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)