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1. if I use 4:4:4 -> 4:2:0, the YUV channel will have the different shape, while I read your mat file, the Y,U,V channel are all the shape 3840x2160.
2. so I decide to use 4:4:4, while I try to save mat and try to read them use code below, the image looks something wrong:
What I did was:
(i) Convert .mp4 file to .yuv using ffmpeg: ffmpeg -i <input_video.mp4> <output_video.yuv>
(ii) Read YUV frames from .yuv videos - like this, there's no need to convert from RGB to YUV. You can refer to Deep-SR-ITM/utils/load_yuv.m for loading YUV frames and this issue for more details on the function.
(iii) Save as .mat file.
As for your question, load_yuv.m basically repeats values in a 4:2:0 frame to create a full 3840x2160 frame.
For (ii) and (iii), please refer to the below Matlab code:
hi, thanks for your fancy work!
I am now trying to put the testset on my own
I download the testset as you say in 4kmedia.org
For HDR video:
ffmpeg -i movie_name -color_primaries bt2020 ./4k/LG_Daylight_4K_Demo_BG/%08d.png
for the rgb2yuv_hdr() function, I refer the issue 19 and write them in python:
questions I happened is below:
1. if I use 4:4:4 -> 4:2:0, the YUV channel will have the different shape, while I read your mat file, the Y,U,V channel are all the shape 3840x2160.
2. so I decide to use 4:4:4, while I try to save mat and try to read them use code below, the image looks something wrong:
Could you please help me out of that problem? How to write to a mat file from a video type?
I just want to re-implement the results you did. But the released test set are so rare. I want to test more dataset and get the quantitative results.
Looking forward to your reply soooo much! @sooyekim @JihyongOh
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