Recherche avancée

Sur d’autres sites (9026)

• 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>

  


  import cv2
import numpy as np
import face_recognition
import os
import subprocess
import ffmpeg

path = '../attendance_imgs'
imgs = []
classNames = []
myList = os.listdir(path)

for cls in myList:
    curruntImg = cv2.imread(f'{path}/{cls}')
    imgs.append(curruntImg)
    classNames.append(os.path.splitext(cls)[0])

def findEncodings(imgs):
    encodeList = []
    for img in imgs:
        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        encode = face_recognition.face_encodings(img)[0]
        encodeList.append(encode)
    return encodeList

encodeListKnown = findEncodings(imgs)
print('Encoding Complete')

cap = cv2.VideoCapture(0)

rtmp_url = "rtmp://127.0.0.1:1935/stream/webcam"

fps = int(cap.get(cv2.CAP_PROP_FPS))
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

# command and params for ffmpeg
command = [ffmpeg,
           '-y',
           '-f', 'rawvideo',
           '-vcodec', 'rawvideo',
           '-pix_fmt', 'bgr24',
           '-s', "{}x{}".format(width, height),
           '-r', str(fps),
           '-i', '-',
           '-c:v', 'libx264',
           '-pix_fmt', 'yuv420p',
           '-preset', 'ultrafast',
           '-f', 'flv',
           'rtmp://127.0.0.1:1935/stream/webcam']

p = subprocess.Popen(command, stdin=subprocess.PIPE, shell=False)


while True:
    ret, frame, success, img = cap.read()
    if not ret:
        print("frame read failed")
        break
    imgSmall = cv2.resize(img, (0,0), None, 0.25, 0.25)
    imgSmall = cv2.cvtColor(imgSmall, cv2.COLOR_BGR2RGB)

    currentFrameFaces = face_recognition.face_locations(imgSmall)
    currentFrameEncodings = face_recognition.face_encodings(imgSmall, currentFrameFaces)

    for encodeFace, faceLocation in zip(currentFrameEncodings, currentFrameFaces):
        matches = face_recognition.compare_faces(encodeListKnown, encodeFace)
        faceDistance = face_recognition.face_distance(encodeListKnown, encodeFace)
        matchIndex = np.argmin(faceDistance)

        if matches[matchIndex]:
            name = classNames[matchIndex].upper()
            y1, x2, y2, x1 = faceLocation
            y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4 
            cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
            cv2.rectangle(img, (x1, y2 - 35), (x2, y2), (0, 255, 0), cv2.FILLED)
            cv2.putText(img, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_DUPLEX, 1, (255, 255, 255), 2) 

    # write to pipe
    p.stdin.write(frame.tobytes())