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• Using ffmpeg Silencedetect in C#

  11 septembre 2018, par jayjay

  I want to build a programm which splitts a long audio file into small peaces.
  I like to use ffmpeg silencedetect. From the console it works fine and returns the detected silence etc.
  Now i want to count many resulting tracks there are an gave the user the possibiliy to change the time parameter of the silencedetect function.
  I want to call the silencedetect function from C# code.
  But i don´t know how to work with the output in C#.

  Thank you for your help.

  Greetings Jan

• avcodec/omx : Fix handling of fragmented buffers

  17 janvier 2019, par Dave Stevenson

  avcodec/omx : Fix handling of fragmented buffers
  See https://trac.ffmpeg.org/ticket/7687
  If an encoded frame is returned split over two or more
  
  IL buffers due to the size, then there is a race between
  
  whether get_buffer will fail, return NULL, and a truncated
  
  frame is passed on, or IL will return the remaining part
  
  of the encoded frame.
  
  If get_buffer returns NULL, part of the frame is left behind
  
  in the codec, and will be collected on the next call. That
  
  then leaves a frame stuck in the codec. Repeat enough times
  
  and the codec FIFO is full, and the pipeline stalls.
  A performance improvement in the Raspberry Pi firmware means
  
  that the timing has changed, and now frequently drops into the
  
  case where get_buffer returns NULL.
  Add code such that should a buffer be received without
  
  OMX_BUFFERFLAG_ENDOFFRAME that get_buffer is called with wait
  
  set, so we wait for the remainder of the frame.
  
  This code has been made conditional on the Pi build in case
  
  other IL implementations don't handle ENDOFFRAME correctly.
  Signed-off-by : Dave Stevenson <dave.stevenson@raspberrypi.org>
  
  Signed-off-by : Aman Gupta <aman@tmm1.net>
  
  Signed-off-by : Martin Storsjö <martin@martin.st>
  

  • [DH] libavcodec/omx.c

• Create Panorama from Non-Sequential Video Frames

  6 mai 2021, par M.Innat

  There is a similar question (not that detailed and no exact solution).

  


  ---

  


  I want to create a single panorama image from video frames. And for that, I need to get minimum non-sequential video frames at first. A demo video file is uploaded here.

  


  What I Need

  


  A mechanism that can produce not-only non-sequential video frames but also in such a way that can be used to create a panorama image. A sample is given below. As we can see to create a panorama image, all the input samples must contain minimum overlap regions to each other otherwise it can not be done.

  


  

  


  So, if I have the following video frame's order

  


  A, A, A, B, B, B, B, C, C, A, A, C, C, C, B, B, B ...


  


  To create a panorama image, I need to get something as follows - reduced sequential frames (or adjacent frames) but with minimum overlapping.

  


       [overlap]  [overlap]  [overlap] [overlap]  [overlap]
 A,    A,B,       B,C,       C,A,       A,C,      C,B,  ...


  


  What I've Tried and Stuck

  


  A demo video clip is given above. To get non-sequential video frames, I primarily rely on ffmpeg software.

  


  Trial 1 Ref.

  


  ffmpeg -i check.mp4 -vf mpdecimate,setpts=N/FRAME_RATE/TB -map 0:v out.mp4


  


  After that, on the out.mp4, I applied slice the video frames using opencv

  


  import cv2, os 
from pathlib import Path

vframe_dir = Path("vid_frames/")
vframe_dir.mkdir(parents=True, exist_ok=True)

vidcap = cv2.VideoCapture('out.mp4')
success,image = vidcap.read()
count = 0

while success:
    cv2.imwrite(f"{vframe_dir}/frame%d.jpg" % count, image)     
    success,image = vidcap.read()
    count += 1


  


  Next, I rotated these saved images horizontally (as my video is a vertical view).

  


  vframe_dir = Path("out/")
vframe_dir.mkdir(parents=True, exist_ok=True)

vframe_dir_rot = Path("vframe_dir_rot/")
vframe_dir_rot.mkdir(parents=True, exist_ok=True)

for i, each_img in tqdm(enumerate(os.listdir(vframe_dir))):
    image = cv2.imread(f"{vframe_dir}/{each_img}")[:, :, ::-1] # Read (with BGRtoRGB)
    
    image = cv2.rotate(image,cv2.cv2.ROTATE_180)
    image = cv2.rotate(image,cv2.ROTATE_90_CLOCKWISE)

    cv2.imwrite(f"{vframe_dir_rot}/{each_img}", image[:, :, ::-1]) # Save (with RGBtoBGR)


  


  The output is ok for this method (with ffmpeg) but inappropriate for creating the panorama image. Because it didn't give some overlapping frames sequentially in the results. Thus panorama can't be generated.

  
 


  Trail 2 - Ref

  


  ffmpeg -i check.mp4 -vf decimate=cycle=2,setpts=N/FRAME_RATE/TB -map 0:v out.mp4


  


  didn't work at all.

  


  Trail 3

  


  ffmpeg -i check.mp4 -ss 0 -qscale 0 -f image2 -r 1 out/images%5d.png


  


  No luck either. However, I've found this last ffmpeg command was close by far but wasn't enough. Comparatively to others, this gave me a small amount of non-duplicate frames (good) but the bad thing is still do not need frames, and I kinda manually pick some desired frames, and then the opecv stitching algorithm works. So, after picking some frames and rotating (as mentioned before) :

  


  stitcher = cv2.Stitcher.create()
status, pano = stitcher.stitch(images) # images: manually picked video frames -_- 


  
 


  Update

  


  After some trials, I am kinda adopting the non-programming solution. But would love to see an efficient programmatic approach.

  


  On the given demo video, I used Adobe products (premiere pro and photoshop) to do this task, video instruction. But the issue was, I kind of took all video frames at first (without dropping to any frames and that will computationally cost further) via premier and use photoshop to stitching them (according to the youtube video instruction). It was too heavy for these editor tools and didn't look better way but the output was better than anything until now. Though I took few (400+ frames) video frames only out of 1200+.

  


  

  


  ---

  


  Here are some big challenges. The original video clips have some conditions though, and it's too serious. Unlike the given demo video clips :

  


  

  • It's not straight forward, i.e. camera shaking

  


  • Lighting condition, i.e. causes different visual look at the same spot

  


  • Cameral flickering or banding

  


  


  This scenario is not included in the given demo video. And this brings additional and heavy challenges to create panorama images from such videos. Even with the non-programming way (using adobe tools) I couldn't make it any good.

  


  ---

  


  However, for now, all I'm interest to get a panorama image from the given demo video which is without the above condition. But I would love to know any comment or suggestion on that.