---
license: apache-2.0
tags:
- ccsr
- super-resolution
- image-to-image
- upscaling
- controlnet
- tensorrt
- rtx
- comfyui
pipeline_tag: image-to-image
---

# CCSR: TensorRT RTX Acceleration Engine

Ultra-fast **TensorRT RTX** execution engine and auxiliary modules for **CCSR (Creative Content Super-Resolution)**, designed for real-time generative image upscaling in **ComfyUI**.

> 📦 **ComfyUI Loader & Upscaler Extension:**
> All nodes supporting TensorRT engine execution are available in:
> 👉 **[https://github.com/ussoewwin/ComfyUI-NunchakuFluxLoraStacker](https://github.com/ussoewwin/ComfyUI-NunchakuFluxLoraStacker)**

---

## 🌟 Overview

Creative Content Super-Resolution (CCSR) is a diffusion-based super-resolution framework leveraging a Controlled UNet and ControlNet structure to synthesize rich photorealistic textures and fine details.

This repository provides an optimized **NVIDIA TensorRT RTX Engine** implementation for CCSR:

- **Fused Denoising Engine (`ccsr_apply_f16io.rtxplan`)**:
  - Fuses the ControlNet and Controlled UNet denoising computation into a single compiled TensorRT engine.
  - Fixed 512px tile resolution (64×64 latent tile) executing at ~**24 ms/step** (~**4.7× speedup** over PyTorch FP16 at ~113 ms/step on modern RTX GPUs).
  - Synchronized stream execution on current PyTorch CUDA streams to eliminate race conditions and deadlocks.
- **Engine-Only Deployment (`ccsr_trt_aux.safetensors`)**:
  - Contains only the essential companion modules: FP16 AutoencoderKL (VAE encoder/decoder) and condition encoder.
  - Automatically loaded alongside the engine, eliminating the need to download large full checkpoints (~3.2 GB saved).

---

## 📦 Available Files

| Filename | Description | Architecture / Components | File Size | Recommended Location | License |
| :--- | :--- | :--- | :--- | :--- | :--- |
| `ccsr_apply_f16io.rtxplan` | TensorRT Fused Denoising Engine | ControlNet + UNet fused RTX Engine (Tile 512px / Latent 64×64) | ~1.4 GB | `custom_nodes/.../nodes/CCSR/trt_engines/` | Apache-2.0 |
| `ccsr_trt_aux.safetensors` | TRT Auxiliary Weights | FP16 VAE AutoencoderKL + Condition Encoder | ~450 MB | `custom_nodes/.../nodes/CCSR/trt_engines/` | Apache-2.0 |

---

## ⚙️ Performance & Benchmark Comparison

Measurements conducted on an NVIDIA RTX 4090 / RTX 5090 environment:

| Execution Mode | Files Required | VRAM Overhead (Denoising) | Step Latency (Tile 512) | Speedup |
| :--- | :--- | :--- | :--- | :--- |
| **Stock CCSR (FP16 PyTorch)** | Full Checkpoint (~3.2 GB) | ~3.8 GiB | ~113 ms / step | 1.0× (Baseline) |
| **CCSR TensorRT RTX** | Engine + Aux (~1.85 GB total) | ~2.2 GiB | ~**24 ms / step** | **~4.7× faster** |

---

## 🚀 Usage in ComfyUI

TensorRT engine execution for CCSR is integrated natively into the **[ComfyUI-NunchakuFluxLoraStacker](https://github.com/ussoewwin/ComfyUI-NunchakuFluxLoraStacker)** custom-node pack.

### Workflow Example

<p align="center">
  <img src="https://huggingface.co/ussoewwin/CCSR-TensorRT-Engine/resolve/main/png/ccsrtensor.png" alt="CCSR TensorRT RTX Engine Workflow in ComfyUI" width="800">
</p>

### Installation & Setup

1. **Install the Custom Node Pack**:
   ```bash
   cd ComfyUI/custom_nodes
   git clone https://github.com/ussoewwin/ComfyUI-NunchakuFluxLoraStacker.git
   ```

2. **Place Engine & Aux Files**:
   Download both `ccsr_apply_f16io.rtxplan` and `ccsr_trt_aux.safetensors` and place them directly into the engine directory:
   ```
   ComfyUI/custom_nodes/ComfyUI-NunchakuFluxLoraStacker/nodes/CCSR/trt_engines/
   ├── ccsr_apply_f16io.rtxplan
   └── ccsr_trt_aux.safetensors
   ```

3. **In ComfyUI**:
   - Add **`Load CCSR Model (TensorRT)`** (`LoadCCSRModelTensorRT`). The node automatically discovers `.rtxplan` files in `trt_engines/` and loads the companion `ccsr_trt_aux.safetensors`.
   - Connect the `ccsr_model` output to **`CCSR Upscale (TRT)`** (`CCSR_Upscale_TRT`).
   - Connect an input image to `image`.
   - Configure upscale parameters:
     - `tile_size`: 512 (fixed to match the compiled static engine shape)
     - `tile_stride`: 256 (recommended for seamless blending)
     - `color_fix_type`: `adain` (or `wavelet` / `none`)
     - `steps`: Effective diffusion step count (densified schedule guarantees exact execution of requested step count)

---

## 📜 Credits & License

- **Original CCSR Implementation & Weights**: [csslc/CCSR](https://github.com/csslc/CCSR) (Apache-2.0 License)
- **Research Paper**: *"Creative Content Super-Resolution with Pre-trained Diffusion Model"* by Liang et al.
- **ComfyUI CCSR Node Foundation**: [kijai/ComfyUI-CCSR](https://github.com/kijai/ComfyUI-CCSR) & [Kijai/ccsr-safetensors](https://huggingface.co/Kijai/ccsr-safetensors) (Apache-2.0 License)
- **TensorRT Engine & ComfyUI Loader**: [ussoewwin/ComfyUI-NunchakuFluxLoraStacker](https://github.com/ussoewwin/ComfyUI-NunchakuFluxLoraStacker) (CCSR nodes located under `nodes/CCSR/`)
- **License**: **Apache-2.0**