将遮罩应用于 opencv 中的网络摄像头流
Apply mask to Webcam streaming in opencv
我使用 OpenCV 对视频源应用了掩码，并希望在网站上显示直播，但以下代码在开始后停止流式传输。我一直在绞尽脑汁，但找不到解决方案。任何帮助将不胜感激。
views.py
def gen(frame):
while True:
# frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
@api_view(['GET'])
def seasoncolor(request):
while True:
return StreamingHttpResponse(gen(color_detection.color_detection(0)),
content_type='multipart/x-mixed-replace; boundary=frame')
color_detection.py
import numpy as np
import cv2
import sys
'''
ML object detection algo(haarcascade)used to identify objects.
the XML file consists of trained Haar Cascade models.
'''
def color_detection(season):
face_cascade = cv2.CascadeClassifier(
'accounts/personal_color/self_detection/haarcascade_frontalface_default.xml')
# 'accounts/personal_color/self_detection/haarcascade_frontalface_default.xml'
# initialize video from the webcam
video = cv2.VideoCapture(1)
# Spring/summer/fall/winter
while True:
# ret tells if the camera works properly. Frame is an actual frame from the video feed
ret, frame = video.read()
# make sure port is working and read the image
if frame is not None and video.isOpened():
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
'''
Detect the faces within the subregions of the image in scales
scaleFactor indicates how much the image size is reduced at each image scale.
minNeighbors: Higher value results in higher quality of the detected face.
'''
faces = face_cascade.detectMultiScale(
gray, scaleFactor=1.1, minNeighbors=6)
# Draw the rectangle around each face
for (x, y, w, h) in faces:
# Use the stcoordinates to find the center of the face and from that point draw a rectangle of radius w/2 or h/2.
center_coordinates = x + w // 2, y + h // 2
radius = w // 2 # or can be h / 2 or can be anything based on your requirements
# background color(black)
mask = np.zeros(frame.shape[:2], dtype="uint8")
# Draw the desired region to crop out in white
cv2.circle(mask, center_coordinates, radius, (255, 255, 255), -1)
masked = cv2.bitwise_and(frame, frame, mask=mask)
if int(season) ==0: # Spring
# Replace all (0,0,0)channel with Coral pink
masked[np.where((masked == [0, 0, 0]).all(axis=2))] = [121, 131, 248]
elif int(season) ==1: # Summer
#Replace all (0,0,0)channel with Rose Red
masked[np.where((masked==[0,0,0]).all(axis=2))]=[86,30,194]
elif int(season) ==2: # Fall
#Replace all (0,0,0)channel with Red Brown /Cinnamon
masked[np.where((masked==[0,0,0]).all(axis=2))]=[30,105,210]
else: # Winter
#Replace all (0,0,0)channel with Burgundy Red
masked[np.where((masked==[0,0,0]).all(axis=2))]=[31,2,141]
# cv2.imshow('mask applied', masked)
ret, jpeg = cv2.imencode('.jpg', masked)
return jpeg.tobytes()
if cv2.waitKey(30) & 0xff == 27:
break
video.release()
cv2.destroyAllWindows()
if __name__ == '__main__':
arg = sys.argv[1]
color_detection(arg)
Self_color_diagnosis.js
import React, { useState, useEffect } from 'react';
import ReactDOM from 'react-dom';
import CameraScreen from './CameraScreen';
import { StyleSheet, Text, View, Image } from 'react-native';
import { NavigationContainer } from '@react-navigation/native';
import { createStackNavigator } from '@react-navigation/stack';
import axios from 'axios';
function Self_color_diagnosis({navigation,route}) {
return (
<View style={styles.title_container}>
<Image style={styles.video} source={{
uri: 'http://localhost:8000/seasoncolor/',}}/>
</View>
);
}
const styles = StyleSheet.create({
video: {
width: 500,
height: 500
},
title_container: {
flex: 1,
justifyContent: 'center'
},
});
export default Self_color_diagnosis;
以上代码生成下图。流式传输停止并且根本没有改变。
gen() 运行s 循环，所有时间都使用相同的 frame().
你必须 frame 进入这个循环。
def gen():
while True:
frame = color_detection.color_detection(0)
if frame:
yield b'--frame\r\nContent-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n'
#else:
# print('no frame')
但是 color_detection 应该 运行 没有 loop。
而且你应该只创建一次 VideoCapture(1)。
即使您没有检测到任何人脸，您也应该 return frame。
path = os.path.join(cv2.data.haarcascades, 'haarcascade_frontalface_default.xml')
face_cascade = cv2.CascadeClassifier(path)
video = cv2.VideoCapture(1)
def color_detection(season):
# ret tells if the camera works properly. Frame is an actual frame from the video feed
ret, frame = video.read()
# make sure port is working and read the image
if frame is not None and video.isOpened():
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
'''
Detect the faces within the subregions of the image in scales
scaleFactor indicates how much the image size is reduced at each image scale.
minNeighbors: Higher value results in higher quality of the detected face.
'''
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=6)
# Draw circle around each face
for (x, y, w, h) in faces:
# Use the stcoordinates to find the center of the face and from that point draw a rectangle of radius w/2 or h/2.
center_coordinates = x + w // 2, y + h // 2
radius = w // 2 # or can be h / 2 or can be anything based on your requirements
# background color(black)
mask = np.zeros(frame.shape[:2], dtype="uint8")
# Draw the desired region to crop out in white
cv2.circle(mask, center_coordinates, radius, (255, 255, 255), -1)
masked = cv2.bitwise_and(frame, frame, mask=mask)
if season == 0: # Spring
# Replace all (0,0,0)channel with Coral pink
masked[np.where((masked == [0, 0, 0]).all(axis=2))] = [121, 131, 248]
elif season == 1: # Summer
#Replace all (0,0,0)channel with Rose Red
masked[np.where((masked==[0,0,0]).all(axis=2))] = [86,30,194]
elif season == 2: # Fall
#Replace all (0,0,0)channel with Red Brown /Cinnamon
masked[np.where((masked==[0,0,0]).all(axis=2))] = [30,105,210]
else: # Winter
#Replace all (0,0,0)channel with Burgundy Red
masked[np.where((masked==[0,0,0]).all(axis=2))] = [31,2,141]
ret, jpeg = cv2.imencode('.jpg', masked)
else: # it is `for/else` construction, not `if/else`
ret, jpeg = cv2.imencode('.jpg', frame)
return jpeg.tobytes()
#return None
顺便说一句：
我看到了其他问题。当它检测到多张脸时，它会为每张脸创建新的面具，并将每个面具分配给原始图像——所以每个面具都会跳过以前的面具——所以它应该只显示最后一张脸，并隐藏其他脸。您应该首先创建一个包含所有圆圈的蒙版，然后在图像上使用它。
编辑：
我不知道您使用的是什么 Web 框架，所以我使用 Flask 创建了最小的工作示例。
import os
from flask import Flask, Response
import cv2
import numpy as np
app = Flask(__name__)
print('\n'.join(sorted(os.listdir(cv2.data.haarcascades))))
path = os.path.join(cv2.data.haarcascades, 'haarcascade_frontalface_default.xml')
face_cascade = cv2.CascadeClassifier(path)
#video = cv2.VideoCapture(0) # my webcam
video = cv2.VideoCapture(0) # your webcam
def color_detection(season):
ret, frame = video.read()
if frame is not None and video.isOpened():
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=6)
# test two circles on image 640x480
#faces = [[100, 100, 250, 250], [640-100-250, 480-100-250, 250, 250]]
if len(faces) > 0: # it can be `if faces:` because `faces` is `numpy array` which need different method to check if not empty
# background color(black)
mask = np.zeros(frame.shape[:2], dtype="uint8")
# draw all circles on mask
for (x, y, w, h) in faces:
#print(x, y, w, h)
# use the coordinates to find the center of the face and from that point draw a rectangle of radius w/2 or h/2.
center_coordinates = x + w // 2, y + h // 2
radius = max(w, h) // 2 # or can be h / 2 or can be anything based on your requirements
# draw the desired region to crop out in white
cv2.circle(mask, center_coordinates, radius, (255, 255, 255), -1)
# use mask with all circles
masked = cv2.bitwise_and(frame, frame, mask=mask)
if season == 0: # Spring - Coral pink
color = [121, 131, 248]
elif season == 1: # Summer - Rose Red
color = [86,30,194]
elif season == 2: # Fall - Red Brown /Cinnamon
color = [30,105,210]
else: # Winter - Burgundy Red
color = [31,2,141]
masked[np.where((masked == [0,0,0]).all(axis=2))] = color
else: # no faces
masked = frame
ret, jpeg = cv2.imencode('.jpg', masked)
return jpeg.tobytes()
def gen():
while True:
frame = color_detection(0)
if frame:
yield (b'--frame\r\nContent-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
#else:
# print('no frame')
@app.route('/')
def index():
return '<image src="/seasoncolor">'
@app.route('/seasoncolor')
def seasoncolor():
return Response(gen(), mimetype='multipart/x-mixed-replace; boundary=frame')
if __name__ == '__main__':
#app.debug = True
app.run()
顺便说一句：
确保：VideoCapture 只能与您 运行 网络服务器所在的本地摄像头一起使用。它不能与用户计算机上的远程摄像头一起使用。只有用户的浏览器可以访问其相机。要在用户计算机上使用远程摄像头，您必须使用 JavaScript 在用户浏览器中访问摄像头并将帧发送到服务器 - 就像我在 GitHub python-examples 中的示例：web camera in browser - canvas - take image and upload to server
我使用 OpenCV 对视频源应用了掩码，并希望在网站上显示直播，但以下代码在开始后停止流式传输。我一直在绞尽脑汁，但找不到解决方案。任何帮助将不胜感激。
views.py
def gen(frame):
while True:
# frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
@api_view(['GET'])
def seasoncolor(request):
while True:
return StreamingHttpResponse(gen(color_detection.color_detection(0)),
content_type='multipart/x-mixed-replace; boundary=frame')
color_detection.py
import numpy as np
import cv2
import sys
'''
ML object detection algo(haarcascade)used to identify objects.
the XML file consists of trained Haar Cascade models.
'''
def color_detection(season):
face_cascade = cv2.CascadeClassifier(
'accounts/personal_color/self_detection/haarcascade_frontalface_default.xml')
# 'accounts/personal_color/self_detection/haarcascade_frontalface_default.xml'
# initialize video from the webcam
video = cv2.VideoCapture(1)
# Spring/summer/fall/winter
while True:
# ret tells if the camera works properly. Frame is an actual frame from the video feed
ret, frame = video.read()
# make sure port is working and read the image
if frame is not None and video.isOpened():
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
'''
Detect the faces within the subregions of the image in scales
scaleFactor indicates how much the image size is reduced at each image scale.
minNeighbors: Higher value results in higher quality of the detected face.
'''
faces = face_cascade.detectMultiScale(
gray, scaleFactor=1.1, minNeighbors=6)
# Draw the rectangle around each face
for (x, y, w, h) in faces:
# Use the stcoordinates to find the center of the face and from that point draw a rectangle of radius w/2 or h/2.
center_coordinates = x + w // 2, y + h // 2
radius = w // 2 # or can be h / 2 or can be anything based on your requirements
# background color(black)
mask = np.zeros(frame.shape[:2], dtype="uint8")
# Draw the desired region to crop out in white
cv2.circle(mask, center_coordinates, radius, (255, 255, 255), -1)
masked = cv2.bitwise_and(frame, frame, mask=mask)
if int(season) ==0: # Spring
# Replace all (0,0,0)channel with Coral pink
masked[np.where((masked == [0, 0, 0]).all(axis=2))] = [121, 131, 248]
elif int(season) ==1: # Summer
#Replace all (0,0,0)channel with Rose Red
masked[np.where((masked==[0,0,0]).all(axis=2))]=[86,30,194]
elif int(season) ==2: # Fall
#Replace all (0,0,0)channel with Red Brown /Cinnamon
masked[np.where((masked==[0,0,0]).all(axis=2))]=[30,105,210]
else: # Winter
#Replace all (0,0,0)channel with Burgundy Red
masked[np.where((masked==[0,0,0]).all(axis=2))]=[31,2,141]
# cv2.imshow('mask applied', masked)
ret, jpeg = cv2.imencode('.jpg', masked)
return jpeg.tobytes()
if cv2.waitKey(30) & 0xff == 27:
break
video.release()
cv2.destroyAllWindows()
if __name__ == '__main__':
arg = sys.argv[1]
color_detection(arg)
Self_color_diagnosis.js
import React, { useState, useEffect } from 'react';
import ReactDOM from 'react-dom';
import CameraScreen from './CameraScreen';
import { StyleSheet, Text, View, Image } from 'react-native';
import { NavigationContainer } from '@react-navigation/native';
import { createStackNavigator } from '@react-navigation/stack';
import axios from 'axios';
function Self_color_diagnosis({navigation,route}) {
return (
<View style={styles.title_container}>
<Image style={styles.video} source={{
uri: 'http://localhost:8000/seasoncolor/',}}/>
</View>
);
}
const styles = StyleSheet.create({
video: {
width: 500,
height: 500
},
title_container: {
flex: 1,
justifyContent: 'center'
},
});
export default Self_color_diagnosis;
以上代码生成下图。流式传输停止并且根本没有改变。
gen() 运行s 循环，所有时间都使用相同的 frame().
你必须 frame 进入这个循环。
def gen():
while True:
frame = color_detection.color_detection(0)
if frame:
yield b'--frame\r\nContent-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n'
#else:
# print('no frame')
但是 color_detection 应该 运行 没有 loop。
而且你应该只创建一次 VideoCapture(1)。
即使您没有检测到任何人脸，您也应该 return frame。
path = os.path.join(cv2.data.haarcascades, 'haarcascade_frontalface_default.xml')
face_cascade = cv2.CascadeClassifier(path)
video = cv2.VideoCapture(1)
def color_detection(season):
# ret tells if the camera works properly. Frame is an actual frame from the video feed
ret, frame = video.read()
# make sure port is working and read the image
if frame is not None and video.isOpened():
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
'''
Detect the faces within the subregions of the image in scales
scaleFactor indicates how much the image size is reduced at each image scale.
minNeighbors: Higher value results in higher quality of the detected face.
'''
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=6)
# Draw circle around each face
for (x, y, w, h) in faces:
# Use the stcoordinates to find the center of the face and from that point draw a rectangle of radius w/2 or h/2.
center_coordinates = x + w // 2, y + h // 2
radius = w // 2 # or can be h / 2 or can be anything based on your requirements
# background color(black)
mask = np.zeros(frame.shape[:2], dtype="uint8")
# Draw the desired region to crop out in white
cv2.circle(mask, center_coordinates, radius, (255, 255, 255), -1)
masked = cv2.bitwise_and(frame, frame, mask=mask)
if season == 0: # Spring
# Replace all (0,0,0)channel with Coral pink
masked[np.where((masked == [0, 0, 0]).all(axis=2))] = [121, 131, 248]
elif season == 1: # Summer
#Replace all (0,0,0)channel with Rose Red
masked[np.where((masked==[0,0,0]).all(axis=2))] = [86,30,194]
elif season == 2: # Fall
#Replace all (0,0,0)channel with Red Brown /Cinnamon
masked[np.where((masked==[0,0,0]).all(axis=2))] = [30,105,210]
else: # Winter
#Replace all (0,0,0)channel with Burgundy Red
masked[np.where((masked==[0,0,0]).all(axis=2))] = [31,2,141]
ret, jpeg = cv2.imencode('.jpg', masked)
else: # it is `for/else` construction, not `if/else`
ret, jpeg = cv2.imencode('.jpg', frame)
return jpeg.tobytes()
#return None
顺便说一句：
我看到了其他问题。当它检测到多张脸时，它会为每张脸创建新的面具，并将每个面具分配给原始图像——所以每个面具都会跳过以前的面具——所以它应该只显示最后一张脸，并隐藏其他脸。您应该首先创建一个包含所有圆圈的蒙版，然后在图像上使用它。
编辑：
我不知道您使用的是什么 Web 框架，所以我使用 Flask 创建了最小的工作示例。
import os
from flask import Flask, Response
import cv2
import numpy as np
app = Flask(__name__)
print('\n'.join(sorted(os.listdir(cv2.data.haarcascades))))
path = os.path.join(cv2.data.haarcascades, 'haarcascade_frontalface_default.xml')
face_cascade = cv2.CascadeClassifier(path)
#video = cv2.VideoCapture(0) # my webcam
video = cv2.VideoCapture(0) # your webcam
def color_detection(season):
ret, frame = video.read()
if frame is not None and video.isOpened():
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=6)
# test two circles on image 640x480
#faces = [[100, 100, 250, 250], [640-100-250, 480-100-250, 250, 250]]
if len(faces) > 0: # it can be `if faces:` because `faces` is `numpy array` which need different method to check if not empty
# background color(black)
mask = np.zeros(frame.shape[:2], dtype="uint8")
# draw all circles on mask
for (x, y, w, h) in faces:
#print(x, y, w, h)
# use the coordinates to find the center of the face and from that point draw a rectangle of radius w/2 or h/2.
center_coordinates = x + w // 2, y + h // 2
radius = max(w, h) // 2 # or can be h / 2 or can be anything based on your requirements
# draw the desired region to crop out in white
cv2.circle(mask, center_coordinates, radius, (255, 255, 255), -1)
# use mask with all circles
masked = cv2.bitwise_and(frame, frame, mask=mask)
if season == 0: # Spring - Coral pink
color = [121, 131, 248]
elif season == 1: # Summer - Rose Red
color = [86,30,194]
elif season == 2: # Fall - Red Brown /Cinnamon
color = [30,105,210]
else: # Winter - Burgundy Red
color = [31,2,141]
masked[np.where((masked == [0,0,0]).all(axis=2))] = color
else: # no faces
masked = frame
ret, jpeg = cv2.imencode('.jpg', masked)
return jpeg.tobytes()
def gen():
while True:
frame = color_detection(0)
if frame:
yield (b'--frame\r\nContent-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
#else:
# print('no frame')
@app.route('/')
def index():
return '<image src="/seasoncolor">'
@app.route('/seasoncolor')
def seasoncolor():
return Response(gen(), mimetype='multipart/x-mixed-replace; boundary=frame')
if __name__ == '__main__':
#app.debug = True
app.run()
顺便说一句：
确保：VideoCapture 只能与您 运行 网络服务器所在的本地摄像头一起使用。它不能与用户计算机上的远程摄像头一起使用。只有用户的浏览器可以访问其相机。要在用户计算机上使用远程摄像头，您必须使用 JavaScript 在用户浏览器中访问摄像头并将帧发送到服务器 - 就像我在 GitHub python-examples 中的示例：web camera in browser - canvas - take image and upload to server