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I am create a rectangle box in video stream using python. how to apply face detection in rectangular box inside only and don't need out of the rectangular box detect face

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()
    output = cv2.rectangle(image, (400, 300), (800, 600), (255, 255, 255), 2)
    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()

I am create a rectangle box in video stream using python. how to apply face detection in rectangular box inside only and don't need out of the rectangular box detect face

import cv2
 cv2

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


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

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

 def get_frame(self):
     success, image = self.video.read()
     output = cv2.rectangle(image, (400, 300), (800, 600), (255, 255, 255), 2)
     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()

          3    None 
      updated 
2020-12-03 06:39:03 -0600
 
 
 
  
 
 
 
  I am create a rectangle box in video stream using python. how to apply face detection in rectangular box inside only and don't need out of the rectangular box detect face
 .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)
 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()
     output = image.copy()
    cv2.rectangle(image, (400, 300), (800, 600), (255, 255, 255), 2)
    -1)
    cv2.addWeighted(image, 0.5, output, 1 - .5, 0, output)
    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()
 
 
 
          4    None 
      updated 
2020-12-03 06:58:18 -0600
 
 
 
  
 
 
 
  I am create a rectangle box in video stream using python. how to apply face detection in rectangular box inside only and don't need out of the rectangular box detect face
 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()
    output = image.copy()
    cv2.rectangle(image, (400, 300), (800, 600), (255, 255, 255), -1)
    cv2.addWeighted(image, 0.5, output, 1 - .5, 0, output)
    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()
 
 
 
          5    None 
      updated 
2020-12-03 07:37:47 -0600
 
    supra56  
 943  ●9 ●6  
 
 
 
  
 
 
 
  I am create a rectangle box in video stream using python. how to apply face detection in rectangular box inside only and don't need out of the rectangular box detect face
 Code:
 import cv2
 cv2

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

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