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• even though my code is running without an error, it does not generate plot or video. I have xming runing

  23 octobre 2017, par Amin Abbasi

  This is my first code and I am really new to coding. I am trying to create a video or just plot my code.Eeven though my code is running without an error, I can’t get the video or the plot to generate. I have xming running and I have plotted a sample to make sure it not a computer Issue. I have also tried the following on GitHub but no success :
  https://jakevdp.github.io/blog/2013/05/19/a-javascript-viewer-for-matplotlib-animations/

  # -*- coding: utf-8 -*-
  
  import numpy as np
  
  def solver(I, V, f, c, L, dt, cc, T, user_action=None):
  
      """Solve u_tt=c^2*u_xx + f on (0,L)x(0,T]."""
  
      Nt = int(round(T/dt))
  
      t = np.linspace(0, Nt*dt, Nt+1) # Mesh points in time
  
      dx = dt*c/float(cc)
  
      Nx = int(round(L/dx))
  
      x = np.linspace(0, L, Nx+1) # Mesh points in space
  
      C2 = cc**2 # Help variable in the scheme
  
      # Make sure dx and dt are compatible with x and t
  
      dx = x[1] - x[0]
  
      dt = t[1] - t[0]
  
      if f is None or f == 0 :
  
          f = lambda x, t: 0
  
      if V is None or V == 0:
  
          V = lambda x: 0
  
      u       = np.zeros(Nx+1) # Solution array at new time level
  
      u_n     = np.zeros(Nx+1) # Solution at 1 time level back
  
      u_nm1   = np.zeros(Nx+1) # Solution at 2 time levels back
  
      import time; t0 = time.clock() # Measure CPU time
  
      # Load initial condition into u_n
  
      for i in range(0,Nx+1):
  
          u_n[i] = I(x[i])
  
      if user_action is not None:
  
          user_action(u_n, x, t, 0)
  
      # Special formula for first time step
  
      n = 0
  
      for i in range(1, Nx):
  
          u[i] = u_n[i] + dt*V(x[i]) + \
  
              0.5*C2*(u_n[i-1] - 2*u_n[i] + u_n[i+1]) + \
  
              0.5*dt**2*f(x[i], t[n])
  
      u[0] = 0; u[Nx] = 0
  
      if user_action is not None:
  
          user_action(u, x, t, 1)
  
      # Switch variables before next step
  
      u_nm1[:] = u_n; u_n[:] = u
  
      for n in range(1, Nt):
  
          # Update all inner points at time t[n+1]
  
          for i in range(1, Nx):
  
              u[i] = - u_nm1[i] + 2*u_n[i] + \
  
                      C2*(u_n[i-1] - 2*u_n[i] + u_n[i+1]) + \
  
                      dt**2*f(x[i], t[n])
  
          # Insert boundary conditions
  
          u[0] = 0; u[Nx] = 0
  
          if user_action is not None:
  
              if user_action(u, x, t, n+1):
  
                  break
  
          # Switch variables before next step
  
          u_nm1[:] = u_n; u_n[:] = u
  
      cpu_time = time.clock() - t0
  
      return u, x, t,
  
  def test_quadratic():
  
      """Check that u(x,t)=x(L-x)(1+t/2) is exactly reproduced."""
  
      def u_exact(x, t):
  
          return x*(L-x)*(1 + 0.5*t)
  
      def I(x):
  
          return u_exact(x, 0)
  
      def V(x):
  
          return 0.5*u_exact(x, 0)
  
      def f(x, t):
  
          return 2*(1 + 0.5*t)*c**2
  
      L = 2.5
  
      c = 1.5
  
      cc = 0.75
  
      Nx = 6 # Very coarse mesh for this exact test
  
      dt = cc*(L/Nx)/c
  
      T = 18
  
      def assert_no_error(u, x, t, n):
  
          u_e = u_exact(x, t[n])
  
          diff = np.abs(u - u_e).max()
  
          tol = 1E-13
  
          assert diff < tol
  
      solver(I, V, f, c, L, dt, cc, T,
  
              user_action=assert_no_error)
  
  def viz(
  
      I, V, f, c, L, dt, C, T,umin, umax, animate=True, tool='matplotlib'):
  
      """Run solver and visualize u at each time level."""
  
      def plot_u_st(u, x, t, n):
  
          """user_action function for solver."""
  
          plt.plot(x, u, 'r-')
  
  #                 xlabel='x', ylabel='u',
  
  #                 axis=[0, L, umin, umax],
  
  #                 title='t=%f' % t[n], show=True)
  
          # Let the initial condition stay on the screen for 2
  
          # seconds, else insert a pause of 0.2 s between each plot
  
          time.sleep(2) if t[n] == 0 else time.sleep(0.2)
  
          plt.savefig('frame_%04d.png' % n) # for movie making
  
      class PlotMatplotlib:
  
          def __call__(self, u, x, t, n):
  
              """user_action function for solver."""
  
              if n == 0:
  
                  plt.ion()
  
                  self.lines = plt.plot(x, u, 'r-')
  
                  plt.xlabel('x'); plt.ylabel('u')
  
                  plt.axis([0, L, umin, umax])
  
                  plt.legend(['t=%f' % t[n]], loc='lower left')
  
              else:
  
                  self.lines[0].set_ydata(u)
  
                  plt.legend(['t=%f' % t[n]], loc='lower left')
  
                  plt.draw()
  
              time.sleep(2) if t[n] == 0 else time.sleep(0.2)
  
              plt.savefig('tmp_%04d.png' % n) # for movie making
  
      if tool == 'matplotlib':
  
          import matplotlib.pyplot as plt
  
          plot_u = PlotMatplotlib()
  
      elif tool == 'scitools':
  
          import scitools.std as plt # scitools.easyviz interface
  
          plot_u = plot_u_st
  
      import time, glob, os
  
      # Clean up old movie frames
  
      for filename in glob.glob('tmp_*.png'):
  
          os.remove(filename)
  
      # Call solver and do the simulaton
  
      user_action = plot_u if animate else None
  
      u, x, t, cpu = solver_function(
  
          I, V, f, c, L, dt, C, T, user_action)
  
      # Make video files
  
      fps = 4 # frames per second
  
      codec2ext = dict(flv='flv', libx264='mp4', libvpx='webm',
  
                       libtheora='ogg') # video formats
  
      filespec = 'tmp_%04d.png'
  
      movie_program = 'ffmpeg' # or 'avconv'
  
      for codec in codec2ext:
  
          ext = codec2ext[codec]
  
          cmd = '%(movie_program)s -r %(fps)d -i %(filespec)s '\
  
                '-vcodec %(codec)s movie.%(ext)s' % vars()
  
          os.system(cmd)
  
      if tool == 'scitools':
  
          # Make an HTML play for showing the animation in a browser
  
          plt.movie('tmp_*.png', encoder='html', fps=fps,
  
                    output_file='movie.html')
  
      return cpu

• Is Replacing Dynamic Resolution with scale_amf in FFmpeg Command a Good Direction ?

  21 novembre 2024, par fred

  I'm working on a Lua script for MPV that processes 360-degree videos using FFmpeg's v360 filter. The original command dynamically calculates the output resolution based on a res variable, like this :

  


  mp.command_native_async({
    "no-osd", "vf", "add", 
    string.format(
        "@vrrev:v360=%s:%s:reset_rot=1:in_stereo=%s:out_stereo=2d:
id_fov=%s:d_fov=%.3f:yaw=%.3f:pitch=%s:roll=%.3f:
w=%s*192.0:h=%.3f*108.0:h_flip=%s:interp=%s",
        in_flip, inputProjection, outputProjection, in_stereo, idfov, dfov, yaw, pitch, roll, res, res, h_flip, scaling
    )
}, updateComplete)


  


  Change Proposal :

  


  I am considering replacing the dynamic width and height calculations with a scale_amf filter to handle scaling more efficiently and leverage GPU acceleration. The updated command would look like this :

  


  mp.command_native_async({
    "no-osd", "vf", "add", 
    string.format(
        "@vrrev:v360=%s:%s:reset_rot=1:in_stereo=%s:out_stereo=2d:
id_fov=%s:d_fov=%.3f:yaw=%.3f:pitch=%s:roll=%.3f,
%sscale_amf=w=%.0f:h=%.0f",
        inputProjection, outputProjection, in_stereo, idfov, dfov, yaw, pitch, roll, in_flip, res * 192.0, res * 108.0
    )


  


  Hardware Specifications :

  


  I am using an AMD Ryzen 5 5600G, no display card, 16GB RAM, Windows 10.

  


  Questions :

  


  Is using scale_amf for scaling a good direction in terms of performance and efficiency ?
Are there any potential drawbacks to this approach that I should be aware of ?
How does using scale_amf compare to the original dynamic resolution method in terms of output quality and processing speed ?
}, updateComplete)

  


  Any insights or experiences with this change would be greatly appreciated !

  


• ffmpeg throwing "errorMessage" : "spawn ffmpeg ENOENT"

  25 avril 2016, par user2792129

  My ffmpeg function thats running as a shell command isnt working. I think its because ’ffmpeg’ isnt really referring to anything. I have the ffmpeg node module in my bundle, but i dont know the execFile command is referring to it here.

  Im following aws-lambda-ffmpeg as an example of how to call this particular function. They are referring to ’ffmpeg’ as a 64-bit linux build they created from John Vansickle’s static FFMPEG builds in their gulp function.

  I want to know how to replace ’ffmpeg’ with something that will just recognize it like a node_module without having to do the whole gulp static build process. To my understanding the only reason they are doing that is to get the latest build which i really dont need.

  If I am wrong and a static build using gulp is needed for another reason please let me know.

  function ffmpegProcess(description, cb) {
  
  console.log('Starting FFmpeg');
  
  
  
  child_process.execFile(
  
      'ffmpeg',
  
      [
  
          '-y',
  
          '-loglevel', 'warning',
  
          '-i', 'download',
  
          '-c:a', 'copy',
  
          '-vf', scaleFilter,
  
          '-movflags', '+faststart',
  
          '-metadata', 'description=' + description,
  
          'out.' + config.format.video.extension,
  
          '-vf', 'thumbnail',
  
          '-vf', scaleFilter,
  
          '-vframes', '1',
  
          'out.' + config.format.image.extension
  
      ],
  
      {
  
          cwd: tempDir
  
      },
  
      function(err, stdout, stderr) {
  
          console.log('FFmpeg done.');
  
          return cb(err, 'FFmpeg finished:' + JSON.stringify({ stdout: stdout, stderr: stderr}));
  
      }
  
  );
  
  }