1. 01 7月, 2020 3 次提交
  2. 30 6月, 2020 4 次提交
  3. 29 6月, 2020 4 次提交
  4. 28 6月, 2020 12 次提交
  5. 27 6月, 2020 4 次提交
  6. 26 6月, 2020 8 次提交
  7. 25 6月, 2020 5 次提交
    • M
      avformat/microdvddec: skip malformed lines without frame number. · a8fb7612
      Michael Niedermayer 提交于
      Fixes: signed integer overflow: 1 - -9223372036854775808 cannot be represented in type 'long'
      Fixes: 23490/clusterfuzz-testcase-minimized-ffmpeg_DEMUXER_fuzzer-5133490093031424
      
      Found-by: continuous fuzzing process https://github.com/google/oss-fuzz/tree/master/projects/ffmpegReviewed-by: NNicolas George <george@nsup.org>
      Signed-off-by: NMichael Niedermayer <michael@niedermayer.cc>
      a8fb7612
    • E
      avfilter/zoompan: add in_time variable · 32d6fe23
      exwm 提交于
      Currently, the zoompan filter exposes a 'time' variable (missing from docs) for use in
      the 'zoom', 'x', and 'y' expressions. This variable is perhaps better named
      'out_time' as it represents the timestamp in seconds of each output frame
      produced by zoompan. This patch adds aliases 'out_time' and 'ot' for 'time'.
      
      This patch also adds an 'in_time' (alias 'it') variable that provides access
      to the timestamp in seconds of each input frame to the zoompan filter.
      This helps to design zoompan filters that depend on the input video timestamps.
      For example, it makes it easy to zoom in instantly for only some portion of a video.
      Both the 'out_time' and 'in_time' variables have been added in the documentation
      for zoompan.
      
      Example usage of 'in_time' in the zoompan filter to zoom in 2x for the
      first second of the input video and 1x for the rest:
          zoompan=z='if(between(in_time,0,1),2,1):d=1'
      
      V2: Fix zoompan filter documentation stating that the time variable
      would be NAN if the input timestamp is unknown.
      
      V3: Add 'it' alias for 'in_time. Add 'out_time' and 'ot' aliases for 'time'.
      Minor corrections to zoompan docs.
      Signed-off-by: Nexwm <thighsman@protonmail.com>
      32d6fe23
    • L
      bd6ae462
    • T
      dnn-layer-math-unary-test: add unit test for atan · 24d1781c
      Ting Fu 提交于
      Signed-off-by: NTing Fu <ting.fu@intel.com>
      Signed-off-by: 郭叶军's avatarGuo Yejun <yejun.guo@intel.com>
      24d1781c
    • T
      dnn_backend_native_layer_mathunary: add atan support · 13f5613e
      Ting Fu 提交于
      It can be tested with the model generated with below python script:
      
      import tensorflow as tf
      import numpy as np
      import imageio
      
      in_img = imageio.imread('input.jpeg')
      in_img = in_img.astype(np.float32)/255.0
      in_data = in_img[np.newaxis, :]
      
      x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
      x1 = tf.atan(x)
      x2 = tf.divide(x1, 3.1416/4) # pi/4
      y = tf.identity(x2, 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, '.', 'image_process.pb', as_text=False)
      
      print("image_process.pb generated, please use \
      path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")
      
      output = sess.run(y, feed_dict={x: in_data})
      imageio.imsave("out.jpg", np.squeeze(output))
      Signed-off-by: NTing Fu <ting.fu@intel.com>
      Signed-off-by: 郭叶军's avatarGuo Yejun <yejun.guo@intel.com>
      13f5613e