JRPG Pixel Art Background Generator
Model Description
JRPG Background Generator is a Diffusion Model trained from scratch to generate pixel art backgrounds in the style of classic JRPG games (Final Fantasy, Chrono Trigger, Secret of Mana).
The model uses a UNet2D architecture with DDPM (Denoising Diffusion Probabilistic Models) scheduler to generate 128x128 pixel art landscapes.
Model Details
- Model Type: Diffusion Model (DDPM)
- Architecture: UNet2D with Attention Blocks
- Resolution: 128x128 pixels
- Training Epochs: 600
- Training Time: ~200 hours on NVIDIA GPU
- Framework: PyTorch + Hugging Face Diffusers
- Parameters: ~45M
Supported Styles
The model can generate various scene types:
- 🏜️ Desert ruins and ancient temples
- 🏰 Castles and fortresses
- 🏔️ Canyons and mountain passes
- ☁️ Floating islands
- 🌅 Sunset/sunrise landscapes
- 🌊 Coastal scenes
-
- and lot of more
Intended Use
Primary Use Cases
- Indie Game Development: Generate background assets for retro-style RPG games
- Concept Art: Quick ideation for game environments
- NFT Collections: Create unique pixel art landscape collections
- Game Prototyping: Rapid background generation for mockups
- AI Art Research: Study diffusion models on pixel art domain
Out-of-Scope Use
- Photorealistic image generation
- Character/sprite generation
- High-resolution outputs (>256x256)
- Real-time generation (inference takes ~30-60 seconds)
How to Use
Installation
pip install torch diffusers pillow matplotlib transformers
Quick Start
Kullanım
from diffusers import DDPMPipeline
pipe = DDPMPipeline.from_pretrained("ayhant/Pixel-Art-JRPG-Background-Generator")
image = pipe(batch_size=1, num_inference_steps=256).images[0]
image.save("background.png")
Training Details
Training Data
- Dataset Size: Custom curated dataset of ~500 JRPG background images
- Data Sources: Open Art, Final Fantasy series, Chrono Trigger, Secret of Mana, etc.
- Preprocessing:
- Resized to 128x128
- Random horizontal flip augmentation
- Normalized to [-1, 1]
Training Hyperparameters
- Training epochs: 100
- Batch size: 32
- Learning rate: 1e-4
- Optimizer: Adam
- Scheduler: DDPM (512 timesteps)
- Loss function: MSE Loss
- GPU: NVIDIA (CUDA)
Training Procedure
for epoch in range(100):
for batch in dataloader:
# Random timestep
timesteps = torch.randint(0, 512, (batch_size,))
# Add noise
noise = torch.randn_like(batch)
noisy_images = scheduler.add_noise(batch, noise, timesteps)
# Predict noise
noise_pred = model(noisy_images, timesteps).sample
# MSE loss
loss = F.mse_loss(noise_pred, noise)
# Backprop
optimizer.zero_grad()
loss.backward()
optimizer.step()
Evaluation
Qualitative Results
The model successfully generates:
- ✅ Diverse scene compositions
- ✅ Appropriate color palettes (warm/cool contrasts)
- ✅ Volumetric lighting effects
- ✅ Multi-layered depth perception
- ✅ JRPG aesthetic consistency
Limitations
- 🔸 Limited to 128x128 resolution
- 🔸 Occasional artifacts in complex scenes
- 🔸 Inference time: ~10-20 seconds per image
- 🔸 Cannot generate characters or sprites
- 🔸 Style limited to training dataset
🚀 Want to try it yourself? • Interactive Demo: https://huggingface.co/spaces/ayhant/Pixel-Art-JRPG-Assets-Background-Generator • Technical Details: https://huggingface.co/ayhant/Pixel-Art-JRPG-Background-Generator
Sample Outputs
License
MIT License - Free for commercial and non-commercial use.
Citation
@misc{jrpg-background-generator-2024,
author = {[Your Name]},
title = {JRPG Pixel Art Background Generator},
year = {2024},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/[your-username]/jrpg-background-generator}}
}
Contact
Interested in citing this work? Please contact us for proper citation format.
🤝 Collaboration Opportunities
I am open to:
- 🎓 Academic Partnerships - Research collaborations
- 🏢 Enterprises - Commercial licensing
- 👥 Community Projects - Open-source initiatives
Average Response Time: 24-48 hours
Acknowledgments
- Inspired by classic JRPG games (Final Fantasy, Chrono Trigger)
- Built with Hugging Face Diffusers
- Thanks to the open pixel art community
Tags: #GenerativeAI #DiffusionModels #PixelArt #GameDev #JRPG #PyTorch
🔒 Licensing
Current Status: Private / Gated Access
Available Licenses:
- Academic License - Free for research
- Indie Developer License - Affordable for small studios
- Commercial License - Full commercial rights
- Enterprise License - Custom terms
🎮 Ready to create amazing JRPG backgrounds?
Made with ❤️ for the retro gaming community