The Zentalic AI Photo Color Grader is a high-performance tool that generates custom .cube LUTs by utilizing AI to analyze the color profile of a reference image and apply that look to other footage. By automating the creation of 3D LUTs, the tool streamlines post-production for software like DaVinci Resolve, Adobe Premiere, and Final Cut Pro.
Developed by Zentalic Labs, this project is specifically engineered to run advanced Vision LLMs on consumer-grade hardware using a unique Layer-by-Layer Inference architecture via AirLLM.
- Layer-by-Layer Inference (AirLLM): Run 11B+ parameter models on just 6GB of RAM by swapping transformer layers from SSD to memory in real-time.
- Hybrid Model Support: Toggle between local execution (AirLLM) and Cloud APIs (Anthropic Claude, OpenAI GPT-4o, or Google Gemini).
- Professional .cube Export: Generates industry-standard 33x33x33 3D LUTs for professional color grading workflows.
- Zentalic "Style ID": Every AI-generated grade is assigned a unique sharing number (e.g.,
Z-1024) for instant style replication. - Dark Immersive UI: A minimalist, high-end interface inspired by the aesthetics of Claude.ai and Cursor.
| Component | Technology |
|---|---|
| AI Backend | Python 3.11+, AirLLM, PyTorch |
| Vision Models | Moondream2 (Local), Llama-3.2-Vision (AirLLM) |
| APIs | Anthropic (Claude 3.5), OpenAI, Google Gemini |
| Image Engine | OpenCV, NumPy, Pillow |
| Frontend | React / Next.js (Web), PyQt6 (Desktop EXE) |
| Compiler | Nuitka (Standalone Executable) |
To support low-RAM environments (6GB), this project utilizes the AirLLM architecture. Instead of loading the entire model into VRAM, it follows this automated cycle:
- Sharding: The model is split into atomic transformer layers on the disk.
- Sequential Loading: Layer 1 is loaded into RAM → Processed → Deleted.
- Cyclic Processing: This repeats for all layers (1 to 32) until a color analysis is produced.
- Parameter Extraction: The AI outputs a JSON object containing
Gain,Gamma,Lift, andSaturationvalues. - LUT Generation: Python calculates the 3D cube map and saves the
.cubefile.
- Python 3.10+
- 6GB RAM (Minimum)
- SSD (Highly recommended for AirLLM swapping speed)
# Clone the repository
git clone [https://github.com/zentalic/ai-photo-color-grader.git](https://github.com/zentalic/ai-photo-color-grader.git)
cd ai-photo-color-grader
# Install dependencies
pip install airllm opencv-python pillow anthropic openai
# Run the application
python app.py