README.md

---
title: Color Grade Transfer
emoji: 😻
colorFrom: purple
colorTo: blue
sdk: gradio
sdk_version: 6.17.3
python_version: '3.12'
app_file: app.py
pinned: true
tags:
- backyard-ai
- an-adventure-in-thousand-token-wood
- well-tuned
- gradio
short_description: Apply the color grade from one image to another image

---

# 🌓 Color Grade Transfer

**Transfer color grade directly from reference image to source image without manual color grading.**

[![Build Small Hackathon](https://img.shields.io/badge/Build%20Small%20Hackathon-blue)](https://huggingface.co/build-small-hackathon)
[![Track 1: Backyard AI](https://img.shields.io/badge/Track%201-Backyard%20AI-blueviolet)](https://huggingface.co/build-small-hackathon)
[![Track 2: An Adventure in Thousand Token Wood](https://img.shields.io/badge/Track%202-An%20Adventure%20in%20Thousand%20Token%20Wood-blueviolet)](https://huggingface.co/build-small-hackathon)

[![Demo Video](https://img.shields.io/badge/▶_Watch_Demo-FF0000?style=for-the-badge&logo=youtube&logoColor=white)](https://youtu.be/DqlLDDgV3kQ)
[![Social Media Post](https://img.shields.io/badge/Social_Media_Post-000000?style=for-the-badge&logo=x&logoColor=white)](https://x.com/ovi054/status/2064060651706925403)
[![Try It Live](https://img.shields.io/badge/🚀_Try_It_Live-7C3AED?style=for-the-badge)](https://huggingface.co/spaces/build-small-hackathon/Color-Grade-Transfer)

## 📖 Overview

It transfers the color grading from a reference image directly onto a source image.


## 🏆 Hackathon Patches

| Patch | Status |
| :--- | :--- |
| 🔬 **Small Models Only** — `Qwen-Image-Edit-2511` at 20B parameters, well under the 32B limit | ✅ |
| 🔌 **Off the Grid** — No cloud APIs, runs entirely on local GPU | ✅ |
| 🎯 **Well-Tuned** — Custom LoRA [`ovi054/QIE-2511-Color-Grade-Transfer-LoRA`](https://huggingface.co/ovi054/QIE-2511-Color-Grade-Transfer-LoRA) published on Hub | ✅ |
| 📓 **Field Notes** — [Blog post on what I built and learned](https://huggingface.co/blog/ovi054/color-grade-transfer) | ✅ |


### Key Features
* **Direct Color Transfer:** Copies styling from a reference image to a source image without manual grading.
* **4-Step Inference:** Uses a lightning adapter for fast, low-step generation.
* **Aspect Ratio Alignment:** Uses an internal VAE dimension calculation 1MP to ensure the 2-D RoPE coordinate systems match, eliminating structural pixel shifts during inference.
* **Interactive UI:** Features a side-by-side image comparison slider.
* **MCP Compliant:** Work as a backend tool for Model Context Protocol clients.

---


<!-- ### 🛠️ Core Constraints
* **Small Models Only:** Powered by the `Qwen-Image-Edit-2511` architecture family running at 20B parameters safely satisfying the 32 Billion parameter limit.
* 🔌 **Off the Grid (Local-First):** **No cloud APIs are used.** The pipeline loads the model weights and runs entirely on the host GPU hardware.
* 🎯 **Well-Tuned:** Utilizes a custom fine-tuned LoRA adapter published directly on my Hugging Face Hub (`ovi054/QIE-2511-Color-Grade-Transfer-LoRA`).

---
 -->

## 🧠 LoRA Fine-Tuning Process

Curating a clean dataset for custom style mapping is often the bottleneck of training. To overcome this, a systematic data-generation technique was engineered to produce high-fidelity, bidirectional training pairs.

### The Dataset Recipe
1. **Palette Extraction:** Two entirely different content images were chosen.
2. **Homogeneous Grading:** The exact same color palette was applied to both images so they shared an identical color profile.
3. **Cross-Pair Mapping:** * The newly graded version of *Image B* was assigned as the color-style reference for *Image A*.
   * The inputs were then flipped, mapping the graded version of *Image A* as the reference for *Image B*.
4. This instantly generated **two highly consistent training pairs** per asset set, allowing the dataset to scale efficiently without content bleeding or style loss.

### Versatility & Flexibility
Because the dataset decoupling separated semantic structure from global grading parameters, the fine-tuned LoRA natively generalizes across all input configurations:
* 👤 ↔️ 👤 **Character to Character**
* 🏞️ ↔️ 🏞️ **Scene to Scene**
* 👤 ↔️ 🏞️ **Character to Scene** / **Scene to Character**

### ⚙️ Training Hyperparameters
The model was fine-tuned using the following precise configuration settings:

| Configuration Category | Parameter | Value / Setting |
| :--- | :--- | :--- |
| **Saving Settings** | Save Precision | `bf16` |
| **Learning Rate** | Learning Rate | `0.0001` |
| | Optimizer | `AdamW` |
| **Dataset Settings** | Base Resolution | 1024 * 1024 |
| | Enable Bucket | True (`open`) |
| | Min Bucket Reso | `128` |
| | Max Bucket Reso | `8192` |
| | Bucket Reso Steps | `64` |
| **Network Settings** | Network Rank Dim (Rank) | `16` |
| | Network Alpha | `16` |

---


## ⚙️ Tech Stack

* **Base Model:** `Qwen/Qwen-Image-Edit-2511`
* **LoRA Adapters:**
  * `ovi054/QIE-2511-Color-Grade-Transfer-LoRA` (Color grade transfer fine-tune)
  * `lightx2v/Qwen-Image-Edit-2511-Lightning` (4-step inference)
* **Frontend:** Gradio

---

## 🔗 Project Links

### Live Demo
* **Hugging Face Space:** [Color Grade Transfer](https://huggingface.co/spaces/build-small-hackathon/Color-Grade-Transfer)

### Blog
* **Blog Post:** [Color Grade Transfer — Instant Cinematic Tone Matching](https://huggingface.co/blog/ovi054/color-grade-transfer)


### Social Media & Demo
* **Twitter/X:** [https://x.com/ovi054/status/2064060651706925403](https://x.com/ovi054/status/2064060651706925403)
* **Hugging Face Post:** [https://huggingface.co/posts/ovi054/229194823175599](https://huggingface.co/posts/ovi054/229194823175599)
* **Youtube Video:** [https://youtu.be/DqlLDDgV3kQ](https://youtu.be/DqlLDDgV3kQ)

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference