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knn for face detection code

Aarav Goel answered on April 19, 2023 Popularity 3/10 Helpfulness 1/10

answer knn for face detection code

knn for face detection code

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cap = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")


skip = 0
face_data = []
dataset_path = './data/'
offset = 10

file_name = input("Enter the name of the person :  ")
while True:
    ret,frame = cap.read()
    
    if(ret == False):
        continue
        
    gray_frame = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)    
    faces = face_cascade.detectMultiScale(frame,1.3,5)
    #print(faces)
    faces = sorted(faces,key=lambda f:f[2]*f[3])
    
    #pick the last face (largest)
    for face in faces[-1:]:
        x,y,w,h =  face 
        cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)
    
    #extract main face
    face_section = frame[y-offset:y+h+offset,x-offset:x+w+offset]
    face_section = cv2.resize(face_section,(100,100))
    
    skip += 1
    if(skip%10 == 0):
        face_data.append(face_section)
        print(len(face_data))
        
    
    cv2.imshow("Cropped",face_section) 
    cv2.imshow("VIDEO FRAME",frame)
        
    keypressed = cv2.waitKey(1) & 0xFF
    if(keypressed == ord('q')):
        break
        
# convert our face list array into a numpy array
face_data = np.array(face_data)
print(face_data.shape)
face_data = face_data.reshape((face_data.shape[0],-1))
print(face_data.shape)

#save this data into file system
np.save(dataset_path + file_name + '.npy',face_data)
print("data successfully saved at " + dataset_path+file_name+'.npy')

Popularity 3/10 Helpfulness 1/10 Language whatever

Source: medium.com

Tags: face-detection knn whatever

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Contributed on Apr 19 2023

Aarav Goel

0 Answers Avg Quality 2/10

knn for face detection code

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