This project provides a Tensorrt implementation for fast image upscaling inside ComfyUI (3-4x faster)
This project provides a Tensorrt implementation for fast image upscaling inside ComfyUI (3-4x faster)
This project is licensed under CC BY-NC-SA, everyone is FREE to access, use, modify and redistribute with the same license.
For commercial purposes, please contact me directly at [email protected]
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Note: The following results were benchmarked on FP16 engines inside ComfyUI, using 100 frames
| Device | Model | Input Resolution (WxH) | Output Resolution (WxH) | FPS | | :----: | :-----------: | :--------------------: | :---------------------: | :-: | | L40s | RealESRGAN_x4 | 512 x 512 | 2048 x 2048 | 5 | | L40s | RealESRGAN_x4 | 960 x 540 | 3840 x 2160 | 2 | | L40s | RealESRGAN_x4 | 1280 x 1280 | 5120 x 5120 | 0.7 |
Navigate to the ComfyUI /custom_nodes
directory
git clone https://github.com/yuvraj108c/ComfyUI-Upscaler-Tensorrt.git
cd ./ComfyUI-Upscaler-Tensorrt
pip install -r requirements.txt
Download one of the available onnx models. These onnx models support dynamic image resolutions from 256x256 to 1280x1280 px (e.g 960x540, 512x512, 1280x720 etc). Here are the original models:
Run python export_trt.py
and set onnx/engine paths accordingly
Place the exported engine inside ComfyUI /models/tensorrt/upscaler
directory
Right Click -> tensorrt -> Upscaler Tensorrt
.pth
to .onnx
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)