人脸识别对比

一、接口服务

#!/usr/bin/env python
# coding=utf-8

"""
@author: shenzh
@contact: shenzh@yutong.com
@file: person_face_compare_api.py
@date: 2022-4-18 8:54
@desc: 根据输入两张图片进行比较判断是否是同一个人
"""

import json

from flask import Flask, request

import uuid
from concurrent.futures import ThreadPoolExecutor
import face_compare_config as config
import shutil
import comparePersonFace

executor = ThreadPoolExecutor()

app = Flask(__name__)


# 只接受POST方法访问
@app.route("/face_compare", methods=["POST"])
def face_compare_method():
    return_dict = {'return_code': '200', 'return_info': 'success', 'result': False}
    # 判断入参是否为空
    if request.get_data() is None:
        return_dict['return_code'] = '5004'
        return_dict['return_info'] = '请求参数为空'
        return json.dumps(return_dict, ensure_ascii=False)
    # 获取传入的参数
    try:
        image_file_datas = request.get_data()
        # print("读取的图片：", image_file)

        image_file_datas_1 = json.loads(image_file_datas)
        face_image_1_base64 = image_file_datas_1.get(config.face_image_1)  ##face_image_1 = 'face_image_1'

        face_image_2_base64 = image_file_datas_1.get(config.face_image_2)  ##face_image_2 = 'face_image_2'

        image_1_path = get_file_as_img(face_image_1_base64)
        image_2_path = get_file_as_img(face_image_2_base64)
    except Exception as e:
        return_dict['return_code'] = '5000'
        return_dict['return_info'] = '请求参数获取失败:' + str(e)
        return json.dumps(return_dict, ensure_ascii=False)
    face_compare_result = executor.submit(comparePersonFace.face_compare_method, image_1_path, image_2_path)
    face_compare_result = face_compare_result.result()
    return_dict['result'] = face_compare_result  ##1：不是同一个人，0：是同一个人

    # print("删除的图片=",image_path)
    shutil.rmtree(image_1_path)
    shutil.rmtree(image_2_path)

    print("返回的结果=", return_dict)

    return json.dumps(return_dict, ensure_ascii=False)


def get_file_as_img(image_file):
    path = str(uuid.uuid4()) + ".jpg"
    with open(path, 'wb') as f:
        f.write(image_file)
    return path


if __name__ == "__main__":
    app.run(host='0.0.0.0', port=face_port, debug=True)

二、对比的方法

##coding=utf-8
import face_recognition
from PIL import Image

def detect_faces_in_image(file_stream1, file_stream2):
    code1 = face_recognition.face_encodings(face_recognition.load_image_file(file_stream1))[0]
    code2 = face_recognition.face_encodings(face_recognition.load_image_file(file_stream2))[0]

    if len(code1) > 0 and len(code2) > 0:
        match_results = face_recognition.face_distance([code1], code2)
        print(match_results)
        # print(match_results[0])
        if match_results[0] > 0.6:
            result = "不是同一个人"
        else:
            result = "同一个人"
        return result


def face_compare_method(file_stream1, file_stream2):
    code1 = face_recognition.face_encodings(face_recognition.load_image_file(file_stream1))[0]
    code2 = face_recognition.face_encodings(face_recognition.load_image_file(file_stream2))[0]

    if len(code1) > 0 and len(code2) > 0:
        match_results = face_recognition.compare_faces([code1], code2)
        print(match_results)
        if match_results[0] == False:
            result = "1"##不是同一个人
        else:
            result = "0"##同一个人
        return result


def face_location_method(file_stream1):
    image = face_recognition.load_image_file(file_stream1)
    face_locations = face_recognition.face_locations(image, number_of_times_to_upsample=0, model="cnn")

    print("I found {} face(s) in this photograph.".format(len(face_locations)))

    for face_location in face_locations:
        # Print the location of each face in this image
        top, right, bottom, left = face_location
        print("A face is located at pixel location Top: {}, Left: {}, Bottom: {}, Right: {}".format(top, left, bottom,
                                                                                                    right))

        # You can access the actual face itself like this:
        face_image = image[top:bottom, left:right]
        pil_image = Image.fromarray(face_image)
        pil_image.show()