大家知道我们的人脸识别已经在进行内测了，并会在不久的将来于EasyCVR及EasyGBS中进行测试。目前人脸识别AI是基于Python实现，在输入RTSP流的时候会直接开始识别人脸，并进行对比人脸的相似度，来判断是不是同一个人。大致实现如下：
代码语言：javascript复制face = my_face_recognition.my_face()
root_path = root '/image/test_images'
known_people_list = os.listdir(root_path)
index = 1
for i in known_people_list:
image_path = os.path.join(root_path, i)
image = face_recognition.load_image_file(image_path)
face.add_user(image, index, i.replace('.jpg', ''))
index = index 1
# path = root '/image/test.mp4'
path = 'rtsp://admin:a1234567@192.168.99.114:554/cam/realmonitor?channel=1&subtype=0'
face.face_search_from_video(path)
def face_search_from_video(self, video_path, model='hog'):
'''
从一段视频中逐帧进行人脸识别,并且保存,
:param video_path: 视频的路径
:param model:人脸检测的模型，默认为hog，可选为cnn
:return:
'''
fourcc = cv2.VideoWriter_fourcc(*'XVID')
input_video = cv2.VideoCapture(video_path)
ret, frame = input_video.read()
print("frame")
print(ret)
# 帧数为每秒20帧
out_video = cv2.VideoWriter(('RTSP' if video_path.find('rtsp') >= 0 else video_path.replace('.mp4', '')) '_result.avi', fourcc, 5,
(frame.shape[1], frame.shape[0]), True)
while ret:
timestamp = int(round(time.time() * 1000))
print("timestamp:%d", timestamp)
frame = self.face_serch_from_picture(frame, model=model, show_result=False)
cv2.imshow('frame', frame)
cv2.waitKey(1)
# out_video.write(frame)
ret, frame = input_video.read()以上方法是直接使用RTSP流来进行人脸识别，如果想要进行所有的语言都要识别人脸，最快的方法就是将人脸识别做成http接口用来调用，所以就要分离各个识别的方法。
具体思路先安装Python的http库：flask。安装方法：pip install flask。
下面是实现的http post接口及代码的实现：
1、先实现http接口
代码语言：javascript复制from flask import Flask, request, make_response, redirect, render_template
app = Flask(__name__)
if __name__ == "__main__":
app.run('0.0.0.0', port=PORT, threaded=False, debug=False)2、http实现人脸的录入，接口是以json的格式传入
代码语言：javascript复制@app.route('/add_user', methods=['POST']) # application/json
def add_user():
global idx
data = request.get_data()
body = {"success": False, "message": "no data or no json data"}
if not data:
return json.dumps(body, ensure_ascii=False)
data_json = json.loads(data)
if "image" not in data_json:
body["message"] = "empty image"
return json.dumps(body, ensure_ascii=False)
if "name" not in data_json:
body["message"] = "empty name"
return json.dumps(body, ensure_ascii=False)
im = face.base64_cv2(str(data_json["image"]))
if im is None:
body["message"] = "image format error"
return json.dumps(body, ensure_ascii=False)
isFace = face.add_user(im, idx, data_json["name"], model='hog')
if not isFace:
body["message"] = "entry failed"
return json.dumps(body, ensure_ascii=False)
idx = 1
body["success"] = True
body["message"] = ""
return json.dumps(body, ensure_ascii=False)3、http实现人脸对比，json的格式
代码语言：javascript复制@app.route('/search_user', methods=['POST'])
def search_user():
body = {"success": False, "message": "no search user", "data": []}
data = request.get_data()
if idx <= 1:
return json.dumps(body, ensure_ascii=False)
if not data:
body["message"] = "empty data"
return json.dumps(body, ensure_ascii=False)
data_json = json.loads(data)
if "image" not in data_json:
body["message"] = "empty image"
return json.dumps(body, ensure_ascii=False)
im = face.base64_cv2(str(data_json["image"]))
if im is None:
body["message"] = "image format error"
return json.dumps(body, ensure_ascii=False)
show = False
if "show" in data_json:
show = data_json["show"]
result_json, images = face.face_search_from_image(im, show, model='hog')
body["success"] = len(result_json) > 0
body["data"] = result_json
if images is not None:
body["image"] = images
body["message"] = "" if len(result_json) > 0 else "empty person"
return json.dumps(body, ensure_ascii=False)4、最后就是验证http是否可以，采用的是直接写html js实现接口测试，代码如下：
代码语言：javascript复制// 注册人脸
AddUser(params) {
this.isLoading = true
let URL = `http://${this.HOST}:${this.PORT}`
return axios.post(`${URL}/add_user`, params)
},
// 查找录入的人脸
SearchUser(params) {
this.isLoading = true
let URL = `http://${this.HOST}:${this.PORT}`
return axios.post(`${URL}/search_user`, params)
},
