Face Detection and Recognition

1import numpy as np
2
3import cv2
4
5face_cascade = cv2.CascadeClassifier('F:/Program  Files/opencv/sources/data/haarcascades/haarcascade_frontalface_default.xml')
6
7eye_cascade  = cv2.CascadeClassifier('F:/Program Files/opencv/sources/data/haarcascades/haarcascade_eye.xml')
8
9cap  = cv2.VideoCapture(0)<br>while 1:
10
11    ret, img = cap.read()
12
13    gray  = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
14
15    faces = face_cascade.detectMultiScale(gray,  1.5, 5)
16
17    for (x,y,w,h) in faces:
18
19        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
20
21        roi_gray = gray[y:y+h, x:x+w]
22
23        roi_color = img[y:y+h, x:x+w]
24
25        eyes = eye_cascade.detectMultiScale(roi_gray)
26
27        for (ex,ey,ew,eh)  in eyes:
28
29            cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
30
31    print "found " +str(len(faces)) +" face(s)"
32
33    cv2.imshow('img',img)
34
35    k = cv2.waitKey(30) & 0xff
36
37    if k == 27:
38
39        break
40
41cap.release()
42
43cv2.destroyAllWindows()

1import numpy as npimport cv2
2face_cascade = cv2.CascadeClassifier('F:/Program  Files/opencv/sources/data/haarcascades/haarcascade_frontalface_default.xml')
3cap  = cv2.VideoCapture(0)
4rec = cv2.createLBPHFaceRecognizer();
5rec.load("F:/Program  Files/projects/face_rec/faceREC/trainingdata.yml")
6id=0
7font=cv2.cv.InitFont(cv2.cv.CV_FONT_HERSHEY_COMPLEX_SMALL,5,1,0,4)
8while  1:
9    ret, img = cap.read()
10    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
11    faces = face_cascade.detectMultiScale(gray, 1.5, 5)
12    for (x,y,w,h) in  faces:
13        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
14        id,conf=rec.predict(gray[y:y+h,x:x+w])
15        if(id==2):
16            id="alok"
17        if id==1:
18            id="alok"
19        if id==3:
20            id="anjali"
21        if id==4:
22            id="Gaurav"
23        if id==5:
24            id='rahul'
25        if id==6:
26            id="akshay"
27        cv2.cv.PutText(cv2.cv.fromarray(img),str(id),(x,y+h),font,255)
28    cv2.imshow('img',img)
29    
30    if cv2.waitKey(1) == ord('q'):
31        break
32cap.release()cv2.destroyAllWindows()

1import numpy as np
2
3import cv2
4
5face_cascade = cv2.CascadeClassifier('F:/Program   Files/opencv/sources/data/haarcascades/haarcascade_frontalface_default.xml')
6
7cap   = cv2.VideoCapture(0)
8
9id = raw_input('enter user id')
10
11sampleN=0;
12
13while   1:
14
15    ret, img = cap.read()
16
17    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
18
19     faces = face_cascade.detectMultiScale(gray, 1.3, 5)
20
21    for (x,y,w,h)   in faces:
22
23        sampleN=sampleN+1;
24
25        cv2.imwrite("F:/Program   Files/projects/face_rec/facesData/User."+str(id)+ "." +str(sampleN)+ ".jpg",   gray[y:y+h, x:x+w])
26
27        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
28
29         cv2.waitKey(100)
30
31    cv2.imshow('img',img)
32
33    cv2.waitKey(1)
34
35     if sampleN > 20:
36
37        break
38
39cap.release()
40
41cv2.destroyAllWindows()

1import os
2
3import numpy as np
4
5import cv2
6
7from PIL  import Image # For face recognition we will the the LBPH Face Recognizer 
8
9recognizer  = cv2.createLBPHFaceRecognizer();
10
11path="F:/Program Files/projects/face_rec/facesData"
12
13def  getImagesWithID(path):
14
15    imagePaths = [os.path.join(path, f) for f in os.listdir(path)]   
16
17 # print image_path   
18
19 #getImagesWithID(path)
20
21    faces  = []
22
23    IDs = []
24
25    for imagePath in imagePaths:      
26
27  #  Read the image and convert to grayscale
28
29        facesImg = Image.open(imagePath).convert('L')
30
31        faceNP = np.array(facesImg, 'uint8')
32
33        # Get the label of the  image
34
35        ID= int(os.path.split(imagePath)[-1].split(".")[1])
36
37         # Detect the face in the image
38
39        faces.append(faceNP)
40
41        IDs.append(ID)
42
43        cv2.imshow("Adding faces for traning",faceNP)
44
45        cv2.waitKey(10)
46
47    return np.array(IDs), faces
48
49Ids,faces  = getImagesWithID(path)
50
51recognizer.train(faces,Ids)
52
53recognizer.save("F:/Program  Files/projects/face_rec/faceREC/trainingdata.yml")
54
55cv2.destroyAllWindows()

1import numpy as npimport cv2
2face_cascade = cv2.CascadeClassifier('F:/Program   Files/opencv/sources/data/haarcascades/haarcascade_frontalface_default.xml')
3cap   = cv2.VideoCapture(0)
4rec = cv2.createLBPHFaceRecognizer();
5rec.load("F:/Program   Files/projects/face_rec/faceREC/trainingdata.yml")
6id=0
7font=cv2.cv.InitFont(cv2.cv.CV_FONT_HERSHEY_COMPLEX_SMALL,5,1,0,4)
8while   1:
9    ret, img = cap.read()
10    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
11     faces = face_cascade.detectMultiScale(gray, 1.5, 5)
12    for (x,y,w,h) in   faces:
13        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
14        id,conf=rec.predict(gray[y:y+h,x:x+w])
15         if(id==2):
16            id="alok"
17        if id==1:
18            id="alok"
19         if id==3:
20            id="anjali"
21        if id==4:
22            id="Gaurav"
23         if id==5:
24            id='rahul'
25        if id==6:
26            id="akshay"
27         cv2.cv.PutText(cv2.cv.fromarray(img),str(id),(x,y+h),font,255)
28    cv2.imshow('img',img)
29     
30    if cv2.waitKey(1) == ord('q'):
31        break
32cap.release()cv2.destroyAllWindows()

1import os
2
3import numpy as np
4
5import cv2
6
7from PIL
8  import Image # For face recognition we will the the LBPH Face Recognizer 
9
10recognizer
11  = cv2.createLBPHFaceRecognizer();
12
13path="F:/Program Files/projects/face_rec/facesData"
14
15def
16  getImagesWithID(path):
17
18    imagePaths = [os.path.join(path, f) for f in os.listdir(path)]
19   
20
21 # print image_path   
22
23 #getImagesWithID(path)
24
25    faces
26  = []
27
28    IDs = []
29
30    for imagePath in imagePaths:      
31
32  #
33  Read the image and convert to grayscale
34
35        facesImg = Image.open(imagePath).convert('L')
36
37
38        faceNP = np.array(facesImg, 'uint8')
39
40        # Get the label of the
41  image
42
43        ID= int(os.path.split(imagePath)[-1].split(".")[1])
44
45
46         # Detect the face in the image
47
48        faces.append(faceNP)
49
50
51        IDs.append(ID)
52
53        cv2.imshow("Adding faces for traning",faceNP)
54
55
56        cv2.waitKey(10)
57
58    return np.array(IDs), faces
59
60Ids,faces
61  = getImagesWithID(path)
62
63recognizer.train(faces,Ids)
64
65recognizer.save("F:/Program
66  Files/projects/face_rec/faceREC/trainingdata.yml")
67
68cv2.destroyAllWindows()

1import numpy as np
2
3import cv2
4
5face_cascade = cv2.CascadeClassifier('F:/Program  Files/opencv/sources/data/haarcascades/haarcascade_frontalface_default.xml')
6
7cap  = cv2.VideoCapture(0)
8
9id = raw_input('enter user id')
10
11sampleN=0;
12
13while  1:
14
15    ret, img = cap.read()
16
17    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
18
19    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
20
21    for (x,y,w,h)  in faces:
22
23        sampleN=sampleN+1;
24
25        cv2.imwrite("F:/Program  Files/projects/face_rec/facesData/User."+str(id)+ "." +str(sampleN)+ ".jpg",  gray[y:y+h, x:x+w])
26
27        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
28
29        cv2.waitKey(100)
30
31    cv2.imshow('img',img)
32
33    cv2.waitKey(1)
34
35    if sampleN > 20:
36
37        break
38
39cap.release()
40
41cv2.destroyAllWindows()

1import numpy as np
2
3import cv2
4
5face_cascade = cv2.CascadeClassifier('F:/Program
6  Files/opencv/sources/data/haarcascades/haarcascade_frontalface_default.xml')
7
8eye_cascade
9  = cv2.CascadeClassifier('F:/Program Files/opencv/sources/data/haarcascades/haarcascade_eye.xml')
10
11cap
12  = cv2.VideoCapture(0)<br>while 1:
13
14    ret, img = cap.read()
15
16    gray
17  = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
18
19    faces = face_cascade.detectMultiScale(gray,
20  1.5, 5)
21
22    for (x,y,w,h) in faces:
23
24        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
25
26
27        roi_gray = gray[y:y+h, x:x+w]
28
29        roi_color = img[y:y+h, x:x+w]
30
31
32        eyes = eye_cascade.detectMultiScale(roi_gray)
33
34        for (ex,ey,ew,eh)
35  in eyes:
36
37            cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
38
39
40    print "found " +str(len(faces)) +" face(s)"
41
42    cv2.imshow('img',img)
43
44
45    k = cv2.waitKey(30) & 0xff
46
47    if k == 27:
48
49        break
50
51cap.release()
52
53cv2.destroyAllWindows()

1import cv2
2
3cap = cv2.VideoCapture("input_video.mp4")
4
5print  cap.isOpened()   # True = read video successfully. False - fail to read video.
6
7fourcc  = cv2.VideoWriter_fourcc(*'XVID')
8
9out = cv2.VideoWriter("output_video.avi",  fourcc, 20.0, (640, 360))
10
11print out.isOpened()  # True = write out video  successfully. False - fail to write out video.
12
13cap.release()
14
15out.release()