0
点赞
收藏
分享

微信扫一扫

跟TED演讲学英文：The exciting, perilous journey toward AGI by Ilya Sutskever

蚁族的乐土 1天前 阅读 2
flask前端python

        怎么样在前端->选择视频文件->点击上传视频后->后端实时分析上传的视频->在前端展示后端分析结果（视频，文本）

↓

咱们先看整看整体代码，有个大概的印象。

Flask后端代码

'''
cljc车流检测Demo
'''
from pytz import timezone
from datetime import datetime

# 用于上传保存视频
@app.route('/upload', methods=['POST'])
def upload_video():
    VIDEOS_FOLDER = 'static\Videos'
    video = request.files['video']
    video.save(os.path.join(VIDEOS_FOLDER, '视频1.mp4'))
    return jsonify({'message': 'Video uploaded and saved successfully'}), 200

# 用于把后端处理的视频帧数据传输到前端展示
@app.route('/video_feed')
def video_feed():
    return Response(generate_frames(),
                    mimetype='multipart/x-mixed-replace; boundary=frame')

# 处理函数
def generate_frames():
    frame_Num = 1                                   
    max_cars = 0
    video_path = './static/Videos/视频1.mp4' # 必须固定一个位置，用于存放上传的视频文件
    cap = cv2.VideoCapture(video_path)
    fps = cap.get(cv2.CAP_PROP_FPS)              
    carsCascade = cv2.CascadeClassifier("car_rear.xml")  
    while cap.isOpened():
        success, frame = cap.read()
        if not success:
            break   
        cv2.putText(frame,"second:"+str(round(frame_Num/fps,2))+"s",
                        (0,100),cv2.FONT_HERSHEY_SIMPLEX,1,(255,0,255),1)
        cars = carsCascade.detectMultiScale(frame[700:1280,0:720], 1.2,minSize=(10,10))   
        for (x, y, w, h) in cars:  # 遍历所有汽车的区域
            cv2.rectangle(frame[700:1280,0:720], (x, y), (x + w, y + h), (0, 0, 255), 2)  

        # ！！！！将每一帧转换为JPEG格式并以字节流方式返回，！！！！！
        ret, buffer = cv2.imencode('.jpg', frame)
        frame = buffer.tobytes()
        frame_Num+=1
        yield (b'--frame\r\n'b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')

@app.route('/')     ###主页面路由
def index():
    return render_template('index.html')

HTML前端代码 

<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml" lang="en">
<head>
	<link rel="stylesheet" type="text/css" href="/static/css/cljc.css">
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta http-equiv="X-UA-Compatible" content="IE=edge">

<title>车流监测</title>
<style type="text/css">
body {
margin:0;
padding:0;
font-size:12px;
}

</style>
</head>
<body>
<div class="header">
    <div><style>* { box-sizing: border-box; } body {margin: 0;}
.c14101{padding:10px;
text-align:center;
font-weight:600;
color:#ffffff;
font-family:"Microsoft Yahei", sans-serif;
background-image:url(/static/img/bg3.jpg);
background-repeat:repeat;
background-position:left top;
background-attachment:scroll;
background-size:auto;}</style>
<div id="ib1w" class="c14101">车流监测</div></div>
</div>
<div class="colmask threecol">
<div class="colmid">
<div class="colleft">
<div class="col1">
<div>
    <style>* {
 box-sizing: border-box; 
} body {margin: 0;}
.c14101{padding:10px;
text-align:center;
font-weight:600;
color:#ffffff;
font-family:"Microsoft Yahei", sans-serif;
background-image:url(/static/img/bg1.jpg);
background-repeat:repeat;
background-position:left top;background-attachment:scroll;
background-size:auto;}
.htmlpage-row{display:table;
padding-top:10px;
padding-right:10px;
padding-bottom:10px;
padding-left:10px;
width:100%;}
.htmlpage-cell{
width:8%;
display:table-cell;height:75px;}
.c4195{height:400px;width:950px;
text-align:center;
position:relative;}
@media (max-width: 768px){
.htmlpage-cell{width:100%;display:block;}}

.footer {
    display: flex;
    justify-content: center;
    align-items: center;
    height: 50; /* 设置合适的高度 */
}

#upload-form {
    display: flex;
    flex-direction: column;
    /* align-items: center; */
}

</style>

<div class="htmlpage-row">
    <!-- <div class="htmlpage-cell"></div> -->
    <!-- <div class="htmlpage-cell">
        <video allowfullscreen="allowfullscreen" class="c4195" src="/static/img/video2.webm" controls="controls"></video>
    </div> -->
    <img src="{{ url_for('video_feed') }}" width="600px" height=590px">

    <!-- <div class="htmlpage-cell"></div> -->
</div>

</div>
</div>

<div class="col2"> 
    <div class="BoxConTop">当前帧数</div>
    <input type="text" id="frameNumber" name="frameNumber" readonly style="margin-top: -100px;">
    <div class="BoxConTop">当前车辆数</div>
    <input type="text" id="vehicleNumber" name="vehicleNumber" readonly style="margin-top: -100px;">
    <div class="BoxConTop">车流量峰值</div>
    <input type="text" id="peakTraffic" name="peakTraffic" readonly style="margin-top: -100px;">
</div>

<div class="col3">
    <p>北京时间</p>
    <input type="text" id="timeShow" name="timeWarning" readonly>
    <p>安全预警栏</p>
    <input type="text" id="safetyWarning" name="safetyWarning" readonly>
</div>

</div>
</div>
</div>
</div>
<div class="footer">
    <form id="upload-form">
        <input type="file" id="video" name="video" accept="video/*">
        <button type="submit">上传视频</button>
    </form>
</div>
<script src="https://cdn.socket.io/4.0.1/socket.io.min.js"></script>
<script>
    var socket = io();

    socket.on('update_data', function(data) {
        document.getElementById('frameNumber').value = data.frame_Num;
        document.getElementById('vehicleNumber').value = data.car_number;
        document.getElementById('peakTraffic').value = data.max_cars;
        document.getElementById('timeShow').value = data.timeShow;
        document.getElementById('safetyWarning').value = data.safetyWarning;
    });
</script>
</body>
<script>
    document.getElementById('upload-form').addEventListener('submit', async (e) => {
        e.preventDefault();
        const formData = new FormData(e.target);
        const response = await fetch('/upload', { method: 'POST', body: formData });
        const data = await response.json();
        console.log(data.message);
    });
    document.getElementById('play-btn').addEventListener('click', () => {
        const videoFrame = document.getElementById('video-frame');
        const source = new EventSource('/play');
        source.onmessage = (event) => {
            videoFrame.src = event.data;
        };
    });
</script>
</html>

代码可以创建一个.py文件，在编译软件（vscode,pycharm）中打开，这样看起来比较清晰。 

video_path = './static/Videos/视频1.mp4'

必须固定一个位置，这个位置是upload路由从前端传输过来视频数据，保存的地址，上面是处理函数generate_frames()里面读取的步骤。

下面是保存的步骤,在upload_video()路由：

 video.save(os.path.join(VIDEOS_FOLDER, '视频1.mp4')) #固定保存视频的地方，

二、前后端代码结合讲解

实现上传视频并保存在指定路径的功能！ 

@app.route('/upload', methods=['POST'])
def upload_video():
    VIDEOS_FOLDER = 'static\Videos'
    video = request.files['video']
    video.save(os.path.join(VIDEOS_FOLDER, '视频1.mp4')) #固定保存视频的地方，
    return jsonify({'message': 'Video uploaded and saved successfully'}), 200
<div class="footer">
    <form id="upload-form">
        <input type="file" id="video" name="video" accept="video/*">
        <button type="submit">上传视频</button>
    </form>
</div>

↓ 

传输在后端处理好的视频帧数据到前端展示

@app.route('/video_feed')
def video_feed():
    return Response(generate_frames(),
                    mimetype='multipart/x-mixed-replace; boundary=frame')
# 处理函数
def generate_frames():
    frame_Num = 1                                   
    max_cars = 0
    video_path = './static/Videos/视频1.mp4' # 必须固定一个位置，用于存放上传的视频文件
    cap = cv2.VideoCapture(video_path)
    fps = cap.get(cv2.CAP_PROP_FPS)              
    carsCascade = cv2.CascadeClassifier("car_rear.xml")  
    while cap.isOpened():
        success, frame = cap.read()
        if not success:
            break   
        cv2.putText(frame,"second:"+str(round(frame_Num/fps,2))+"s",
                        (0,100),cv2.FONT_HERSHEY_SIMPLEX,1,(255,0,255),1)
        cars = carsCascade.detectMultiScale(frame[700:1280,0:720], 1.2,minSize=(10,10))   
        for (x, y, w, h) in cars:  # 遍历所有汽车的区域
            cv2.rectangle(frame[700:1280,0:720], (x, y), (x + w, y + h), (0, 0, 255), 2)  

        # ！！！！将每一帧转换为JPEG格式并以字节流方式返回，！！！！！
        ret, buffer = cv2.imencode('.jpg', frame)
        frame = buffer.tobytes()
        frame_Num+=1
        yield (b'--frame\r\n'b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')

这是最关键的，其余都是处理函数。最后这一步将每一帧数据转换为了JPEG的格式并以字节流的方式返回。

        # ！！！！将每一帧转换为JPEG格式并以字节流方式返回，！！！！！
        # 1.转换为JPEG格式
        ret, buffer = cv2.imencode('.jpg', frame)
        # 2.转换为字节流
        frame = buffer.tobytes()
        # 3.通过路由函数发送给前端
        yield (b'--frame\r\n'b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')

yield (b'--frame\r\n'b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')

 通过上面这个方法yield（），把转换好的图像以字节流的方式传送给前端，那么前端如何接收到呢？这很简单，  

<div class="htmlpage-row">

    <img src="{{ url_for('video_feed') }}" width="600px" height=590px">

</div>
  • 前端HTML：“接收来自后端路由video_feed（）函数传过来的参数。”
  • 后端FLASK：“yield（）通过video_feed（）函数发送数据给前端。”
举报

相关推荐

跟TED演讲学英文：How AI could empower any business by Andrew Ng

论文阅读自动驾驶计算机视觉人工智能
0 条评论