77 lines
3.8 KiB
Markdown
77 lines
3.8 KiB
Markdown
# ComfyUI RIFE TensorRT-RTX
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[](https://www.python.org/downloads/release/python-31313/)
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[](https://developer.nvidia.com/cuda-downloads)
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[](https://developer.nvidia.com/tensorrt)
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[](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en)
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## Overview
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This project is a fork of the original [ComfyUI_RIFE_TensorRT_Auto](https://github.com/silveroxides/ComfyUI_RIFE_TensorRT_Auto) by [silveroxides](https://github.com/silveroxides).
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This project uses TensorRT-RTX to do RIFE interpolation
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## Features
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- **NVIDIA TensorRT Acceleration**: Leverages Tensor Cores for up to 30x faster frame interpolation compared to standard local methods.
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- **Dynamic Shape Support**: Configure minimum, optimal, and maximum resolutions to handle varying input sizes without rebuilding the engine for every image.
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- **Automatic Engine Building**: Automatically compiles specialized `.trt` files from your `.onnx` models if a matching engine isn't found.
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- **Persistent Timing Cache**: Saves hardware-specific optimization data to a local cache to speed up subsequent engine builds.
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- **Memory Efficient**: Optimized for VRAM management with automatic garbage collection and cache clearing after inference.
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## Examples
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## Installation
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### ComfyUI Manager
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This project has not been submitted to the ComfyUI Manager registry yet. But you can still install it this way:
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1. Open ComfyUI Manager.
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2. Click the `Custom Nodes Manager` to open the custom nodes manager page.
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3. On the bottom right corner, click the `Install via Git URL` button.
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4. Enter the URL of this repository: `https://github.com/ThreadsOfFate/ComfyUI-RIFE-TensorRT-RTX`
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5. Click "Confirm".
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6. Restart ComfyUI.
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### Manual
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1. On the github page, click on the green `<> Code` button and then "Download ZIP".
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2. Extract the root folder within the downloaded ZIP file to your ComfyUI `custom_nodes` directory.
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3. Using the same python environment that runs ComfyUI, install the required dependencies: `python -m pip install -r custom_nodes/ComfyUI-Upscaler-TensorRT-Advanced/requirements.txt`.
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4. Restart ComfyUI.
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### Requirements
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pip install -r requirements.txt
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### CUDA Toolkit Required
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Please download NVIDIA CUDA Toolkit [https://developer.nvidia.com/cuda/toolkit](https://developer.nvidia.com/cuda/toolkit)
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###Nodes Included
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🟦 RIFE RTX Engine Builder (RIFERTXEngineLoader)
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Loads a TensorRT-RTX engine. If the engine file for your specific GPU and resolution settings does not exist, it will automatically build one from the source ONNX model.
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🟦 RIFE RTX Frame Interpolation (RIFERTXFrameInterpolation)
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The core execution node. It takes an image and a loaded engine to perform the upscale. It supports an optional resize input for custom final dimensions.
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🟦 RIFE RTX Engine Config (RIFERTXEngineConfig)
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Allows you to define the resolution bounds (min/opt/max) for the engine.
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Min/Max: The range of resolutions the engine can handle.
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Opt: The resolution the engine is most optimized for.
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GPU: NVIDIA RTX Series (TensorRT-RTX requires Tensor Cores).
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Software: NVIDIA Drivers and a compatible version of TensorRT (handled via requirements.txt).
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###Troubleshooting
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First Build Time: The first time you load a model with new shape settings, it may take several minutes to compile the engine. Check the console for progress via the TQDM bar.
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VRAM Errors: If the build fails, try reducing the width_max or height_max in the Dynamic Shape Config.
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## 🛠️ Supported Models
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rife47_ensemble_True_scale_1_sim
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rife48_ensemble_True_scale_1_sim
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rife49_ensemble_True_scale_1_sim
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