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Face_data
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Face_data
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#Tanvesh Bhattad
import cv2
import numpy as np
cap = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")
skip = 0
face_data = []
dataset_path = "./face_dataset/"
file_name = input("Enter the name of person : ")
while True:
ret,frame = cap.read()
gray_frame = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
if ret == False:
continue
faces = face_cascade.detectMultiScale(gray_frame,1.3,5)
if len(faces) == 0:
continue
k = 1
faces = sorted(faces, key = lambda x : x[2]*x[3] , reverse = True)
skip += 1
for face in faces[:1]:
x,y,w,h = face
offset = 5
face_offset = frame[y-offset:y+h+offset,x-offset:x+w+offset]
face_selection = cv2.resize(face_offset,(100,100))
if skip % 10 == 0:
face_data.append(face_selection)
print (len(face_data))
cv2.imshow(str(k), face_selection)
k += 1
cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),2)
cv2.imshow("faces",frame)
key_pressed = cv2.waitKey(1) & 0xFF
if key_pressed == ord('q'):
break
face_data = np.array(face_data)
face_data = face_data.reshape((face_data.shape[0], -1))
print (face_data.shape)
np.save(dataset_path + file_name, face_data)
print ("Dataset saved at : {}".format(dataset_path + file_name + '.npy'))
cap.release()
cv2.destroyAllWindows()