| # Anime Video Models | |
| :white_check_mark: We add small models that are optimized for anime videos :-)<br> | |
| More comparisons can be found in [anime_comparisons.md](anime_comparisons.md) | |
| - [How to Use](#how-to-use) | |
| - [PyTorch Inference](#pytorch-inference) | |
| - [ncnn Executable File](#ncnn-executable-file) | |
| - [Step 1: Use ffmpeg to extract frames from video](#step-1-use-ffmpeg-to-extract-frames-from-video) | |
| - [Step 2: Inference with Real-ESRGAN executable file](#step-2-inference-with-real-esrgan-executable-file) | |
| - [Step 3: Merge the enhanced frames back into a video](#step-3-merge-the-enhanced-frames-back-into-a-video) | |
| - [More Demos](#more-demos) | |
| | Models | Scale | Description | | |
| | ---------------------------------------------------------------------------------------------------------------------------------- | :---- | :----------------------------- | | |
| | [realesr-animevideov3](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-animevideov3.pth) | X4 <sup>1</sup> | Anime video model with XS size | | |
| Note: <br> | |
| <sup>1</sup> This model can also be used for X1, X2, X3. | |
| --- | |
| The following are some demos (best view in the full screen mode). | |
| <https://user-images.githubusercontent.com/17445847/145706977-98bc64a4-af27-481c-8abe-c475e15db7ff.MP4> | |
| <https://user-images.githubusercontent.com/17445847/145707055-6a4b79cb-3d9d-477f-8610-c6be43797133.MP4> | |
| <https://user-images.githubusercontent.com/17445847/145783523-f4553729-9f03-44a8-a7cc-782aadf67b50.MP4> | |
| ## How to Use | |
| ### PyTorch Inference | |
| ```bash | |
| # download model | |
| wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-animevideov3.pth -P weights | |
| # single gpu and single process inference | |
| CUDA_VISIBLE_DEVICES=0 python inference_realesrgan_video.py -i inputs/video/onepiece_demo.mp4 -n realesr-animevideov3 -s 2 --suffix outx2 | |
| # single gpu and multi process inference (you can use multi-processing to improve GPU utilization) | |
| CUDA_VISIBLE_DEVICES=0 python inference_realesrgan_video.py -i inputs/video/onepiece_demo.mp4 -n realesr-animevideov3 -s 2 --suffix outx2 --num_process_per_gpu 2 | |
| # multi gpu and multi process inference | |
| CUDA_VISIBLE_DEVICES=0,1,2,3 python inference_realesrgan_video.py -i inputs/video/onepiece_demo.mp4 -n realesr-animevideov3 -s 2 --suffix outx2 --num_process_per_gpu 2 | |
| ``` | |
| ```console | |
| Usage: | |
| --num_process_per_gpu The total number of process is num_gpu * num_process_per_gpu. The bottleneck of | |
| the program lies on the IO, so the GPUs are usually not fully utilized. To alleviate | |
| this issue, you can use multi-processing by setting this parameter. As long as it | |
| does not exceed the CUDA memory | |
| --extract_frame_first If you encounter ffmpeg error when using multi-processing, you can turn this option on. | |
| ``` | |
| ### NCNN Executable File | |
| #### Step 1: Use ffmpeg to extract frames from video | |
| ```bash | |
| ffmpeg -i onepiece_demo.mp4 -qscale:v 1 -qmin 1 -qmax 1 -vsync 0 tmp_frames/frame%08d.png | |
| ``` | |
| - Remember to create the folder `tmp_frames` ahead | |
| #### Step 2: Inference with Real-ESRGAN executable file | |
| 1. Download the latest portable [Windows](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-windows.zip) / [Linux](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-ubuntu.zip) / [MacOS](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesrgan-ncnn-vulkan-20220424-macos.zip) **executable files for Intel/AMD/Nvidia GPU** | |
| 1. Taking the Windows as example, run: | |
| ```bash | |
| ./realesrgan-ncnn-vulkan.exe -i tmp_frames -o out_frames -n realesr-animevideov3 -s 2 -f jpg | |
| ``` | |
| - Remember to create the folder `out_frames` ahead | |
| #### Step 3: Merge the enhanced frames back into a video | |
| 1. First obtain fps from input videos by | |
| ```bash | |
| ffmpeg -i onepiece_demo.mp4 | |
| ``` | |
| ```console | |
| Usage: | |
| -i input video path | |
| ``` | |
| You will get the output similar to the following screenshot. | |
| <p align="center"> | |
| <img src="https://user-images.githubusercontent.com/17445847/145710145-c4f3accf-b82f-4307-9f20-3803a2c73f57.png"> | |
| </p> | |
| 2. Merge frames | |
| ```bash | |
| ffmpeg -r 23.98 -i out_frames/frame%08d.jpg -c:v libx264 -r 23.98 -pix_fmt yuv420p output.mp4 | |
| ``` | |
| ```console | |
| Usage: | |
| -i input video path | |
| -c:v video encoder (usually we use libx264) | |
| -r fps, remember to modify it to meet your needs | |
| -pix_fmt pixel format in video | |
| ``` | |
| If you also want to copy audio from the input videos, run: | |
| ```bash | |
| ffmpeg -r 23.98 -i out_frames/frame%08d.jpg -i onepiece_demo.mp4 -map 0:v:0 -map 1:a:0 -c:a copy -c:v libx264 -r 23.98 -pix_fmt yuv420p output_w_audio.mp4 | |
| ``` | |
| ```console | |
| Usage: | |
| -i input video path, here we use two input streams | |
| -c:v video encoder (usually we use libx264) | |
| -r fps, remember to modify it to meet your needs | |
| -pix_fmt pixel format in video | |
| ``` | |
| ## More Demos | |
| - Input video for One Piece: | |
| <https://user-images.githubusercontent.com/17445847/145706822-0e83d9c4-78ef-40ee-b2a4-d8b8c3692d17.mp4> | |
| - Out video for One Piece | |
| <https://user-images.githubusercontent.com/17445847/164960481-759658cf-fcb8-480c-b888-cecb606e8744.mp4> | |
| **More comparisons** | |
| <https://user-images.githubusercontent.com/17445847/145707458-04a5e9b9-2edd-4d1f-b400-380a72e5f5e6.MP4> | |