Python 3 利用 Dlib 19.7 实现摄像头人脸检测特征点标定

1 import dlib         # 人脸识别的库dlib
2 import numpy as np  # 数据处理的库numpy
3 import cv2          # 图像处理的库OpenCv

 1 # 2018-2-26
 2 # By TimeStamp
 3 # cnblogs: http://www.cnblogs.com/AdaminXie
 4 
 5 """
 6 cv2.VideoCapture(), 创建cv2摄像头对象/ open the default camera
 7 
 8     Python: cv2.VideoCapture() → <VideoCapture object>
 9 
10     Python: cv2.VideoCapture(filename) → <VideoCapture object>    
11     filename – name of the opened video file (eg. video.avi) or image sequence (eg. img_%02d.jpg, which will read samples like img_00.jpg, img_01.jpg, img_02.jpg, ...)
12 
13     Python: cv2.VideoCapture(device) → <VideoCapture object>
14     device – id of the opened video capturing device (i.e. a camera index). If there is a single camera connected, just pass 0.
15 
16 """
17 cap = cv2.VideoCapture(0)
18 
19 
20 """
21 cv2.VideoCapture.set(propId, value)，设置视频参数;
22 
23     propId:
24     CV_CAP_PROP_POS_MSEC Current position of the video file in milliseconds.
25     CV_CAP_PROP_POS_FRAMES 0-based index of the frame to be decoded/captured next.
26     CV_CAP_PROP_POS_AVI_RATIO Relative position of the video file: 0 - start of the film, 1 - end of the film.
27     CV_CAP_PROP_FRAME_WIDTH Width of the frames in the video stream.
28     CV_CAP_PROP_FRAME_HEIGHT Height of the frames in the video stream.
29     CV_CAP_PROP_FPS Frame rate.
30     CV_CAP_PROP_FOURCC 4-character code of codec.
31     CV_CAP_PROP_FRAME_COUNT Number of frames in the video file.
32     CV_CAP_PROP_FORMAT Format of the Mat objects returned by retrieve() .
33     CV_CAP_PROP_MODE Backend-specific value indicating the current capture mode.
34     CV_CAP_PROP_BRIGHTNESS Brightness of the image (only for cameras).
35     CV_CAP_PROP_CONTRAST Contrast of the image (only for cameras).
36     CV_CAP_PROP_SATURATION Saturation of the image (only for cameras).
37     CV_CAP_PROP_HUE Hue of the image (only for cameras).
38     CV_CAP_PROP_GAIN Gain of the image (only for cameras).
39     CV_CAP_PROP_EXPOSURE Exposure (only for cameras).
40     CV_CAP_PROP_CONVERT_RGB Boolean flags indicating whether images should be converted to RGB.
41     CV_CAP_PROP_WHITE_BALANCE_U The U value of the whitebalance setting (note: only supported by DC1394 v 2.x backend currently)
42     CV_CAP_PROP_WHITE_BALANCE_V The V value of the whitebalance setting (note: only supported by DC1394 v 2.x backend currently)
43     CV_CAP_PROP_RECTIFICATION Rectification flag for stereo cameras (note: only supported by DC1394 v 2.x backend currently)
44     CV_CAP_PROP_ISO_SPEED The ISO speed of the camera (note: only supported by DC1394 v 2.x backend currently)
45     CV_CAP_PROP_BUFFERSIZE Amount of frames stored in internal buffer memory (note: only supported by DC1394 v 2.x backend currently)
46     
47     value: 设置的参数值/ Value of the property
48 """
49 cap.set(3, 480)
50 
51 """
52 cv2.VideoCapture.isOpened(), 检查摄像头初始化是否成功 / check if we succeeded
53 返回true或false
54 """
55 cap.isOpened()
56 
57 """ 
58 cv2.VideoCapture.read([imgage]) -> retval,image, 读取视频 / Grabs, decodes and returns the next video frame
59 返回两个值：
60     一个是布尔值true/false，用来判断读取视频是否成功/是否到视频末尾
61     图像对象，图像的三维矩阵
62 """
63 flag, im_rd = cap.read()

 1 # 2018-2-26
 2 # By TimeStamp
 3 # cnblogs: http://www.cnblogs.com/AdaminXie
 4 # github: https://github.com/coneypo/Dlib_face_detection_from_camera
 5 
 6 import dlib                     #人脸识别的库dlib
 7 import numpy as np              #数据处理的库numpy
 8 import cv2                      #图像处理的库OpenCv
 9 
10 # dlib预测器
11 detector = dlib.get_frontal_face_detector()
12 predictor = dlib.shape_predictor(‘shape_predictor_68_face_landmarks.dat‘)
13 
14 # 创建cv2摄像头对象
15 cap = cv2.VideoCapture(0)
16 
17 # cap.set(propId, value)
18 # 设置视频参数，propId设置的视频参数，value设置的参数值
19 cap.set(3, 480)
20 
21 # 截图screenshoot的计数器
22 cnt = 0
23 
24 # cap.isOpened（） 返回true/false 检查初始化是否成功
25 while(cap.isOpened()):
26 
27     # cap.read()
28     # 返回两个值：
29     #    一个布尔值true/false，用来判断读取视频是否成功/是否到视频末尾
30     #    图像对象，图像的三维矩阵
31     flag, im_rd = cap.read()
32 
33     # 每帧数据延时1ms，延时为0读取的是静态帧
34     k = cv2.waitKey(1)
35 
36     # 取灰度
37     img_gray = cv2.cvtColor(im_rd, cv2.COLOR_RGB2GRAY)
38 
39     # 人脸数rects
40     rects = detector(img_gray, 0)
41 
42     #print(len(rects))
43 
44     # 待会要写的字体
45     font = cv2.FONT_HERSHEY_SIMPLEX
46 
47     # 标68个点
48     if(len(rects)!=0):
49         # 检测到人脸
50         for i in range(len(rects)):
51             landmarks = np.matrix([[p.x, p.y] for p in predictor(im_rd, rects[i]).parts()])
52 
53             for idx, point in enumerate(landmarks):
54                 # 68点的坐标
55                 pos = (point[0, 0], point[0, 1])
56 
57                 # 利用cv2.circle给每个特征点画一个圈，共68个
58                 cv2.circle(im_rd, pos, 2, color=(0, 255, 0))
59 
60                 # 利用cv2.putText输出1-68
61                 cv2.putText(im_rd, str(idx + 1), pos, font, 0.2, (0, 0, 255), 1, cv2.LINE_AA)
62         cv2.putText(im_rd, "faces: "+str(len(rects)), (20,50), font, 1, (0, 0, 255), 1, cv2.LINE_AA)
63     else:
64         # 没有检测到人脸
65         cv2.putText(im_rd, "no face", (20, 50), font, 1, (0, 0, 255), 1, cv2.LINE_AA)
66 
67     # 添加说明
68     im_rd = cv2.putText(im_rd, "s: screenshot", (20, 400), font, 0.8, (255, 255, 255), 1, cv2.LINE_AA)
69     im_rd = cv2.putText(im_rd, "q: quit", (20, 450), font, 0.8, (255, 255, 255), 1, cv2.LINE_AA)
70 
71     # 按下s键保存
72     if (k == ord(‘s‘)):
73         cnt+=1
74         cv2.imwrite("screenshoot"+str(cnt)+".jpg", im_rd)
75 
76     # 按下q键退出
77     if(k==ord(‘q‘)):
78         break
79 
80     # 窗口显示
81     cv2.imshow("camera", im_rd)
82 
83 # 释放摄像头
84 cap.release()
85 
86 # 删除建立的窗口
87 cv2.destroyAllWindows()