Keras之CNN:基于Keras利用cv2建立训练存储卷积神经网络模型(2+1)并调用摄像头进行实时人脸识别
目录
- -*- coding:utf-8 -*-
- import cv2
- from train_model import Model
- from read_data import read_name_list
- from timeit import default_timer as timer to calculate FPS
-
- class Camera_reader(-title class_ inherited__">object):
- def __init__(self):
- self.model = Model()
- self.model.load()
- self.img_size = 128
-
-
- def build_camera(self):
- face_cascade = cv2.CascadeClassifier('F:\\Program Files\\Python\\Python36\\Lib\\site-packages\\cv2\\data\\haarcascade_frontalface_alt.xml')
- print(face_cascade) 输出<CascadeClassifier 000002240244CC70>
- name_list = read_name_list('F:\\File_Python\\Python_example\\face_recognition_name\\After_cut_picture')
- print(name_list)
-
- cameraCapture = cv2.VideoCapture(0)
-
- success, frame = cameraCapture.read()
-
- while success and cv2.waitKey(1) == -1:
- success, frame = cameraCapture.read()
- gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
- faces = face_cascade.detectMultiScale(gray, 1.3, 5)
- ROI = gray[x:x + w, y:y + h]
- ROI = cv2.resize(ROI, (self.img_size, self.img_size), interpolation=cv2.INTER_LINEAR)
- label,prob = self.model.predict(ROI)
- if prob >0.7:
- show_name = name_list[label]
- else:
- show_name = 'Stranger'
- cv2.putText(frame, show_name, (x, y - 20), cv2.FONT_HERSHEY_SIMPLEX, 1, 255, 2)
- frame = cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
- cv2.imshow("Camera", frame)
-
- cameraCapture.release()
- cv2.destroyAllWindows()
- def detect_video(self):
- face_cascade = cv2.CascadeClassifier('F:\\Program Files\\Python\\Python36\\Lib\\site-packages\\cv2\\data\\haarcascade_frontalface_alt.xml')
-
- name_list = read_name_list('F:\\File_Python\\Python_example\\face_recognition_name\\After_cut_picture')
- video = cv2.VideoCapture(video_path) -doctag">TODO: will video path other than 0 be used?
- success, frame = video.read()
- accum_time = 0
- curr_fps = 0
- fps = "FPS: ??" fps = "FPS: ??"
- prev_time = timer()
-
- while success and cv2.waitKey(1) == -1:
- success, frame = video.read()
- gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
- faces = face_cascade.detectMultiScale(gray, 1.3, 5)
-
- curr_time = timer()
- exec_time = curr_time - prev_time
- prev_time = curr_time
- accum_time = accum_time + exec_time
- curr_fps = curr_fps + 1 1
- if accum_time > 1:
- accum_time = accum_time - 1 1
- fps = "FPS: " + str(curr_fps)
- curr_fps = 0 0
-
- for (x, y, w, h) in faces:
- ROI = gray[x:x + w, y:y + h]
- ROI = cv2.resize(ROI, (self.img_size, self.img_size), interpolation=cv2.INTER_LINEAR) cv2.INTER_LINEAR图像尺寸变换的方法,默认的双线性插值
- label,prob = self.model.predict(ROI)
-
- if prob >0.7:
- show_name = name_list[label]
- else:
- show_name = 'Stranger'
- cv2.putText(frame, show_name, (x, y - 20), cv2.FONT_HERSHEY_SIMPLEX, 1, 255, 2)
- frame = cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
- cv2.namedWindow("result", cv2.WINDOW_NORMAL)
- cv2.imshow("result",frame)
-
- if __name__ == '__main__':
- camera = Camera_reader()
- camera.build_camera()
- video_path='F:/File_Python/Python_example/YOLOv3_use_TF/RunMan1.mp4'
- camera.detect_video()
网站声明:如果转载,请联系本站管理员。否则一切后果自行承担。
加入交流群
请使用微信扫一扫!