face_data_collect.py

import cv2
import numpy as np

#initialise webcam

cap = cv2.VideoCapture(0)

#face Detection
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")

skip = 0
face_data = []
dataset_path = "./data/"
file_name = input("Enter the name of 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)

	if (len(faces)) == 0:
		continue

	faces = sorted(faces,key = lambda f:f[2]*f[3])

	#pick the last face(largest area)

	for face in faces[-1:]:
		#draw bounding box
		x,y,w,h = face
		cv2.rectangle(frame,(x,y), (x+w,y+h), (0,255,255), 2)

		#extract (crop out face)
		offset = 10
		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))
		#print(faces[-1:])


	cv2.imshow("Frame" , frame)
	cv2.imshow("Face Section" , face_section)
	#cv2.imshow("gray_frame" , gray_frame)

	key_pressed = cv2.waitKey(1) & 0xFF
	if key_pressed == ord('q'):
		break

#convert face data list to numpy array
face_data = np.asarray(face_data)
face_data = face_data.reshape((face_data.shape[0],-1))
print(face_data.shape)

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

cap.release()
cv2.destroyAllWindows()