye, success, test = row
total_number += total
compare_number += compare
live_number += live
success_number += success
test_number += test
if type_ != 0:
eye_number += eye
if type_ == 0:
result = [i, maps[i][0], total_number, compare_number,
live_number,success_number, test_number]
else:
result = [i, total_number, compare_number, live_number,
eye_number, success_number, test_number,]
result.append(percentage(compare_number, total_number))
result.append(percentage(live_number, total_number))
result.append(percentage(success_number, test_number))
if type_ != 0:
result.append(percentage(eye_number, total_number))
datas.append(result)
# 最后的用例需要进行汇总
if type_ ==0:
if i == len(maps):
datas.append(count(datas, values))
values = []
try:
writer = pandas.ExcelWriter(output)
df = pandas.DataFrame(datas)
df.to_excel(writer, sheet_name='output', index=False)
writer.save()
except IOError:
print("please close the output file!")
def check_directory(name):
if Path(name).exists():
print("{0} Exists,Now Delete it!".format(name))
try:
shutil.rmtree(name)
time.sleep(0.5)
except Exception as info:
print('Error: shutil.rmtree {}'.format(name))
print(info)
traceback.print_exc()
print('Please close file and directories and continue...')
print("mkdir {0} .".format(name))
Path(name).mkdir(parents=True, exist_ok=True)
def get_labels(files, real):
labels = []
for file_ in files:
if real in file_:
labels.append(1)
else:
labels.append(0)
return labels
def get_filelistandlabel(src, real, filetype="ir",file_name='output/files.txt',
label_name='output/label.txt'):
types = filetype.split(",")
# print(src)
if len(types)>1:
filetype = types[0]
# print(src, filetype)
files = find_files_by_type(src,filetype)
# print(files)
files.sort()
if len(types)==2:
files2 = find_files_by_type(src,types[1])
files2.sort()
files = concat_list(files, files2, sep=' ')
labels = get_labels(files, real)
output_file(file_name, files)
output_file(label_name, labels)
def find_files_by_type(src, filetype="ir"):
p = Path(src)
#print(str(p))
files = []
for file_name in p.glob('**/*.{0}'.format(filetype)):
files.append(str(file_name))
return files
def copy_files_by_types(src, dst, types="csv,py",
directories=None, one_directory=True):
'''
拷贝指定扩展名的文件从源目录src到目的目录dst。
directories: 是否指定目录,多个目录用逗号分隔。
one_directory:是否拷贝到一个目录,选择为False会建立目录层次。
示例:
copy_files_by_types(r"d:\tmp", r"d:\tmp2", types="csv,py",
directories=None, one_directory=False)
copy_files_by_types(r"d:\tmp", r"d:\tmp2", types="csv,py,pdf",
one_directory=False, directories="back,test")
'''
check_directory(dst)
p = Path(src)
for file_ext in types.split(','):
for file_name in p.glob('**/*.{0}'.format(file_ext)):
# print(file_name)
if directories is not None:
flag = False
for directory in directories.split(','):
if os.sep + directory + os.sep in str(file_name):
flag = True
if not flag:
continue
if not one_directory:
dirname = str(file_name.parent).replace(src, dst)
dst_filename = "{}{}{}".format(
dirname, os.sep, file_name.name)
if not Path(dirname).exists():
print("mkdir {}".format(dirname))
Path(dirname).mkdir(parents=True, exist_ok=True)
else:
dst_filename = "{}{}{}".format(
dst, os.sep, Path(file_name).name)
print("Copying {} to {}".format(file_name, dst_filename))
shutil.copyfile(str(file_name), dst_filename)
def count_number_by_filetypes(directory, file_types, output=False):
'''
统计用户目录directory的用例目录下的指定类型文件的个数。
可以指定多种文件类型。
output为True时会在屏幕输出。
比如:count_number_by_filetypes(r'd:\tmp3',"jpg,pdf", output=True)
'''
datas = {}
for file_ext in file_types.split(','):
datas[file_ext] = count_number_by_filetype(directory, file_ext, output)
return datas
def count_number_by_filetype(directory, file_type, output=False):
'''
统计用户目录directory的用例目录下的指定类型文件的个数。
output为True时会在屏幕输出。
比如:count_number_by_filetypes(r'd:\tmp3',"jpg", output=True)
'''
datas = {}
dirs = glob.glob("{0}/*/".format(directory))
if output:
print('\n', file_type, ':\n')
for dir_ in (dirs):
files = glob.glob("{0}/*.{1}".format(dir_, file_type))
datas[int(dir_.split(os.sep)[-2].lstrip('0'))] = len(files)
for seq in range(1,len(maps) + 1):
if seq not in datas:
datas[seq] = 0
if output:
print(datas[seq])
return datas
def concat_excel(files, usecols=None, index_col=None, strips={}):
all_data_frames = []
for file_name in files:
df = pandas.read_excel(file_name, index_col=index_col, usecols=usecols)
all_data_frames.append(df)
df = pandas.concat(all_data_frames, ignore_index=True)
if strips:
for item in strips:
df[item] = df[item].str.replace(strips[item], "")
return df
def file2dict(filename, change=False, multi=False, basename=False, sep='\s'):
result = {}
for line in open(filename):
if line.strip():
if change:
value, key = line.split(sep)
else:
key, value = line.split(sep)
key = key.strip()
value = value.strip()
if basename:
key = os.path.basename(key)
if multi:
if key not in result:
result[key] = []
result[key].append(value)
else:
result[key] = value
return result
def file2dict1(filename, value=-1, basename=False):
'''
输入文件只有一列,从该列提取一个字段做key。
'''
result = collections.OrderedDict()
for line in open(filename):
item = line.strip()
if not item:
continue
key = item.split('/')[value]
if basename:
item = os.path.basename(item)
result[key] = item
return result
def get_md5(content, is_file=False):
if is_file:
return hashlib.md5(open(content,'rb').read()).hexdigest()
else:
return hashlib.md5(content).hexdigest()
def merge_excel(df1, df2, key,fixes=None,columns=None,sorts=None):
"""
key: 能区分行的列名
fixes: 不需要相加的列,默认为None
columns: 需要输出的列,默认为None,输出所有列
sorts: 排序
"""
df1.fillna(method='ffill',inplace=True)
df2.fillna(method='ffill',inplace=True)
columns1 = set(df1.columns)
columns2 = set(df2.columns)
for item in columns2 - columns1:
df1[item] = 0
for item in columns1 - columns2:
df2[item] = 0
key1 = list(df1[key])
key2 = list(df2[key])
df = df1.iloc[0:0]
for item in set(key1)|set(key2):
if item in set(key1)&set(key2):
value = df1.iloc[key1.index(item)] + df2.iloc[key2.index(item)]
value[key] = df1.iloc[key1.index(item)][key]
for name in fixes:
value[name] = df1.iloc[key1.index(item)][name]
elif item in set(df1[key]):
value = df1.iloc[key1.index(item)]
else:
value = df2.iloc[key2.index(item)]
df = pandas.concat([df, value.to_frame().T])
if sorts:
df = df.sort_values(by=sorts)
if sorts:
df = df.loc[:,columns]
return df
def output_file(name, items):
'''输出列表为文本文件'''
f = open(name,'w')
for item in items:
f.write("{}\n".format(item))
f.close()
def get_filename(items):
'''将列名中的文件字符串只保留文件名'''
return [ os.path.basename(x.strip()) for x in items]
def get_filename_without_ext(items, full=False):
'''将列名中的文件字符串只保留文件名'''
if full:
return [ os.path.splitext(x.strip())[0] for x in items]
else:
return [ os.path.basename(x.strip()).split('.')[0] for x in items]
def get_shuangtong_photos(diretory):
results = {}
base_human = r'{}{}human_test'.format(diretory, os.sep)
base_paper = r'{}{}paper'.format(diretory, os.sep)
base_noface = r'{}{}noface'.format(diretory, os.sep)
human_photos = get_filename(glob.glob('{}{}*.*'.format(base_human,os.sep)))
human_photos = get_filename(human_photos)
paper_photos = get_filename(glob.glob('{}{}*.*'.format(base_paper,os.sep)))
paper_photos = get_filename(paper_photos)
noface_photos = get_filename(glob.glob('{}{}*.*'.format(base_noface,os.sep)))
noface_photos = get_filename(noface_photos)
results['human_test'] = human_photos
results['paper'] = paper_photos
results['noface'] = noface_photos
return results
def get_bj_results(filename,return_dict=False):
names=['name','left','top','length','height','v','score']
df = pandas.read_csv(filename, names=names, sep='\s', engine='python')
rename = lambda x: os.path.basename(x)
df['name'] = df['name'].apply(rename)
if return_dict:
results = {}
for num in range(len(df)):
row = df.iloc[num]
results[row['name']] = (
row['left'],row['top'],row['left'] + row['length'],
row['top'] + row['height'])
return results
else:
return df
def rename_shuangtong(name):
names = name.split('/')
if 'noface' in name:
filename = "double/{}/{}".format(names[-2],names[-1])
else:
filename = "{}{}/{}".format(
"20180228_双通人脸检测_zhourong/Image/33941/双通活体检测全集数据/",
names[-2],names[-1])
return filename
def get_sz_shuangtong_results(
filenames,shuangtong_photos, output_file=False,
out_filename="/home/andrew/code/detection_results.txt"):
print(filenames)
cols = [0,3,6]
df_paper = pandas.read_excel(filenames['paper'],usecols=cols)
df_human = pandas.read_excel(filenames['human_test'],usecols=cols)
#df_noface = pandas.read_excel(filenames['noface'],usecols=cols)
df = pandas.concat([df_paper, df_human])
df['图片的路径'] = df['图片的路径'].apply(rename_shuangtong)
print(df["人脸检测时间"].mean())
if output_file:
# 生成北京需要的测试结果
detection_results = ""
for num in range(len(df)):
row = df.iloc[num]
name = row['图片的路径']
result = row['测试结果']
# left, top, right, bottom
#if os.path.basename(name) in shuangtong_photos['noface']:
#if result != '未检测到人脸':
#detection_result = "{0}\n".format(name)
##detection_results = detection_results + detection_result
#else:
#print("Error: Find face in {}".format(os.path.basename(name)))
#else:
if result != '未检测到人脸':
sore = float(result.split(':')[-1].strip())
temps = result.split('[')
left, top = temps[1].strip(']').split(',')
right, bottom = temps[2].split(']')[0].split(',')
detection_result = "{0} {1} {2} {3} {4} 1 {5} \n".format(
name,left, top, int(right) - int(left), int(bottom) - int(top), sore)
detection_results = detection_results + detection_result
else:
detection_result = "{0}\n".format(name)
#detection_results = detection_results + detection_result
f = open(out_filename, 'wb')
f.write(detection_results.encode(encoding='utf_8', errors='strict'))
f.close()
else:
return df
def get_result_filelist(directoy):
'''获取深圳的XLS结果文件列表'''
p = Path(directoy)
files = p.glob('**/*.{0}'.format("xls"))
xls_files = {}
for filename in files:
version = re.search('v\d+\.\d+\.\d+',str(filename)).group()
if version not in xls_files:
xls_files[version] = {}
if "双通" in str(filename):
if "paper" in str(filename):
xls_files[version]['paper'] = str(filename)
elif "human" in str(filename):
xls_files[version]['human_test'] = str(filename)
else:
xls_files[version]['noface'] = str(filename)
else:
xls_files[version]['tongyong'] = str(filename)
return xls_files
def file2list(filename,basename=False):
result = []
for line in open(filename):
item = line.strip()
if item:
if basename:
item = os.path.basename(item)
result.append(item)
return result
def concat_list(list1, list2, sep=','):
result = []
for i in range(len(list1)):
try:
result.append("{}{}{}".format(list1[i], sep, list2[i]))
except Exception as info:
print('Error: concat_list')
print(i)
print(len(list1), len(list2))
#print(list1)
#print(list2)
if len(list1) > i:
print(list1[i])
else:
print(list2[i])
print(info)
traceback.print_exc()
continue
return result
def concat_file(file1, file2, sep=','):
list1 = file2list(file1)
list2 = file2list(file2)
result = concat_list(list1, list2, sep)
return result
def check_pair_file(src, type1, type2, flag=False):
print("directory: {}".format(src))
files1 = find_files_by_type(src, type1)
print("{}: {}".format(type1, len(files1)))
files1_name = get_filename_without_ext(files1, full=True)
files2 = find_files_by_type(src, type2)
print("{}: {}".format(type2, len(files2)))
files2_name = get_filename_without_ext(files2, full=True)
print(set(files1_name)^set(files2_name))
for name in set(files1_name)^set(files2_name):
#print(name)
if name in files1_name:
location = files1[files1_name.index(name)]
else:
location = files2[files2_name.index(name)]
print(location)
if flag:
print("--remove {}".format(location))
os.remove(location)
def get_leaf_directories(input_directory):
results = set()
for root, dirs, files in os.walk(input_directory):
if files:
results.add(root)
return results
def get_compare_reulst(files, server_file, key, out, server_columns, output_columns):
'''
data_common.get_compare_reulst(['_little_photo.xls','_little_real.xls'],
'liveness_little.csv', '活体分数', 'dataframe.xlsx',
["server_score", "filename", "depth_file_name"],
['活体分数','server_score','diff_score'])
data_common.get_compare_reulst('verify.xls',
server_result_file, '最高相似度',
'dataframe.xlsx',
["server_score", "name","filename"],
['最高相似度','server_score','diff_score'])
data_common.get_compare_reulst(['gaze.xls', 'no_gaze.xls'],
server_result_path + '\gaze_little.csv', '注视分数',
'dataframe.xlsx',
["server_score", "filename"],
['注视分数','server_score','diff_score'])
'''
if type(files) is list:
df = concat_excel(files)
else:
df = pandas.read_excel(files)
df.index = df[u'识别图片的路径'].apply(
lambda x:os.path.basename(x.split()[0]))
df_server = pandas.read_csv(server_file, sep='\s', names=server_columns)
df_server.index = df_server['filename'].apply(
lambda x:os.path.basename(x.split()[0]))
print(df.index)
print(df_server.index)
df['server_score'] = df_server['server_score']
df['diff_score'] = df['server_score'] - df[key]
df.to_excel(out, columns=output_columns)
if __name__ == '__main__':
src = '/home/andrew/code/data/tof/vivo3D_batch_test/liveness/demo_1.7.5_test'
files = find_files_by_type(src)
print(files)