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• WARN : Tried to pass invalid video frame, marking as broken : Your frame has data type int64, but we require uint8

  5 septembre 2019, par Tavo Diaz

  I am doing some Udemy AI courses and came across with one that "teaches" a bidimensional cheetah how to walk. I was doing the exercises on my computer, but it takes too much time. I decided to use Google Cloud to run the code and see the results some hours after. Nevertheless, when I run the code I get the following error " WARN : Tried to pass
  invalid video frame, marking as broken : Your frame has data type int64, but we require uint8 (i.e. RGB values from 0-255)".

  After the code is executed, I see into the folder and I don’t see any videos (just the meta info).

  Some more info (if it helps) :
  I have a 1 CPU (4g), SSD Ubuntu 16.04 LTS

  I have not tried anything yet to solve it because I don´t know what to try. Im looking for solutions on the web, but nothing I could try.

  This is the code

  import os 
  
  import numpy as np
  
  import gym
  
  from gym import wrappers
  
  import pybullet_envs
  
  
  
  
  
  class Hp():
  
      def __init__(self):
  
          self.nb_steps = 1000
  
          self.episode_lenght =   1000
  
          self.learning_rate = 0.02
  
          self.nb_directions = 32
  
          self.nb_best_directions = 32
  
          assert self.nb_best_directions <= self.nb_directions
  
          self.noise = 0.03
  
          self.seed = 1
  
          self.env_name = 'HalfCheetahBulletEnv-v0'
  
  
  
  
  
  class Normalizer():
  
      def __init__(self, nb_inputs):
  
          self.n = np.zeros(nb_inputs)
  
          self.mean = np.zeros(nb_inputs)
  
          self.mean_diff = np.zeros(nb_inputs)
  
          self.var = np.zeros(nb_inputs)
  
  
  
      def observe(self, x):
  
          self.n += 1.
  
          last_mean = self.mean.copy()
  
          self.mean += (x - self.mean) / self.n
  
          #abajo es el online numerator update
  
          self.mean_diff += (x - last_mean) * (x - self.mean)
  
          #abajo online computation de la varianza
  
          self.var = (self.mean_diff / self.n).clip(min = 1e-2)  
  
  
  
      def normalize(self, inputs):
  
          obs_mean = self.mean
  
          obs_std = np.sqrt(self.var)
  
          return (inputs - obs_mean) / obs_std
  
  
  
  class Policy():
  
      def __init__(self, input_size, output_size):
  
          self.theta = np.zeros((output_size, input_size))
  
  
  
      def evaluate(self, input, delta = None, direction = None):
  
          if direction is None:
  
              return self.theta.dot(input)
  
          elif direction == 'positive':
  
              return (self.theta + hp.noise * delta).dot(input)
  
          else:
  
              return (self.theta - hp.noise * delta).dot(input)
  
  
  
      def sample_deltas(self):
  
          return [np.random.randn(*self.theta.shape) for _ in range(hp.nb_directions)]
  
  
  
      def update (self, rollouts, sigma_r):
  
          step = np.zeros(self.theta.shape)
  
          for r_pos, r_neg, d in rollouts:
  
              step += (r_pos - r_neg) * d
  
          self.theta += hp.learning_rate / (hp.nb_best_directions * sigma_r) * step
  
  
  
  
  
  def explore(env, normalizer, policy, direction = None, delta = None):
  
      state = env.reset()
  
      done = False
  
      num_plays = 0.
  
      #abajo puede ser promedio de las rewards
  
      sum_rewards = 0
  
      while not done and num_plays < hp.episode_lenght:
  
          normalizer.observe(state)
  
          state = normalizer.normalize(state)
  
          action = policy.evaluate(state, delta, direction)
  
          state, reward, done, _ = env.step(action)
  
          reward = max(min(reward, 1), -1)
  
          #abajo sería poner un promedio
  
          sum_rewards += reward
  
          num_plays += 1
  
      return sum_rewards
  
  
  
  def train (env, policy, normalizer, hp):
  
      for step in range(hp.nb_steps):
  
          #iniciar las perturbaciones deltas y los rewards positivos/negativos
  
          deltas = policy.sample_deltas()
  
          positive_rewards = [0] * hp.nb_directions
  
          negative_rewards = [0] * hp.nb_directions
  
          #sacar las rewards en la dirección positiva
  
          for k in range(hp.nb_directions):
  
              positive_rewards[k] = explore(env, normalizer, policy, direction = 'positive', delta = deltas[k])
  
          #sacar las rewards en dirección negativo
  
          for k in range(hp.nb_directions):
  
              negative_rewards[k] = explore(env, normalizer, policy, direction = 'negative', delta = deltas[k])
  
          #sacar todas las rewards para sacar la desvest
  
          all_rewards = np.array(positive_rewards + negative_rewards)
  
          sigma_r = all_rewards.std()
  
          #acomodar los rollauts por el max (r_pos, r_neg) y seleccionar la mejor dirección
  
          scores = {k:max(r_pos, r_neg) for k, (r_pos, r_neg) in enumerate(zip(positive_rewards, negative_rewards))}
  
          order = sorted(scores.keys(), key = lambda x:scores[x])[:hp.nb_best_directions]
  
          rollouts = [(positive_rewards[k], negative_rewards[k], deltas[k]) for k in order]
  
          #actualizar policy
  
          policy.update (rollouts, sigma_r)
  
          #poner el final reward del policy luego del update
  
          reward_evaluation = explore (env, normalizer, policy)
  
          print('Paso: ', step, 'Lejania: ', reward_evaluation)
  
  
  
  def mkdir(base, name):
  
      path = os.path.join(base, name)
  
      if not os.path.exists(path):
  
          os.makedirs(path)
  
      return path
  
  work_dir = mkdir('exp', 'brs')
  
  monitor_dir = mkdir(work_dir, 'monitor')
  
  
  
  hp = Hp()
  
  np.random.seed(hp.seed)
  
  env = gym.make(hp.env_name)
  
  env = wrappers.Monitor(env, monitor_dir, force = True)
  
  nb_inputs = env.observation_space.shape[0]
  
  nb_outputs = env.action_space.shape[0]
  
  policy = Policy(nb_inputs, nb_outputs)
  
  normalizer = Normalizer(nb_inputs)
  
  train(env, policy, normalizer, hp)

• Nodejs couldn't find the ffmpeg module for some reason

  29 décembre 2020, par Chawchawchaw

  I need to display the live streaming vidoe(rtsp) on a website(http, vue framework) with nodejs and vue framework.

  


  I've looked it up a lot and got the basic logic of what they are and how it works.
So I'm planning on to convert rtsp to hls with nodejs using socket.io and display it on a web.(let me know if there's more efficient way way to do it)

  


  The thing is, for some reason, when I try to develop it in my backend(nodejs), node just keep sends me an error that FFMpeg module wasn't found. It's been over a week.. please help.

  


  Btw, all works with ffmpeg cmd(window powerShell).

  


  How I set up(ffmpeg) :

  


  


  1. downloaded ffmpeg from https://ffmpeg.org/

     


  


  2. added to system path : C :\Users\Marie\Desktop\ffmpeg-4.3.1-2020-11-19-full_build\bin

     


  


  3. tested with window powerShell and converted rstp to m3u8 :

     


     ffmpeg -i 'rtsp ://ip.ip.ip/media/video1' -hls_time 3 -hls_wrap 10 'C :\Users\Marie\Desktop\tmp\hls/streaming.m3u8'

     


  


  


  below is a screen shot of no. 3 result


  


  ---

  


  how I set up(nodejs)

  


  

  1. npm i ffmpeg fluent-ffmpeg rtsp-ffmpeg

  


  2. I've just copied and pasted the example working code and changed rtsp link to mine. e.g : (https://www.npmjs.com/package/rtsp-ffmpeg)

  


  


  => didn't work out, error says can't find ffmpeg module

  


  

  3. set up path manually e.g.) ffmpeg.setFfmpegPath(path)

  


  


  => didn't work out. error says can't find ffmpeg module

  


  ...
I've seriously tried almost everything like delete, re-install ffmpeg, changed path, added path manyally, .. Please help....

  


  Edited :
package.json

  


  {
  "name": "streaming",
  "version": "1.0.0",
  "description": "",
  "main": "index.js",
  "scripts": {
    "start": "node app.js"
  },
  "author": "",
  "license": "ISC",
  "dependencies": {
    "express": "^4.17.1",
    "ffmpeg": "0.0.4",
    "fluent-ffmpeg": "^2.1.2",
    "jsmpeg": "^1.0.0",
    "node-media-server": "^2.2.4",
    "node-onvif": "^0.1.7",
    "node-rtsp-stream": "0.0.9",
    "rtsp-ffmpeg": "0.0.15",
    "socket.io": "^3.0.4",
    "ws": "^7.4.1"
  }
}


  


  app.js

  


  const Stream = require('node-rtsp-stream')

// let path = 'C:/Users/Marie/Desktop/ffmpeg-4.3.1-2020-11-19-full_build/bin/ffmpeg.exe'
// let path = 'C:/Users/Marie/Desktop/ffmpeg-4.3.1-2020-11-19-full_build/bin/'
let path = 'C:/Users/Marie/Desktop/ffmpeg-4.3.1-2020-11-19-full_build/bin'
const ffmpeg = require('fluent-ffmpeg')

ffmpeg.setFfmpegPath(path)

stream = new Stream({
  name: 'name',
  streamUrl: 'rtsp://ip.ip.ip.ip/media/video1',
  wsPort: 9999,
  ffmpegOptions: { // options ffmpeg flags
    '-stats': '', // an option with no neccessary value uses a blank string
    '-r': 30 // options with required values specify the value after the key
  }
})


  


  Error : spawn ffmpeg ENOENT

  


  app.js (for another test)

  


  const app = require( 'express' )(),
    server = require( 'http' ).Server( app ),
    io = require( 'socket.io' )( server ),
    rtsp = require( 'rtsp-ffmpeg' )

process.env.FFMPEG_PATH = 'C:/Users/Marie/Desktop/ffmpeg-4.3.1-2020-11-19-full_build/bin/ffmpeg.exe'
// console.log( rtsp.FFMpeg )

server.listen( 6147 )
var uri = 'rtsp://ip.ip.ip.ip/media/video1',
    stream = new rtsp.FFMpeg( { input: uri } )
io.on( 'connection', function ( socket )
{
    var pipeStream = function ( data )
    {
        socket.emit( 'data', data.toString( 'base64' ) )
    }
    stream.on( 'data', pipeStream )
    socket.on( 'disconnect', function ()
    {
        stream.removeListener( 'data', pipeStream )
    } )
} )
app.get( '/', function ( req, res )
{
    res.sendFile( __dirname + '/index.html' )
} )


  


  error :
FMpeg executable wasn't found. Install this package and check FFMpeg.cmd property

  


  nodejs version = 10.16.3

  


• Flutter_ffmpeg : At least one output file must be specified

  22 mars 2020, par Jehonadab Okpukoro

  I’m trying to crop a video with Flutter_ffmpeg package using this -i $inputPath -filter:v "crop=80:60:200:100" -c $outputPath, but I’m having this error message

  Running FFmpeg with arguments: [-i, /data/user/0/com.timz/app_flutter/Movies/flutter_test/1584827688309.mp4, -filter:v, crop=80:60:200:100, -c, /data/user/0/com.timz/cache/output.mp4].
  
  I/flutter (20728): ffmpeg version git-2020-01-25-fd11dd500
  
  I/flutter (20728):  Copyright (c) 2000-2020 the FFmpeg developers
  
  I/flutter (20728): 
  
  I/flutter (20728):   built with Android (5220042 based on r346389c) clang version 8.0.7 (https://android.googlesource.com/toolchain/clang b55f2d4ebfd35bf643d27dbca1bb228957008617) (https://android.googlesource.com/toolchain/llvm 3c393fe7a7e13b0fba4ac75a01aa683d7a5b11cd) (based on LLVM 8.0.7svn)
  
  I/flutter (20728):   configuration: --cross-prefix=aarch64-linux-android- --sysroot=/files/android-sdk/ndk-bundle/toolchains/llvm/prebuilt/linux-x86_64/sysroot --prefix=/home/taner/Projects/mobile-ffmpeg/prebuilt/android-arm64/ffmpeg --pkg-config=/usr/bin/pkg-config --enable-version3 --arch=aarch64 --cpu=armv8-a --cc=aarch64-linux-android24-clang --cxx=aarch64-linux-android24-clang++ --target-os=android --enable-neon --enable-asm --enable-inline-asm --enable-cross-compile --enable-pic --enable-jni --enable-optimizations --enable-swscale --enable-shared --disable-v4l2-m2m --disable-outdev=v4l2 --disable-outdev=fbdev --disable-indev=v4l2 --disable-indev=fbdev --enable-small --disable-openssl --disable-xmm-clobber-test --disable-debug --enable-lto --disable-neon-clobber-test --disable-programs --disable-postproc --disable-doc --disable-htmlpages --disable-manpages --disable-podpages --disable-txtpages --disable-static --disable-sndio --disable-schannel --disable-securetransport --disable-xlib --disable-cuda --disable-cuvid --disa
  
  I/flutter (20728):   libavutil      56. 38.100 / 56. 38.100
  
  I/flutter (20728):   libavcodec     58. 65.102 / 58. 65.102
  
  I/flutter (20728):   libavformat    58. 35.101 / 58. 35.101
  
  I/flutter (20728):   libavdevice    58.  9.103 / 58.  9.103
  
  I/flutter (20728):   libavfilter     7. 70.101 /  7. 70.101
  
  I/flutter (20728):   libswscale      5.  6.100 /  5.  6.100
  
  I/flutter (20728):   libswresample   3.  6.100 /  3.  6.100
  
  I/flutter (20728): Trailing option(s) found in the command: may be ignored.
  
  D/flutter-ffmpeg(20728): FFmpeg exited with rc: 1
  
  I/flutter (20728): Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/data/user/0/com.timz/app_flutter/Movies/flutter_test/1584827688309.mp4':
  
  I/flutter (20728):   Metadata:
  
  I/flutter (20728):     major_brand     : 
  
  I/flutter (20728): mp42
  
  I/flutter (20728): 
  
  I/flutter (20728):     minor_version   : 
  
  I/flutter (20728): 0
  
  I/flutter (20728): 
  
  I/flutter (20728):     compatible_brands: 
  
  I/flutter (20728): isommp42
  
  I/flutter (20728): 
  
  I/flutter (20728):     creation_time   : 
  
  I/flutter (20728): 2020-03-21T21:54:56.000000Z
  
  I/flutter (20728): 
  
  I/flutter (20728):     com.android.version: 
  
  I/flutter (20728): 9
  
  I/flutter (20728): 
  
  I/flutter (20728):   Duration: 
  
  I/flutter (20728): 00:00:07.17
  
  I/flutter (20728): , start: 
  
  I/flutter (20728): 0.000000
  
  I/flutter (20728): , bitrate: 
  
  I/flutter (20728): 3870 kb/s
  
  I/flutter (20728): 
  
  I/flutter (20728):     Stream #0:0
  
  I/flutter (20728): (eng)
  
  I/flutter (20728): : Video: h264 (avc1 / 0x31637661), yuv420p(tv, bt709), 720x480, 3854 kb/s
  
  I/flutter (20728): , SAR 1:1 DAR 3:2
  
  I/flutter (20728): , 
  
  I/flutter (20728): 29.44 fps, 
  
  I/flutter (20728): 29.83 tbr, 
  
  I/flutter (20728): 90k tbn, 
  
  I/flutter (20728): 180k tbc
  
  I/flutter (20728):  (default)
  
  I/flutter (20728): 
  
  I/flutter (20728):     Metadata:
  
  I/flutter (20728):       rotate          : 
  
  I/flutter (20728): 270
  
  I/flutter (20728): 
  
  I/flutter (20728):       creation_time   : 
  
  I/flutter (20728): 2020-03-21T21:54:56.000000Z
  
  I/flutter (20728): 
  
  I/flutter (20728):       handler_name    : 
  
  I/flutter (20728): VideoHandle
  
  I/flutter (20728): 
  
  I/flutter (20728):     Side data:
  
  I/flutter (20728):       
  
  I/flutter (20728): displaymatrix: rotation of 90.00 degrees
  
  I/flutter (20728): 
  
  I/flutter (20728):     Stream #0:1
  
  I/flutter (20728): (eng)
  
  I/flutter (20728): : Audio: aac (mp4a / 0x6134706D), 48000 Hz, mono, fltp, 12 kb/s
  
  I/flutter (20728):  (default)
  
  I/flutter (20728): 
  
  I/flutter (20728):     Metadata:
  
  I/flutter (20728):       creation_time   : 
  
  I/flutter (20728): 2020-03-21T21:54:56.000000Z
  
  I/flutter (20728): 
  
  I/flutter (20728):       handler_name    : 
  
  I/flutter (20728): SoundHandle
  
  I/flutter (20728): 
  
  I/flutter (20728): At least one output file must be specified

  I’ve been cracking my head with this for the past two days, kindly share your thoughts on what might wrong.