流式传输到网站而不是Window OpenCV

Question

Human Recogition Program

class PeopleTracker：

hog = cv2.HOGDescriptor()
caps = cv2.VideoCapture(r'C:/Users/Emyr/Documents/Jupyter/pedestrian-detection/video/Ped4.MOV')
count = int(caps.get(cv2.CAP_PROP_FRAME_COUNT))
center = []
recCount = 0
pick = 0
#          Red       Yellow      Blue      Green     Purple 
colors = [(255,0,0),(255,255,0),(0,0,255),(0,128,0),(128,0,128)]

def BBoxes(self, frame):
    #frame = imutils.resize(frame, width = min(frame.shape[0], frame.shape[1]))
    frame = imutils.resize(frame, width= 1000,height = 1000)

    # detect people in the image
    (rects, weights) = self.hog.detectMultiScale(frame, winStride=(1,1), padding=(3, 3), scale=0.5)

    # apply non-maxima suppression to the bounding boxes using a
    # fairly large overlap threshold to try to maintain overlapping
    # boxes that are still people

    rects = np.array([[x, y, x + w, y + h] for (x, y, w, h) in rects])

    self.pick = non_max_suppression(rects, probs=None, overlapThresh=0.7)

    # draw the final bounding boxes
    self.recCount  = 0

    for (xA, yA, xB, yB) in self.pick:

        #cv2.rectangle(frame, (xA, yA), (xB, yB), (0, 255, 0), 2)

        CentxPos = int((xA + xB)/2)
        CentyPos = int((yA + yB)/2)

        cv2.circle(frame,(CentxPos, CentyPos), 5, (0,255,0), -1)
        self.recCount += 1

        if len(rects) >1:
               self.center.append([CentxPos, CentyPos])


    return frame


def Clustering(self, frame):

    db = DBSCAN(eps= 70, min_samples = 2).fit(self.center)

    labels = db.labels_

    # Number of clusters in labels, ignoring noise if present.
    n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)
    n_noise_ = list(labels).count(-1)
    #print("Labels: ", labels)
    # Black removed and is used for noise instead.
    unique_labels = set(labels)
    #print("Unique Labels: ", unique_labels)

    #colors = plt.cm.rainbow(np.linspace(0, 255, len(unique_labels)))

    #colors = [(random.randint(0, 255), random.randint(0, 255), random.randint(0, 255)) for k in range(len(unique_labels)) ]

    #print(self.colors)

    i = 0

    for (xA, yA, xB, yB) in self.pick:

        if labels[i] == -1:
            cv2.rectangle(frame, (xA, yA), (xB, yB), (0, 0, 0), 2)
            i += 1
        else:

            cv2.rectangle(frame, (xA, yA), (xB, yB), (self.colors[labels[i]][0], self.colors[labels[i]][1], self.colors[labels[i]][2]), 2)
            i += 1


    #print("Colours: ", colors)
    center = np.asarray(self.center)

    #fig, ax = plt.subplots()

    #ax.set_xlim(0,frame.shape[1])
    #ax.set_ylim(frame.shape[0], 0)

    #for k, col in zip(unique_labels, colors):

        #if k == -1:
             #Black used for noise.
             #col = [0, 0, 0, 1]

        #class_member_mask = (labels == k)
        #xy = center[class_member_mask]
        #plt.plot(xy[:, 0], xy[:, 1], 'o', markerfacecolor=tuple(col), markeredgecolor='k', markersize=8)

def main（）：

PT = PeopleTracker()
PT.hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())



while PT.count > 1:

    PT.center = []

    ret, frame = PT.caps.read()

    frame = PT.BBoxes(frame)

    if PT.recCount >= 2:

        PT.Clustering(frame)


        #plt.title('Estimated number of clusters: %d' % n_clusters_)
        #plt.show()   
        cv2.imshow("Tracker", frame)
        cv2.waitKey(1)
        #cv2.destroyAllWindows()
        PT.count = PT.count - 1

    else:

        cv2.imshow("Tracker", frame)
        cv2.waitKey(1)
        #cv2.destroyAllWindows()
        PT.count = PT.count - 1

我目前在这里的代码将一个现有人类识别视频的流显示到一个窗口（如链接中的图片所示），如果可能的话，我想知道是否有一种方法可以将该视频源发送到一个网站我开发而不是使用窗口？

先感谢您 ：）

Answer 1

我有半工作，我最终使用烧瓶，但问题是，我显示原始视频而不是opencv我生成的视频我想知道是否有人有任何想法如何我可以实现以前的代码到这？并使用“frame”变量作为视频Feed

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():
    ramp_frames=100

    camera=cv2.VideoCapture('IMG_2649.MOV')

    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)

HTML代码

   <html>
      <head>
        <title>Video Streaming Demonstration</title>
      </head>
      <body>
        <h1>Video Streaming Demonstration</h1>
        <img src="{{ url_for('calc') }}">
        <!-- <h1>{{ url_for('calc') }}</h1> -->
      </body>
    </html>