time.sleep(3)
servers.wait_until_stop('sample')
time.sleep(3)
new_result = "{0}{1}{2}-result.csv".format(directory, os.sep, version)
print(result)
print(new_result)
shutil.copyfile(result, new_result)
error_name = "{0}{1}{2}----result.xlsx".format(directory, os.sep, version)
if options.test_type == 'detect':
# 生成图片
names = data_common.file2list(result, basename=True)
data_common.output_file('/home/andrew/code/tmp/detection_results.txt',
names)
subprocess.call(
"cd /home/andrew/code/tmp/facedet-profile && rm -rf cache",
shell=True)
subprocess.check_output(
"cd /home/andrew/code/tmp/facedet-profile && python3 get_roc.py > {}/log.txt"
.format(directory),
shell=True)
print("copyinig")
src = "/home/andrew/code/tmp/facedet-profile/roc.png"
dst = "{}/{}-roc.png".format(directory, version)
time.sleep(0.5)
shutil.copyfile(src, dst)
if options.test_type != 'verify':
values = "{0}{1}{2}-values.csv".format(directory, os.sep, version)
process = []
queue = multiprocessing.Queue()
results = multiprocessing.Manager().list()
lock = multiprocessing.Lock()
if multiprocessing.cpu_count() < 3:
number = multiprocessing.cpu_count()
else:
number = multiprocessing.cpu_count() - 1
# Launch the consumer process
for i in range(number):
t = multiprocessing.Process(target=consumer,
args=(queue, results, lock))
t.daemon = True
process.append(t)
for i in range(number):
process[i].start()
for item in df['ir']:
queue.put(item)
for i in range(number):
queue.put(None)
for i in range(number):
process[i].join()
data_common.output_file("output.txt", results)
# wait for result
if not options.w:
exit(0)
# anlyse result
result = "{0}{1}{2}{1}{2}_output%files.txt.csv".format(
tool, os.sep, options.test_type)
servers.wait_until_stop(types[options.test_type]['process'])
new_result = "{0}{1}{2}-result.csv".format(directory, os.sep, version)
shutil.copyfile(result, new_result)
if options.test_type != 'verify':
values = "{0}{1}{2}-values.csv".format(directory, os.sep, version)
maps = data_common.concat_file(new_result, file_name, sep=',')
data_common.output_file(values, maps)
if options.test_type == 'liveness':
new_result_ = "{0}{1}{2}-result_.csv".format(directory, os.sep, version)
shutil.copyfile(result, new_result_)
cmd = "sed -i 's#-1#1#' {}".format(new_result_)
subprocess.call(cmd,shell=True)
if options.data_type == 'base':
replace = '/home/andrew/code/data/tof/base_test_data/vivo-liveness/'
else:
replace = ''
error_name = "{0}{1}{2}-result.xlsx".format(directory, os.sep, version)
servers.get_liveness_server_result(new_result, file_name, label_name,
replace=replace, error_name=error_name)
#!/usr/bin/python3
# -*- coding: utf-8 -*-
# Author: xurongzhong#126.com
# CreateDate: 2018-3-31
import os
import argparse
from pathlib import Path
import data_common
parser = argparse.ArgumentParser()
parser.add_argument('file1', action="store")
parser.add_argument('file2', action='store', help='测试类型')
parser.add_argument('-s', action='store', dest='sep', default=' ',
help='分隔符')
parser.add_argument('--version', action='version',
version='%(prog)s 1.0 Rongzhong xu 2018 03 31')
options = parser.parse_args()
new = data_common.concat_file(options.file1,options.file2,options.sep)
data_common.output_file(options.file1, new)
results = []
poses = []
for filename in files:
d = json.load(open(filename))
name = d['image']['rawFilename'].strip('.jpg')
pos = d['objects']['face'][0]['position']
num = len(d['objects']['face'])
if num > 1:
print(filename)
print(name)
pprint.pprint(d['objects']['face'])
out = "# {}\n{}\n3 640 480 1\n0\n{}\n".format(i, name, num)
for face in d['objects']['face']:
pos = face['position']
top = round(pos['top'])
bottom = round(pos['bottom'])
left = round(pos['left'])
right = round(pos['right'])
out = out + "1 {} {} {} {}\n".format(left, top, right, bottom)
poses.append("{},{},{},{},{},{},{}".format(name, left, top, right,
bottom, right - left,
bottom - top))
i = i + 1
#print(out)
file_list.append(name)
results.append(out.rstrip('\n'))
data_common.output_file("files.txt", file_list)
data_common.output_file("results.txt", results)
data_common.output_file("poses.txt", poses)
if options.type_name == 'android':
print('In android')
df = pd.read_excel(options.filename,
usecols=[0, 4],
names=['name', 'result'])
rename = lambda x: os.path.basename(x)
df['name'] = df['name'].apply(rename)
print(df.head())
for num in range(len(df)):
row = df.iloc[num]
result = row['result']
if result != '未检测到人脸':
temps = result.split('[')
left, top, = temps[1].strip(']').split(',')
right, bottom = temps[2].strip(']').split(',')
out = "# {}\n{}\n3 640 480 1\n0\n1\n".format(i, row['name'])
out = out + "1 {} {} {} {}\n".format(left, top, right, bottom)
detection_result = "{0} {1} {2} {3} {4} 1 {5}".format(
row['name'], left, top,
int(right) - int(left),
int(bottom) - int(top), 0.99)
i = i + 1
#print(out)
file_list.append(row['name'])
results.append(out.rstrip('\n'))
detection_results.append(detection_result)
data_common.output_file("files.txt", file_list)
data_common.output_file("gt.txt", results)
data_common.output_file("dt.txt", detection_results)
