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• FFMPEG(?) Error : [out#0/s16le @ 000002452f906a00] Output file does not contain any stream

  11 mars 2024, par Ondosh

  FFMPEG_OPTIONS = {
    'before_options': '-reconnect 1 -reconnect_streamed 1 -reconnect_delay_max 5',
    'options': '-vn'}
YDL_OPTIONS = {
    'format': 'bestaudio/best',
    'extractaudio': True,
    'noplaylist': True,
    'simulate': 'True',
    'preferredquality': '192',
    'preferredcodec': 'mp3',
    'key': 'FFmpegExtractAudio'}
@bot.command(aliases=['Ping', 'PING', 'Пинг', 'ПИНГ', 'зштп', 'ЗШТП', 'Зштп',
                      'пинг'])
async def ping(ctx):
    await ctx.message.reply(f'Ping: {round(bot.latency * 1000)}ms')
#########################[PLAY MUSIC BLOCK]#########################
@bot.command()
async def add(ctx, *url):
    url = ' '.join(url)
    with yt_dlp.YoutubeDL(YDL_OPTIONS) as ydl:
        try:
            info = ydl.extract_info(url, download=False)
        except:
            info = ydl.extract_info(f"ytsearch:{url}",
                                    download=False)['entries'][0]

    URL = info['formats'][0]['url']
    name = info['title']
    time = str(datetime.timedelta(seconds=info['duration']))
    songs_queue.q_add([name, time, URL])
    embed = nextcord.Embed(description=f'Записываю [{name}]({url}) в очередь 📝',
                           colour=nextcord.Colour.red())
    await ctx.message.reply(embed=embed)
def step_and_remove(voice_client):
    if loop_flag:
        songs_queue.q_add(songs_queue.get_value()[0])
    songs_queue.q_remove()
    audio_player_task(voice_client)
def audio_player_task(voice_client):
    if not voice_client.is_playing() and songs_queue.get_value():
        voice_client.play(nextcord.FFmpegPCMAudio(
            executable="ffmpeg\\bin\\ffmpeg.exe",
            source=songs_queue.get_value()[0][2],
            **FFMPEG_OPTIONS),
            after=lambda e: step_and_remove(voice_client))
@bot.command(aliases=['Play', 'PLAY', 'играй', 'ИГРАЙ', 'Играй', 'сыграй',
                      'Сыграй', 'СЫГРАЙ', 'здфн', 'Здфн', 'ЗДФН', 'p', 'P',
                      'pl', 'PL', 'Pl', 'Плей',
                      'ПЛЕЙ', 'плей'])
async def play(ctx, *url):
    await join(ctx)
    await add(ctx, ' '.join(url))
    await ctx.message.add_reaction(emoji='🎸')
    voice_client = ctx.guild.voice_client
    audio_player_task(voice_client)
@bot.command(aliases=['Queue', 'QUEUE', 'йгугу', 'Йгугу', 'ЙГУГУ', 'очередь',
                      'Очередь', 'ОЧЕРЕДЬ', 'список', 'Список', 'СПИСОК',
                      'list', 'List', 'LIST', 'дшые', 'Дшые', 'ДШЫЕ', 'Лист',
                      'лист', 'ЛИСТ', 'песни', 'Песни', 'ПЕСНИ', 'songs',
                      'Songs', 'SONGS', 'ыщтпы', 'ЫЩТПЫ', 'Ыщтпы', 'q'])
async def queue(ctx):
    if len(songs_queue.get_value()) > 0:
        only_names_and_time_queue = []
        for i in songs_queue.get_value():
            name = i[0]
            if len(i[0]) > 30:
                name = i[0][:30] + '...'
            only_names_and_time_queue.append(f'📀 `{name:<33}   {i[1]:>20}`\n')
        c = 0
        queue_of_queues = []
        while c < len(only_names_and_time_queue):
            queue_of_queues.append(only_names_and_time_queue[c:c + 10])
            c += 10

        embed = nextcord.Embed(title=f'ОЧЕРЕДЬ [LOOP: {loop_flag}]',
                               description=''.join(queue_of_queues[0]),
                               colour=nextcord.Colour.red())
        await ctx.send(embed=embed)

        for i in range(1, len(queue_of_queues)):
            embed = nextcord.Embed(description=''.join(queue_of_queues[i]),
                                   colour=nextcord.Colour.red())
            await ctx.send(embed=embed)
    else:
        await ctx.send('Очередь пуста')


  


  There is the part of my music bot in Discord, I don't really know why it doesn't work. Actually, I tried to use someone's old code, so it needs to be fixed. I have cut out the most important parts of the code, which most likely had an error.
I found other questions, but there was another errors.
After trying to start the video, I get the following errors :
[out#0/s16le @ 000002452f906a00] Output file does not contain any stream
Error opening output file pipe:1.
Error opening output files : Invalid argument

  


• Can't view and record graph at the same time using FFMpegWriter [closed]

  7 juillet 2024, par Barkın Özer

  So this code is used for graphing and logging sensor data coming from bluetooth ports. I wanted to add an function that will record the graph in mp4 format. In order to achieve this I used ffmpegWriter. The issue is while this code records the graph I can't view the graph at the same time.

  


  import serial
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation, FFMpegWriter
import openpyxl
from datetime import datetime

# Constants
GRAVITY = 9.81  # Standard gravity in m/s²

# Initialize serial connections to HC-06 devices
ser_x_accel = serial.Serial('COM4', 9600, timeout=1)  # X-axis acceleration data
ser_y_angle = serial.Serial('COM11', 9600, timeout=1)  # Y-axis angle data

# Initialize empty lists to store data
x_accel_data = []
y_angle_data = []
timestamps = []

# Initialize Excel workbook
wb = openpyxl.Workbook()
ws = wb.active
ws.title = "Sensor Data"
ws.append(["Timestamp", "X Acceleration (m/s²)", "Y Angle (degrees)"])

# Function to update the plot and log data
def update(frame):
    # Read data from serial connections
    line_x_accel = ser_x_accel.readline().decode('utf-8').strip()
    line_y_angle = ser_y_angle.readline().decode('utf-8').strip()
    
    try:
        # Parse and process X-axis acceleration data
        x_accel_g = float(line_x_accel)  # Acceleration in g read from serial
        x_accel_ms2 = x_accel_g * GRAVITY  # Convert from g to m/s²
        x_accel_data.append(x_accel_ms2)
        
        # Parse and process Y-axis angle data
        y_angle = float(line_y_angle)
        y_angle_data.append(y_angle)
        
        # Append timestamp
        timestamps.append(datetime.now())

        # Limit data points to show only the latest 100
        if len(x_accel_data) > 100:
            x_accel_data.pop(0)
            y_angle_data.pop(0)
            timestamps.pop(0)

        # Log data to Excel with timestamp
        timestamp_str = timestamps[-1].strftime("%H:%M:%S")
        ws.append([timestamp_str, x_accel_data[-1], y_angle_data[-1]])

        # Clear and update plots
        ax1.clear()
        ax1.plot(timestamps, x_accel_data, label='X Acceleration', color='b')
        ax1.legend(loc='upper left')
        ax1.set_ylim([-20, 20])  # Adjust based on expected acceleration range in m/s²
        ax1.set_title('Real-time X Acceleration Data')
        ax1.set_xlabel('Time')
        ax1.set_ylabel('Acceleration (m/s²)')
        ax1.grid(True)

        ax2.clear()
        ax2.plot(timestamps, y_angle_data, label='Y Angle', color='g')
        ax2.legend(loc='upper left')
        ax2.set_ylim([-180, 180])
        ax2.set_title('Real-time Y Angle Data')
        ax2.set_xlabel('Time')
        ax2.set_ylabel('Angle (degrees)')
        ax2.grid(True)

        # Update text boxes with latest values
        text_box.set_text(f'X Acceleration: {x_accel_data[-1]:.2f} m/s²')
        text_box2.set_text(f'Y Angle: {y_angle_data[-1]:.2f}°')
        
        # Save the workbook periodically (every 100 updates)
        if frame % 100 == 0:
            wb.save("sensor_data.xlsx")
        
    except ValueError:
        pass  # Ignore lines that are not properly formatted

# Setup the plots
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8))
text_box = ax1.text(0.05, 0.95, '', transform=ax1.transAxes, fontsize=12, verticalalignment='top', bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))
text_box2 = ax2.text(0.05, 0.95, '', transform=ax2.transAxes, fontsize=12, verticalalignment='top', bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))

# Animate the plots
ani = FuncAnimation(fig, update, interval=100)  # Update interval of 100ms

# Save the animation as a video file
writer = FFMpegWriter(fps=10, metadata=dict(artist='Me'), bitrate=1800)
ani.save("sensor_data.mp4", writer=writer)

plt.tight_layout()
plt.show()

# Save the workbook at the end of the session
wb.save("sensor_data.xlsx")



  


  I tried using OpenCV to record the graph but then I didn't even got any recording. I think solving this issue with my original code would be a better approach.

  


• Issue with streaming in realtime to HTML5 video player

  24 juillet 2023, par ImaSquareBTW

  ok so i created a project which should take an mkv file convert it to a sutaible fomrat in relatime and play it as it transcodes in the html 5 video player and should play as soon as small segement is ready for playback but unfornatlly it does seem to work heres my code if your curious, help would be very much appreicted

  


  &#xA;&#xA;  &#xA;    &#xA;  &#xA;  &#xA;    <video controls="controls">&#xA;      <source src="output.mp4" type="video/mp4">&#xA;    </source></video>&#xA;    <code class="echappe-js">&lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/ffmpeg/0.11.6/ffmpeg.min.js&quot; integrity=&quot;sha512-91IRkhfv1tLVYAdH5KTV&amp;#x2B;KntIZP/7VzQ9E/qbihXFSj0igeacWWB7bQrdiuaJVMXlCVREL4Z5r&amp;#x2B;3C4yagAlwEw==&quot; crossorigin=&quot;anonymous&quot; referrerpolicy=&quot;no-referrer&quot;&gt;&lt;/script&gt;&#xA;    &lt;script src='http://stackoverflow.com/feeds/tag/player.js'&gt;&lt;/script&gt;&#xA;  &#xA;&#xA;

  


  and my javscript :

  


  let mediaSource;
let sourceBuffer;
let isTranscoding = false;
let bufferedSeconds = 0;

async function setupMediaSource() {
  mediaSource = new MediaSource();
  const videoPlayer = document.getElementById('video-player');
  videoPlayer.src = URL.createObjectURL(mediaSource);
  await new Promise(resolve => {
    mediaSource.addEventListener('sourceopen', () => {
      sourceBuffer = mediaSource.addSourceBuffer('video/mp4; codecs="avc1.64001E, mp4a.40.2"'); // Match the transcoded format
      sourceBuffer.addEventListener('updateend', () => {
        if (!sourceBuffer.updating && mediaSource.readyState === 'open') {
          mediaSource.endOfStream();
          resolve();
        }
      });
    });
  });
}

async function transcodeVideo() {
  const ffmpeg = createFFmpeg({ log: true });
  const videoPlayer = document.getElementById('video-player');

  await ffmpeg.load();
  const transcodeCommand = ['-i', 'The Legend of Old Gregg S02E05.mkv', '-c:v', 'libx264', '-preset', 'ultrafast', '-c:a', 'aac', '-strict', 'experimental', '-f', 'mp4', '-movflags', 'frag_keyframe+empty_moov', 'output.mp4'];

  const videoUrl = 'The Legend of Old Gregg S02E05.mkv'; // The URL of the original video file

  let lastBufferedSeconds = 0;
  let currentTime = 0;
  while (currentTime < videoPlayer.duration) {
    if (!isTranscoding && sourceBuffer.buffered.length > 0 && sourceBuffer.buffered.end(0) - currentTime < 5) {
      isTranscoding = true;
      const start = sourceBuffer.buffered.end(0);
      const end = Math.min(videoPlayer.duration, start + 10);
      await fetchAndTranscode(videoUrl, start, end, ffmpeg, transcodeCommand);
      isTranscoding = false;
      currentTime = end;
      bufferedSeconds += (end - start);
      const transcodingSpeed = bufferedSeconds / (currentTime);
      lastBufferedSeconds = bufferedSeconds;
      console.log(`Transcoded ${end - start} seconds of video. Buffered: ${bufferedSeconds.toFixed(2)}s (${transcodingSpeed.toFixed(2)}x speed)`);
    }
    await new Promise(resolve => setTimeout(resolve, 500));
  }

  await ffmpeg.exit();
}

async function fetchAndTranscode(url, start, end, ffmpeg, transcodeCommand) {
  const response = await fetch(url, { headers: { Range: `bytes=${start}-${end}` } });
  const data = new Uint8Array(await response.arrayBuffer());
  ffmpeg.FS('writeFile', 'input.mkv', data); // Use 'input.mkv' as a temporary file
  await ffmpeg.run(...transcodeCommand);
  const outputData = ffmpeg.FS('readFile', 'output.mp4');
  appendSegmentToBuffer(outputData);
}

function appendSegmentToBuffer(segment) {
  if (!sourceBuffer.updating) {
    sourceBuffer.appendBuffer(segment);
  } else {
    sourceBuffer.addEventListener('updateend', () => {
      sourceBuffer.appendBuffer(segment);
    });
  }
}

async function createFFmpeg(options) {
  const { createFFmpeg } = FFmpeg;
  const ffmpeg = createFFmpeg(options);
  await ffmpeg.load();
  return ffmpeg;
}

(async () => {
  await setupMediaSource();
  await transcodeVideo();
})();