def main():
#paramaters
WINDOW_NAME = ("WEBCAM")
webcam = cv2.VideoCapture(0)
frame = 0
faceInit = []
initFrames = 5
nearRatio = 1.5
farRatio = 0.7
start = False
state = 0 #face distance state
previousX = 0
previousY = 0
previousW = 0
previousH = 0
#Read Shooting images
while 1:
#get face
ret, webImage = webcam.read()
faceIndex = face.faceDetection(webImage, previousX, previousY,
previousW, previousH)
cv2.imshow(WINDOW_NAME, webImage)
if (faceIndex != None):
#print(faceInit)
if (start == False): #init
faceInit.append(faceIndex)
if (len(faceInit) == initFrames):
original = compute.computeThreshold(np.asarray(faceInit))
start = True
else: #compute state
faceArea = faceIndex[2] * faceIndex[3]
state = compute.stateCompute(faceArea, state, original,
nearRatio, farRatio)
frame += 1
previousX = faceIndex[0]
previousY = faceIndex[1]
previousW = faceIndex[2]
previousH = faceIndex[3]
yield state
else:
previousX = 0
previousY = 0
previousW = 0
previousH = 0
yield state
k = cv2.waitKey(20) & 0xFF
if k == 27:
break
#press ESC leave
cv2.destroyAllWindows()
import numpy as np
import cv2
import os
import face as fr
test_img=cv2.imread(r'Test_Image.jpg') #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'trainingData.json') #Give path of where trainingData.yml is saved
name={0:"Sujit",1:"Roshan",2:"Neue"} #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]
fr.put_text(test_img,predicted_name,x,y)
resized_img=cv2.resize(test_img,(1000,700))