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how to restrict 2d image (photo) face detection in real time face recognition using opencv python import cv2 import nump

how to restrict 2d image (photo) face detection in real time face recognition using opencv python import cv2 import nump

how to read value from input form in python flask dynamically and to store the value as image name inside directory when

I am creating web application for face recognition using python flask app. I am already create static dataset. I need th

I'm creating a web application for face recognition using the python flask app. I already create a static dataset. I nee

I am creating web application for face recognition using python flask app. I am already create static dataset. I need th

I am creating web application for face recognition using python flask app. I am already create static dataset. I need th

I am creating web application for face recognition using python flask app. I am already create static dataset. I need th

I am creating web application for face recognition using python flask app. I am already create static dataset. I need th

I am creating a dataset for face recognition using python. Then i want to validate if the face is already available in t

i am creating a dataset for real time face recognition using python. i want it should intimate if the image already avai

I am create a rectangle box in video stream using python. how to apply face detection in rectangular box inside only and

your solution is worked

Code:

import cv2

face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
ds_factor = 0.6
font = cv2.FONT_HERSHEY_SIMPLEX

class VideoCamera(object):
    def __init__(self):
        self.video = cv2.VideoCapture(0)

    def __del__(self):
        self.video.release()

    def get_frame(self):
        success, image = self.video.read()
        cv2.rectangle(image, (400, 300), (800, 600), (255, 255, 255), -1)
        cv2.resize(output, None, fx=ds_factor, fy=ds_factor, interpolation=cv2.INTER_AREA)
        gray = cv2.cvtColor(output, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(
            gray, scaleFactor=1.1,
            minNeighbors=5,
            minSize=(200, 200),
            flags=cv2.CASCADE_SCALE_IMAGE)

        for (x, y, w, h) in faces:
            cv2.rectangle(output, (x, y), (x + w, y + h), (255, 0, 0), 3)
            cv2.putText(output, 'Number of Faces : ' + str(len(faces)), (40, 40), font, 1, (255, 0, 0), 2)
            break
        ret, jpeg = cv2.imencode('.jpg', output)
        return jpeg.tobytes()

thank you so much