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