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• How to convert animated webp to gif in android / java ?

  21 avril 2022, par UHS

  I want to convert the animated webp files to gif file and looking for solution since couple of days but did not get any easy straight solution yet.

  


  I tried ffmpeg but it could not do the job and after looking for solution I found that webp decoder is not implemented in ffmpeg yet.
https://trac.ffmpeg.org/ticket/4907

  


  I also checked libwebp library by google and they also says animated webp is not supported. https://developers.google.com/speed/webp/docs/dwebp

  


  I tried demo of aspose this library also fail to convert animated webp to gif.
https://products.aspose.com/imaging/java/conversion/webp-to-gif/

  


  I think ImageMagick can convert animated webp to gif but do not know how to implement that in my project.
How can I avoid dropouts when using (imagemagick) `mogrify` to convert webp files to animated gif ?

  


  So is there any easy way to convert webp to gif

  


• How do I convert a 3D SBS dual-fisheye image to 3D SBS dual-equirectangular with only open-source tools ? [closed]

  21 octobre 2024, par Ethan T

  Canon has released a new 3D VR lens for their RF mount and I recently rented it to see what it's like to work with. Unfortunately, they charge a subscription fee for their conversion software, which I've also found to be inconveniently limited in real-world use cases. Thus I'm interested in an open-source approach to converting the video captured by this lens using something like ffmpeg.

  


  The video is dual-fisheye and the Canon tool produces dual-equirectangular side-by-side video. I would like to perform this same conversion in ffmpeg or a similarly-powerful open-source tool.

  


  Related questions exist but aren't quite correct. Most dual-fisheye input seems to be used to create 360-degree 2D video, not 3D SBS.

  


• 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.