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--- |
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title: Imagen |
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emoji: 🌖 |
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colorFrom: pink |
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colorTo: red |
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sdk: gradio |
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sdk_version: 5.22.0 |
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app_file: main.py |
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pinned: false |
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license: other |
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short_description: Generate and edit images |
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--- |
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# Diffusion Models App |
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A unified interface for text-to-image and image-to-image generation using Hugging Face models. |
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## Features |
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- 🖼️ **Text to Image**: Generate images from text prompts |
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- 🔄 **Image to Image**: Transform images using text prompts |
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- 🧠 **ControlNet Support**: Built-in ControlNet depth model for enhanced image transformations |
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- 🌐 **Flexible Models**: Use inference endpoints or on-device models |
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- 🚀 **Dual Interface**: Web UI and API endpoints |
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## Deployment Notes |
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### IMPORTANT: Using ControlNet on Hugging Face Spaces |
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For ControlNet to work correctly: |
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1. Import `spaces` before any `torch` or CUDA-related imports |
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2. Select GPU hardware in Space settings |
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3. Add your HF_TOKEN as a Repository Secret (Settings → Repository Secrets) |
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4. Do NOT commit any sensitive tokens to the repository |
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If you encounter CUDA initialization errors, ensure spaces package is imported first. |
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## Usage |
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### Text to Image |
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1. Enter your text prompt |
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2. Optionally provide a negative prompt to exclude unwanted elements |
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3. Choose a model or use the default |
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4. Click "Generate Image" |
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### Image to Image |
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1. Upload an image |
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2. Enter a prompt to guide the transformation |
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3. Choose between HF inference API or ControlNet on-device model |
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4. Click "Transform Image" |
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--- |
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tags: |
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- diffusers |
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- stable-diffusion |
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- text-to-image |
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- image-to-image |
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- depth-estimation |
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- controlnet |
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- spaces |
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- huggingface-hub |
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