Kiteretsu77

I wonder if you are interested in deploying our new Anime model from CVPR2024 (https://github.com/Kiteretsu77/APISR). This one provides 4xGRL (different from regular GRL, we add another conv before it) and...

Personally, I think that if your input source is the same resolution, the x1,x2,x4 inference speed won't be too different because most computation of RRDB structure (the core architecture of...

To completely extract the performance of GPU, I have created a GitHub repo (https://github.com/Kiteretsu77/FAST_Anime_VSR). I implemented it in TensorRT version and utilized a frame division algorithm (self-designed) to accelerate it...

This comment appears when your computation resources cannot catch up the fast decode speed. I think that what I wrote is confusing. I will change it.

The new branch supports GPU encoding as the default option (you can change it in the config.py if you don't want). Moreover, based on my test, GPU encoding accelerates the...

> The new branch will support GPU encoding as default option (you can change it in the config.py if you don't want). Moreover, based on my test, GPU encoding help...

For Windows task manager, I always feel that their utilization of GPU reports is inaccurate. What I used for encoding is actually the Nvidia Hardware encoder (-c:v hevc_nvenc) built in...

Thanks for your advice! I will think about it!

Thanks for the update! Personally, I recommend checking the step4 of https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html#installing-zip It is necessary to make sure that the environment variable is set correctly. I am not sure if...

The format I have tested is "mp4" and "mkv". For other input video formats, I didn't test them, so on line 11 of mass_production.py, I didn't add other accepted formats....