import numpy as np
import cv2
import os
import face_recognition as fr
print (fr)
test_img=cv2.imread(r'C:\Users\msath\Desktop\LBPH\Test.jpeg') #Give path to the image which you want to test
faces_detected,gray_img=fr.faceDetection(test_img)
print("face Detected: ",faces_detected)
face_recognizer=cv2.face.LBPHFaceRecognizer_create()
face_recognizer.read(r'C:\Users\msath\Desktop\LBPH\trainingData.yml') #Give path of where trainingData.yml is saved
name={0:"Saan"} #Change names accordingly. If you want to recognize only one person then write:- name={0:"name"} thats all. Dont write for id number 1.
for face in faces_detected:
(x,y,w,h)=face
roi_gray=gray_img[y:y+h,x:x+h]
label,confidence=face_recognizer.predict(roi_gray)
print ("Confidence :",confidence)
print("label :",label)
fr.draw_rect(test_img,face)
predicted_name=name[label]
if(confidence>60):
fr.put_text(test_img,'Unknown',x,y)
continue
fr.put_text(test_img,predicted_name,x,y)
import cv2
import numpy as np
import face_recognition as fr
import os
test_img = cv2.imread('img/Narendra.jpg', 0)
faces, gray_img = fr.faceDetection(test_img)
print("Face Detected: ", faces)
for (x, y, w, h) in faces:
cv2.rectangle(test_img, (x, y), (x + w, y + h), (255, 0, 0), thickness=5)
resized_image = cv2.resize(test_img, (1000, 700))
cv2.imshow("Face Detection: ", resized_image)
cv2.waitKey(0)
cv2.destroyAllWindows