CODE FOR FACE DETECTION USING OpenCV #2

Hope you have visited my first blog now we will start testing our code that is the model which we have trained is it working or not from this you will come to know.


STEP 3 - Now open a new tab and copy this programme there and so that you can recognize the face is it user or anyone else.

STEP 4 - Before this install the NUMPY Lib.

Here is the link for #1(https://t.co/nn1Tfc1YUI)

import cv2
import numpy as np
from os import listdir
from os.path import isfile, join

data_path = 'C:/python/open cv/faces/'onlyfiles = [f for f in listdir(data_path) if isfile(join(data_path,f))]

Training_Data, Labels = [], []

for i, files in enumerate(onlyfiles):
    image_path = data_path + onlyfiles[i]
    images = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
    Training_Data.append(np.asarray(images, dtype=np.uint8))
    Labels.append(i)

Labels = np.asarray(Labels, dtype=np.int32)

model = cv2.face.LBPHFaceRecognizer_create()

model.train(np.asarray(Training_Data), np.asarray(Labels))

print("Model Training Complete!!!!!")

face_classifier = cv2.CascadeClassifier('C:/Users/rahul/PycharmProjects/open/venv/Lib/site-packages/cv2/data/haarcascade_frontalface_default.xml')

def face_detector(img, size = 0.5):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_classifier.detectMultiScale(gray,1.3,5)

    if faces is():
        return img,[]

    for(x,y,w,h) in faces:
        cv2.rectangle(img, (x,y),(x+w,y+h),(0,255,255),2)
        roi = img[y:y+h, x:x+w]
        roi = cv2.resize(roi, (200,200))

    return img,roi

cap = cv2.VideoCapture(0)
while True:

    ret, frame = cap.read()

    image, face = face_detector(frame)

    try:
        face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
        result = model.predict(face)

        if result[1] < 500:
            confidence = int(100*(1-(result[1])/300))
            display_string = str(confidence)+'% Confidence it is user'

        cv2.putText(image,display_string,(100,120), cv2.FONT_HERSHEY_COMPLEX,1,(250,120,255),2)

        if confidence > 75:
            cv2.putText(image, "Unlocked", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2)
            cv2.imshow('Face Cropper', image)

        else:
            cv2.putText(image, "Locked", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2)
            cv2.imshow('Face Cropper', image)


    except:
        cv2.putText(image, "Face Not Found", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 0, 0), 2)
        cv2.imshow('Face Cropper', image)
        pass
    if cv2.waitKey(1)==13:
        break

cap.release()

cv2.destroyAllWindows()

KEEP IN MIND THAT THE CODE WHICH IS GIVEN COPY IT AS IT SHOWN EVEN SPACE TOO IF NOT THE CODE WILL NOT WORK