README.md

metadata

title: ObjectAssembler - LEGO 3D Assembly Prediction
emoji: 🧱
colorFrom: blue
colorTo: red
sdk: docker
app_port: 7860
pinned: false
license: mit
preload_from_hub:
  - 0xZohar/object-assembler-models
  - openai/clip-vit-base-patch32
env:
  HF_HOME: /home/user/.cache/huggingface
  HF_HUB_CACHE: /home/user/.cache/huggingface/hub
  TRANSFORMERS_CACHE: /home/user/.cache/huggingface/transformers
  HF_HUB_DISABLE_XET: '1'
  LDRAW_LIBRARY_PATH: /home/user/ldraw

ObjectAssembler: Assemble Your Object with Diverse Components

A deep learning-based system for predicting and visualizing LEGO brick assembly sequences using transformer models.

Features

• LDR File Processing: Upload .ldr (LDraw format) files containing LEGO brick assembly instructions
• Text-to-LEGO: Describe your desired design in natural language (e.g., "red sports car")
• AI-Powered Prediction: Uses GPT-based transformer models to predict optimal assembly sequences
• 3D Rendering: Generates high-quality 3D visualizations using Blender
• Part Visualization: Displays individual brick components with rendered previews
• Interactive UI: User-friendly Gradio interface for easy interaction

Model Architecture

• GPT Model: 5-layer transformer with 12 attention heads
• Shape Tokenizer: VQ-VAE autoencoder with 16,384 token vocabulary
• CLIP Integration: Vision-language model for text-to-design retrieval
• Model Size: ~1.6GB total weights

Usage

Option 1: Upload LDR File

1. Upload an .ldr file containing LEGO part names
2. Click "Load Input" to process and visualize individual parts
3. Click "Generate New LDR & Render" to predict assembly sequence
4. Download the generated LDR file or view the 3D rendering

Option 2: Text-to-LEGO

1. Enter a text description (e.g., "red sports car", "blue police car")
2. Click "Load Input" to retrieve a similar design
3. Click "Generate New LDR & Render" to generate assembly sequence
4. View the AI-generated LEGO model

Hardware Requirements

• GPU: Runs on HuggingFace ZeroGPU (H200, 70GB VRAM)
• Memory: At least 8GB RAM
• Storage: ~2GB for model weights and dependencies

Technical Stack

• PyTorch 2.0+
• Gradio 5.12.0+
• Blender 3.6 (for rendering)
• Transformers (Hugging Face)
• CLIP (OpenAI)
• ZeroGPU for efficient GPU allocation

Citation

If you use this work in your research, please cite:

@article{objectassembler2024,
  title={ObjectAssembler: Assemble Your Object with Diverse Components},
  year={2024}
}

License

MIT License

Acknowledgments

Built with PyTorch, Gradio, Blender, and HuggingFace ZeroGPU.

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Latest Update (2025-11-24): Enhanced LDraw library verification with detailed part counts and critical part checks.

Previous Update (2025-11-14): Added complete label mapping files for Text-to-LEGO functionality.