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• Video out of LinkedList sequence

  14 janvier 2020, par Marks Gniteckis

  I just started working on a side project to learn JavaFX 13 and the idea is to play a sequence of frames like a video without saving the actual video or frames in temp folders. I’d like to buffer images and output them onto ImageView at 30fps. Here is what I’ve got so far :

  The method that buffers images -

  @FXML void takeVideo(ActionEvent event)
  
              throws InterruptedException {
  
          model.purgeBufferedVideo();
  
          Timer timer = new Timer();
  
          long startedAt = System.currentTimeMillis();
  
          TimerTask task = new TimerTask() {
  
              @Override public void run() {
  
                  while (System.currentTimeMillis() < startedAt + (1000 * Long.parseLong(s.getText()))) {
  
                      generateVideo(new Rectangle(Toolkit.getDefaultToolkit()
  
                              .getScreenSize()));
  
                      System.out.println(System.currentTimeMillis() != startedAt + (1000 * Long
  
                              .parseLong(s.getText())));
  
                  }
  
                  cancel();
  
                  System.out.println("Video buffered");
  
              }
  
          };
  
          timer.schedule(task, 0L);
  
      }

  Method to output images onto ImageView -

  @FXML void playVideo(ActionEvent event) {
  
          model.getBufferedVideo().forEach(i -> {
  
  
  
              try {
  
                  preview.setImage(i);
  
                  Thread.sleep((60000 / Long.parseLong(s.getText()))/30);
  
                  preview.setImage(i);
  
              } catch (InterruptedException e) {
  
                  e.printStackTrace();
  
              }
  
          });
  
      }

  List population is working but only last image in the list is displayed in the ImageView and I can’t really get my head around why... Thanks in advance to everyone !

• vf_dnn_processing : remove parameter 'fmt'

  27 décembre 2019, par Guo, Yejun

  vf_dnn_processing : remove parameter 'fmt'
  do not request AVFrame's format in vf_ddn_processing with 'fmt',
  
  but to add another filter for the format.
  command examples :
  
  ./ffmpeg -i input.jpg -vf format=bgr24,dnn_processing=model=halve_first_channel.model:input=dnn_in:output=dnn_out:dnn_backend=native -y out.native.png
  
  ./ffmpeg -i input.jpg -vf format=rgb24,dnn_processing=model=halve_first_channel.model:input=dnn_in:output=dnn_out:dnn_backend=native -y out.native.png
  Signed-off-by : Guo, Yejun <yejun.guo@intel.com>
  
  Signed-off-by : Pedro Arthur <bygrandao@gmail.com>
  

  • [DH] doc/filters.texi
  • [DH] libavfilter/vf_dnn_processing.c

• vf_dnn_processing : add support for more formats gray8 and grayf32

  27 décembre 2019, par Guo, Yejun

  vf_dnn_processing : add support for more formats gray8 and grayf32
  The following is a python script to halve the value of the gray
  
  image. It demos how to setup and execute dnn model with python+tensorflow.
  
  It also generates .pb file which will be used by ffmpeg.
  import tensorflow as tf
  
  import numpy as np
  
  from skimage import color
  
  from skimage import io
  
  in_img = io.imread('input.jpg')
  
  in_img = color.rgb2gray(in_img)
  
  io.imsave('ori_gray.jpg', np.squeeze(in_img))
  
  in_data = np.expand_dims(in_img, axis=0)
  
  in_data = np.expand_dims(in_data, axis=3)
  
  filter_data = np.array([0.5]).reshape(1,1,1,1).astype(np.float32)
  
  filter = tf.Variable(filter_data)
  
  x = tf.placeholder(tf.float32, shape=[1, None, None, 1], name='dnn_in')
  
  y = tf.nn.conv2d(x, filter, strides=[1, 1, 1, 1], padding='VALID', name='dnn_out')
  
  sess=tf.Session()
  
  sess.run(tf.global_variables_initializer())
  
  graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
  
  tf.train.write_graph(graph_def, '.', 'halve_gray_float.pb', as_text=False)
  
  print("halve_gray_float.pb generated, please use \
  
  path_to_ffmpeg/tools/python/convert.py to generate halve_gray_float.model\n")
  
  output = sess.run(y, feed_dict=x : in_data)
  
  output = output * 255.0
  
  output = output.astype(np.uint8)
  
  io.imsave("out.jpg", np.squeeze(output))
  To do the same thing with ffmpeg :
  
   generate halve_gray_float.pb with the above script
  
   generate halve_gray_float.model with tools/python/convert.py
  
   try with following commands
  
    ./ffmpeg -i input.jpg -vf format=grayf32,dnn_processing=model=halve_gray_float.model:input=dnn_in:output=dnn_out:dnn_backend=native out.native.png
  
    ./ffmpeg -i input.jpg -vf format=grayf32,dnn_processing=model=halve_gray_float.pb:input=dnn_in:output=dnn_out:dnn_backend=tensorflow out.tf.png
  Signed-off-by : Guo, Yejun <yejun.guo@intel.com>
  
  Signed-off-by : Pedro Arthur <bygrandao@gmail.com>
  

  • [DH] doc/filters.texi
  • [DH] libavfilter/vf_dnn_processing.c