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--- |
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title: UltraPixel Multi-Stage (Community Fixed) |
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emoji: 🎨 |
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colorFrom: blue |
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colorTo: purple |
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sdk: gradio |
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sdk_version: 5.49.1 |
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app_file: app.py |
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pinned: false |
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license: apache-2.0 |
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--- |
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# 🎨 UltraPixel Multi-Stage Generator (Community Fixed) |
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A **properly working** UltraPixel-style high-resolution image generator that actually respects your parameter inputs. |
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## What's Different From Original UltraPixel Spaces? |
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The original public UltraPixel spaces have a critical flaw - they **hardcode CFG and timesteps inside the generation function**, making the UI sliders meaningless: |
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```python |
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# Original broken code: |
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extras.sampling_configs['cfg'] = 4 # ← Always uses 4! |
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extras.sampling_configs['timesteps'] = 20 # ← Ignores your slider! |
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``` |
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### This Space Fixes That ✅ |
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- **Real CFG Control**: Your slider values are actually passed to the model |
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- **Real Steps Control**: Set your own timesteps (10-100) per stage |
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- **Memory Optimized**: Won't OOM on ZeroGPU (max 3072×3072 with tiling) |
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- **No Login Required**: Public access for easy testing |
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## Features |
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- 🎯 **3-Stage Pipeline**: Stable Cascade architecture (Stage C → B → A) |
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- 🔧 **Independent Controls**: Separate CFG/steps for each stage |
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- 💾 **Memory Safe**: Aggressive cleanup between stages, forced tiling |
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- ⏱️ **120s Per Stage**: Each stage gets fresh GPU allocation |
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- 🔓 **Public Access**: No authentication needed |
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## How to Use |
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### Standard Workflow (3-4 minutes total) |
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1. **Stage C - Generate Initial Latent** (~30-60s) |
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- Enter your prompt |
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- Set CFG (recommended: 7.5) and Steps (recommended: 30) |
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- Click "Generate Stage C" |
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- Wait for completion |
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2. **Wait for GPU availability** (if needed during high traffic) |
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3. **Stage B - Upscale Latent** (~30-50s) |
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- Adjust CFG (recommended: 5.0) and Steps (recommended: 15) |
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- Click "Generate Stage B" |
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- Uses the latent from Stage C automatically |
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4. **Wait again if needed** |
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5. **Stage A - Final Decode** (~60-90s) |
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- Keep "Use Tiling" checked (prevents OOM) |
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- Click "Generate Final Image" |
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- Download your high-res result! |
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### Optimal Settings 💡 |
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- **Stage C**: CFG 7-8, Steps 30-40 |
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- **Stage B**: CFG 4-6, Steps 15-20 |
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- **Stage A**: Always use tiling |
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- **Resolution Limits**: Max 3072×3072 for stability (1536×1536 per stage C/B) |
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- **For Training Data**: Generate at 3072px, then downscale to 1024px for optimal quality |
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## Technical Details |
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### Memory Management |
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Each stage runs in isolated `@spaces.GPU(duration=120)` calls: |
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- Models loaded only when needed |
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- Aggressive `torch.cuda.empty_cache()` after each stage |
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- Latents stored in-memory (automatically cleaned after 1 hour) |
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- VAE tiling enabled for Stage A decode |
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### Resolution Scaling |
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- **Stage C Input**: 512-1536px (base resolution) |
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- **Stage B Output**: 2× Stage C (1024-3072px) |
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- **Stage A Output**: Full decode to target resolution |
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- **Memory Usage**: ~20-30GB peak per stage (safe for ZeroGPU) |
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## Why This Matters |
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Many public AI spaces claim to offer "full control" but secretly override your parameters. This leads to: |
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- ❌ Inconsistent results despite changing settings |
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- ❌ Users wasting time tweaking sliders that do nothing |
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- ❌ Frustration when trying to reproduce outputs |
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This space guarantees that **your inputs = actual model parameters**. |
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## Deployment Notes |
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Built specifically for: |
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- ZeroGPU compatibility (120s duration per stage) |
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- Public/unlogged access |
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- High-resolution output (up to 3072×3072 stable) |
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- Proper parameter control |
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## Credits |
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- **Stable Cascade**: Stability AI |
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- **Original UltraPixel Concept**: Various community implementations |
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- **This Implementation**: Community-fixed version with proper parameter control |
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## License |
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Apache 2.0 |
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