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Autres articles (77)

  • Websites made ​​with MediaSPIP

    2 mai 2011, par

    This page lists some websites based on MediaSPIP.

  • Creating farms of unique websites

    13 avril 2011, par

    MediaSPIP platforms can be installed as a farm, with a single "core" hosted on a dedicated server and used by multiple websites.
    This allows (among other things) : implementation costs to be shared between several different projects / individuals rapid deployment of multiple unique sites creation of groups of like-minded sites, making it possible to browse media in a more controlled and selective environment than the major "open" (...)

  • Other interesting software

    13 avril 2011, par

    We don’t claim to be the only ones doing what we do ... and especially not to assert claims to be the best either ... What we do, we just try to do it well and getting better ...
    The following list represents softwares that tend to be more or less as MediaSPIP or that MediaSPIP tries more or less to do the same, whatever ...
    We don’t know them, we didn’t try them, but you can take a peek.
    Videopress
    Website : http://videopress.com/
    License : GNU/GPL v2
    Source code : (...)

Sur d’autres sites (11034)

  • sent file using axios using passthrough stream module in nodejs

    12 août 2022, par Harikrushna Patel

    Imports

    


    const ffmpegPath = require('@ffmpeg-installer/ffmpeg').path;
const FfmpegCommand = require('fluent-ffmpeg');
const fs = require('fs');
const path = require('path');
const streamNode = require('stream');
const FormData = require('form-data');
const axios = require('axios').default;


    


    Code here

    


    async function audios() {
  let stream = fs.createReadStream(path.join(__dirname, '../videos/video.mp4'));
  let writeStream = fs.createWriteStream(path.join(__dirname, '../response/audios/' + +new Date() + '.wav'));
  let pass = new streamNode.PassThrough();
  let outputFile = path.join(__dirname, '../response/audios/' + +new Date() + '.wav');
  const ffmpeg = FfmpegCommand(file);

  ffmpeg
    .setFfmpegPath(ffmpegPath)
    .format('mp4')
    .toFormat('wav')
    .on('end', function () {
      console.log('file has been converted successfully');
    })
    .on('error', function (err, stdout, stderr) {
      console.log('an error happened: ' + err.message);
      console.log('ffmpeg stdout: ' + stdout);
      console.log('ffmpeg stderr: ' + stderr);
    })
    .on('end', function() {
      console.log('Processing finished !');
    })
    .stream(pass, { end: false })
    var bodyFormData = new FormData();
    bodyFormData.append('file', pass);
    let headers = bodyFormData.getHeaders(); 

    try {
      const jdata = await axios.post('http://localhost:4080/video',bodyFormData, {    maxContentLength: Infinity,
      maxBodyLength: Infinity,validateStatus: (status) => true ,headers:headers });
      console.log(jdata.data);
    } catch (error) {
      console.log("error" ,error.message);
    }

}


    


    I am getting errors to sent passthrough stream through formdata ;
issue is ffmpeg not creating readstrem so I am created passthrough from it and passed in formdata but not working right now

    


  • ffmpeg module saving not working after compression

    27 août 2022, par nickcoding2

    I'm just trying to save an mp4 to a different mp4 (before I even start playing around with the different compression settings). What exactly is going wrong here ?

    


    const ffmpeg = require('ffmpeg');

try {
    var process = new ffmpeg('./original.mp4');
    process.then(function (video) {
        video
        .save('./new.mp4', function (error, file) {
            if (!error) {
                console.log('Video file: ' + file);
            } else {
                console.log(error)
            }
        });
    }, function (err) {
        console.log('Error: ' + err);
    });
} catch (e) {
    console.log(e.code);
    console.log(e.msg);
}


    


    I get the following error :

    


    Error: Command failed: ffmpeg -i ./original.mp4  ./new.mp4
/bin/sh: ffmpeg: command not found

    at ChildProcess.exithandler (child_process.js:390:12)
    at ChildProcess.emit (events.js:400:28)
    at maybeClose (internal/child_process.js:1055:16)
    at Process.ChildProcess._handle.onexit (internal/child_process.js:288:5) {
  killed: false,
  code: 127,
  signal: null,
  cmd: 'ffmpeg -i ./original.mp4  ./new.mp4'
}


    


  • TypeError : expected str, bytes or os.PathLike object, not module when trying to sream openCv frames to rtmp server

    30 novembre 2022, par seriously

    I am using openCv and face-recognition api to detect a face using a webcam then compare it with a previously taken image to check and see if the people on both images are the same and the openCv and face-recognition part of the code works properly now what I am trying to achieve is to stream the openCv processed video frames to an rtmp server so for this I am trying to use ffmpeg and running the command using subprocess but when I run the code I get error TypeError: expected str, bytes or os.PathLike object, not module. But I am writing the frames as bytes to stdin hence p.stdin.write(frame.tobytes()). How can I fix it and properly stream my openCv frames to an rtmp server using ffmpeg. Thanks in advance.

    


    Traceback (most recent call last):&#xA;  File "C:\Users\blah\blah\test.py", line 52, in <module>&#xA;    p = subprocess.Popen(command, stdin=subprocess.PIPE, shell=False)&#xA;  File "C:\Python310\lib\subprocess.py", line 969, in __init__&#xA;    self._execute_child(args, executable, preexec_fn, close_fds,&#xA;  File "C:\Python310\lib\subprocess.py", line 1378, in _execute_child&#xA;    args = list2cmdline(args)&#xA;  File "C:\Python310\lib\subprocess.py", line 561, in list2cmdline&#xA;    for arg in map(os.fsdecode, seq):&#xA;  File "C:\Python310\lib\os.py", line 822, in fsdecode&#xA;    filename = fspath(filename)  # Does type-checking of `filename`.&#xA;TypeError: expected str, bytes or os.PathLike object, not module&#xA;</module>

    &#xA;

    import cv2&#xA;import numpy as np&#xA;import face_recognition&#xA;import os&#xA;import subprocess&#xA;import ffmpeg&#xA;&#xA;path = &#x27;../attendance_imgs&#x27;&#xA;imgs = []&#xA;classNames = []&#xA;myList = os.listdir(path)&#xA;&#xA;for cls in myList:&#xA;    curruntImg = cv2.imread(f&#x27;{path}/{cls}&#x27;)&#xA;    imgs.append(curruntImg)&#xA;    classNames.append(os.path.splitext(cls)[0])&#xA;&#xA;def findEncodings(imgs):&#xA;    encodeList = []&#xA;    for img in imgs:&#xA;        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)&#xA;        encode = face_recognition.face_encodings(img)[0]&#xA;        encodeList.append(encode)&#xA;    return encodeList&#xA;&#xA;encodeListKnown = findEncodings(imgs)&#xA;print(&#x27;Encoding Complete&#x27;)&#xA;&#xA;cap = cv2.VideoCapture(0)&#xA;&#xA;rtmp_url = "rtmp://127.0.0.1:1935/stream/webcam"&#xA;&#xA;fps = int(cap.get(cv2.CAP_PROP_FPS))&#xA;width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))&#xA;height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))&#xA;&#xA;# command and params for ffmpeg&#xA;command = [ffmpeg,&#xA;           &#x27;-y&#x27;,&#xA;           &#x27;-f&#x27;, &#x27;rawvideo&#x27;,&#xA;           &#x27;-vcodec&#x27;, &#x27;rawvideo&#x27;,&#xA;           &#x27;-pix_fmt&#x27;, &#x27;bgr24&#x27;,&#xA;           &#x27;-s&#x27;, "{}x{}".format(width, height),&#xA;           &#x27;-r&#x27;, str(fps),&#xA;           &#x27;-i&#x27;, &#x27;-&#x27;,&#xA;           &#x27;-c:v&#x27;, &#x27;libx264&#x27;,&#xA;           &#x27;-pix_fmt&#x27;, &#x27;yuv420p&#x27;,&#xA;           &#x27;-preset&#x27;, &#x27;ultrafast&#x27;,&#xA;           &#x27;-f&#x27;, &#x27;flv&#x27;,&#xA;           &#x27;rtmp://127.0.0.1:1935/stream/webcam&#x27;]&#xA;&#xA;p = subprocess.Popen(command, stdin=subprocess.PIPE, shell=False)&#xA;&#xA;&#xA;while True:&#xA;    ret, frame, success, img = cap.read()&#xA;    if not ret:&#xA;        print("frame read failed")&#xA;        break&#xA;    imgSmall = cv2.resize(img, (0,0), None, 0.25, 0.25)&#xA;    imgSmall = cv2.cvtColor(imgSmall, cv2.COLOR_BGR2RGB)&#xA;&#xA;    currentFrameFaces = face_recognition.face_locations(imgSmall)&#xA;    currentFrameEncodings = face_recognition.face_encodings(imgSmall, currentFrameFaces)&#xA;&#xA;    for encodeFace, faceLocation in zip(currentFrameEncodings, currentFrameFaces):&#xA;        matches = face_recognition.compare_faces(encodeListKnown, encodeFace)&#xA;        faceDistance = face_recognition.face_distance(encodeListKnown, encodeFace)&#xA;        matchIndex = np.argmin(faceDistance)&#xA;&#xA;        if matches[matchIndex]:&#xA;            name = classNames[matchIndex].upper()&#xA;            y1, x2, y2, x1 = faceLocation&#xA;            y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4 &#xA;            cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)&#xA;            cv2.rectangle(img, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)&#xA;            cv2.putText(img, name, (x1 &#x2B; 6, y2 - 6), cv2.FONT_HERSHEY_DUPLEX, 1, (255, 255, 255), 2) &#xA;&#xA;    # write to pipe&#xA;    p.stdin.write(frame.tobytes())&#xA;

    &#xA;