facemaster.py

#trainfunction()
import cv2
import numpy as np
import face_detect as face_detect
import prepare_training_data as prepare_training_data

label = []
def predict(test_img):
	img = cv2.imread(test_img).copy()
	print "\n\n\n"
	print "Face Prediction Running -\-"
	face, rect, length = face_detect.face_detect(test_img)
	print len(face), "faces detected."
	for i in range(0, len(face)):
		labeltemp, confidence = face_recognizer.predict(face[i])
		label.append(labeltemp)
	return img, label

faces, labels = prepare_training_data.prepare_training_data("training-data")
face_recognizer = cv2.face.LBPHFaceRecognizer_create()
face_recognizer.train(faces, np.array(labels))


test_img1 = "test-data/test5.jpg"
predicted_img , label= predict(test_img1)
cv2.destroyAllWindows()
cv2.waitKey(1)
cv2.destroyAllWindows()
print "Recognized Students = ", label