Python 由于Flask集成的帧到字节导致OpenCV问题

我正在使用以下代码：

def gen_frames():  # generate frame by frame from camera
    while True:
        # Capture frame-by-frame
        success, frame = camera.read()  # read the camera frame
        if not success:
            break
        else:
            ret, buffer = cv2.imencode('.jpg', frame)
            frame = buffer.tobytes()
            yield (b'--frame\r\n'
                   b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')  # concat frame one by one and show result
            #frame_resized = cv2.resize(frame,None,fx=0.75,fy=0.75)
            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

我收到一个错误：

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
TypeError: Expected Ptr<cv::UMat> for argument 'src'

---

我应该如何使其工作？

已修复，需要移动一些代码。 现在的解决方案是：

from flask import Flask, render_template, Response
import numpy as np
import cv2
import pickle
import rtsp
import PIL as Image
import threading
import time
import queue

app = Flask(__name__)
url = 'rtsp://user:password@192.168.1.xxx:YYYY/stream0/mobotix.mjpeg'
#camera = cv2.VideoCapture(url)  # use 0 for web camera
#  for cctv camera use rtsp://username:password@ip_address:554/user=username_password='password'_channel=channel_number_stream=0.sdp' instead of camera
face_cascade = cv2.CascadeClassifier('cascades\data\haarcascade_frontalface_alt2.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("trainner.yml")

labels = {"person_name": 1}
with open("labels.pickle", 'rb') as f:
    og_labels = pickle.load(f)
    labels = {v:k for k,v in og_labels.items()}

class VideoCapture:

  def __init__(self, name):
    self.cap = cv2.VideoCapture(name)
    self.q = queue.Queue()
    t = threading.Thread(target=self._reader)
    t.daemon = True
    t.start()

  # read frames as soon as they are available, keeping only most recent one
  def _reader(self):
    while True:
      ret, frame = self.cap.read()
      if not ret:
        break
      if not self.q.empty():
        try:
          self.q.get_nowait()   # discard previous (unprocessed) frame
        except queue.Empty:
          pass
      self.q.put(frame)

  def read(self):
    return self.q.get()

def gen_frames():
    cap = VideoCapture(url)
    while True:
        time.sleep(.5)   # simulate time between events
        frame = cap.read()
        frame_detection(frame)
        ret, buffer = cv2.imencode('.jpg', frame)
        frame = buffer.tobytes()
        yield (b'--frame\r\n'
               b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')  # concat frame one by one and show result

def frame_detection(frame):
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=5)
    for (x,y,w,h) in faces:
      print(x,y,w,h)
      roi_gray = gray[y:y+h, x:x+w]
      roi_color = frame[y:y+h, x:x+w]
            
      #recognize?
      id_, conf = recognizer.predict(roi_gray)
      if conf>=45: # and conf <=85:
        print(id_)
        print(labels[id_])
        font = cv2.FONT_HERSHEY_SIMPLEX
        name = labels[id_]
        color = (0,0,255)
        stroke = 2
        cv2.putText(frame, name, (x,y), font, 1, color, stroke, cv2.LINE_AA)

        #img_item = "my-image.png"
        #cv2.imwrite(img_item, roi_gray)

        color = (0, 0, 255)
        stroke = 2
        end_cord_x = x + w
        end_cord_y = y + h
        cv2.rectangle(frame, (x,y), (end_cord_x, end_cord_y), color, stroke)
        return frame

@app.route('/video_feed')
def video_feed():
    """Video streaming route. Put this in the src attribute of an img tag."""
    return Response(gen_frames(),
                    mimetype='multipart/x-mixed-replace; boundary=frame')


@app.route('/')
def index():
    """Video streaming home page."""
    return render_template('index.html')


if __name__ == '__main__':
    app.run(host='0.0.0.0')

从烧瓶导入烧瓶，呈现模板，响应
将numpy作为np导入
进口cv2
进口泡菜
导入rtsp
将PIL作为图像导入
导入线程
导入时间
导入队列
app=烧瓶（名称）
url='1〕rtsp://user:password@192.168.1.xxx:YYYY/stream0/mobotix.mjpeg'
#摄像头=cv2.视频捕获（url）#将0用于网络摄像头
#供闭路电视摄影机使用rtsp://username:password@ip地址：554/user=username\u password='password'\u channel=channel\u number\u stream=0.sdp'而不是摄像头
face\u cascade=cv2.CascadeClassifier（'cascades\data\haarcascade\u frontalface\u alt2.xml'））
recognizer=cv2.face.LBPHFaceRecognizer_create（）
识别器读取（“trainer.yml”）
标签={“人名”：1}
将open（“labels.pickle”，“rb”）作为f：
og_标签=pickle.load（f）
labels={v:k代表k，在og_labels.items（）中为v
类视频捕获：
定义初始化（self，name）：
self.cap=cv2.VideoCapture（名称）
self.q=queue.queue（）
t=线程。线程（目标=自身。\读卡器）
t、 daemon=True
t、 开始（）
#帧可用时立即读取帧，只保留最新的帧
def_读卡器（自身）：
尽管如此：
ret，frame=self.cap.read（）
如果不是ret：
打破
如果不是self.q.empty（）：
尝试：
self.q.get_nowait（）#放弃上一个（未处理的）帧
队列除外。空：
通过
自q.put（帧）
def读取（自）：
返回self.q.get（）
def gen_框架（）：
cap=视频捕获（url）
尽管如此：
time.sleep（.5）#模拟事件之间的时间
frame=cap.read（）
帧检测（帧）
ret，buffer=cv2.imencode（'.jpg'，frame）
frame=buffer.tobytes（）
产量（b'--帧\r\n'
b'Content-Type:image/jpeg\r\n\r\n'+frame+b'\r\n'）#逐帧压缩并显示结果
def帧_检测（帧）：
灰色=cv2.CVT颜色（边框，cv2.COLOR\u BGR2GRAY）
faces=face_级联。检测多尺度（灰色，scaleFactor=1.3，minNeighbors=5）
对于面中的（x，y，w，h）：
打印（x、y、w、h）
roi_gray=灰色[y:y+h，x:x+w]
roi_color=帧[y:y+h，x:x+w]
#认识吗？
id\u，conf=recognizer.predict（roi\u灰色）
如果conf>=45:#和conf
from flask import Flask, render_template, Response
import numpy as np
import cv2
import pickle
import rtsp
import PIL as Image
import threading
import time
import queue

app = Flask(__name__)
url = 'rtsp://user:password@192.168.1.xxx:YYYY/stream0/mobotix.mjpeg'
#camera = cv2.VideoCapture(url)  # use 0 for web camera
#  for cctv camera use rtsp://username:password@ip_address:554/user=username_password='password'_channel=channel_number_stream=0.sdp' instead of camera
face_cascade = cv2.CascadeClassifier('cascades\data\haarcascade_frontalface_alt2.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("trainner.yml")

labels = {"person_name": 1}
with open("labels.pickle", 'rb') as f:
    og_labels = pickle.load(f)
    labels = {v:k for k,v in og_labels.items()}

class VideoCapture:

  def __init__(self, name):
    self.cap = cv2.VideoCapture(name)
    self.q = queue.Queue()
    t = threading.Thread(target=self._reader)
    t.daemon = True
    t.start()

  # read frames as soon as they are available, keeping only most recent one
  def _reader(self):
    while True:
      ret, frame = self.cap.read()
      if not ret:
        break
      if not self.q.empty():
        try:
          self.q.get_nowait()   # discard previous (unprocessed) frame
        except queue.Empty:
          pass
      self.q.put(frame)

  def read(self):
    return self.q.get()

def gen_frames():
    cap = VideoCapture(url)
    while True:
        time.sleep(.5)   # simulate time between events
        frame = cap.read()
        frame_detection(frame)
        ret, buffer = cv2.imencode('.jpg', frame)
        frame = buffer.tobytes()
        yield (b'--frame\r\n'
               b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')  # concat frame one by one and show result

def frame_detection(frame):
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=5)
    for (x,y,w,h) in faces:
      print(x,y,w,h)
      roi_gray = gray[y:y+h, x:x+w]
      roi_color = frame[y:y+h, x:x+w]
            
      #recognize?
      id_, conf = recognizer.predict(roi_gray)
      if conf>=45: # and conf <=85:
        print(id_)
        print(labels[id_])
        font = cv2.FONT_HERSHEY_SIMPLEX
        name = labels[id_]
        color = (0,0,255)
        stroke = 2
        cv2.putText(frame, name, (x,y), font, 1, color, stroke, cv2.LINE_AA)

        #img_item = "my-image.png"
        #cv2.imwrite(img_item, roi_gray)

        color = (0, 0, 255)
        stroke = 2
        end_cord_x = x + w
        end_cord_y = y + h
        cv2.rectangle(frame, (x,y), (end_cord_x, end_cord_y), color, stroke)
        return frame

@app.route('/video_feed')
def video_feed():
    """Video streaming route. Put this in the src attribute of an img tag."""
    return Response(gen_frames(),
                    mimetype='multipart/x-mixed-replace; boundary=frame')


@app.route('/')
def index():
    """Video streaming home page."""
    return render_template('index.html')


if __name__ == '__main__':
    app.run(host='0.0.0.0')