Question

我目前正在尝试使用网络摄像头使用Python设置面部识别程序。我已经在Python中设置了用于面部识别的代码，并且可以工作，但是我想通过Flask在HTML上流式传输视频（具有面部识别功能）。

当前，使用OpenCV面部识别显示流的代码为：

faces.py

import numpy as np
import cv2
import pickle

face_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_alt2.xml')
eye_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_eye.xml')
smile_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_smile.xml')


recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("./recognizers/face-trainner.yml")

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

cap = cv2.VideoCapture(0)

while(True):
    # Capture frame-by-frame
    ret, frame = cap.read()
    gray  = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.5, minNeighbors=5)
    for (x, y, w, h) in faces:
        #print(x,y,w,h)
        roi_gray = gray[y:y+h, x:x+w] #(ycord_start, ycord_end)
        roi_color = frame[y:y+h, x:x+w]

        # recognize? deep learned model predict keras tensorflow pytorch scikit learn
        id_, conf = recognizer.predict(roi_gray)
        if conf>=4 and conf <= 85:
            #print(5: #id_)
            #print(labels[id_])
            font = cv2.FONT_HERSHEY_SIMPLEX
            name = labels[id_]
            color = (255, 255, 255)
            stroke = 2
            cv2.putText(frame, name, (x,y), font, 1, color, stroke, cv2.LINE_AA)

        img_item = "8.png"
        cv2.imwrite(img_item, roi_color)

        color = (255, 0, 0) #BGR 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)
        #subitems = smile_cascade.detectMultiScale(roi_gray)
        #for (ex,ey,ew,eh) in subitems:
        #   cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
    # Display the resulting frame
    cv2.imshow('frame',frame)
    if cv2.waitKey(20) & 0xFF == ord('q'):
        break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()

这是我的Flask代码： stream.py

#!/usr/bin/env python
from flask import Flask, render_template, Response
import cv2
import sys
import numpy


app = Flask(__name__)

@app.route('/')
def index():
    return render_template('index.html')

def gen():
    i=1
    while i<10:
        yield (b'--frame\r\n'
            b'Content-Type: text/plain\r\n\r\n'+str(i)+b'\r\n')
        i+=1

def get_frame():

    camera_port=0

    ramp_frames=100

    camera=cv2.VideoCapture(camera_port) #this makes a web cam object


    i=1
    while True:
        retval, im = camera.read()
        imgencode=cv2.imencode('.jpg',im)[1]
        stringData=imgencode.tostring()
        yield (b'--frame\r\n'
            b'Content-Type: text/plain\r\n\r\n'+stringData+b'\r\n')
        i+=1

    del(camera)

@app.route('/calc')
def calc():
     return Response(get_frame(),mimetype='multipart/x-mixed-replace; boundary=frame')


if __name__ == '__main__':
    app.run(host='localhost', debug=True, threaded=True)

我的目标是在我的flask程序上流式传输我的OpenCV面部识别程序（运行stream.py后可以在HTML中显示）。

如何通过Flask将视频流从Python（面部识别后的OpenCV）转移到HTML？

0 个答案: