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elismasilva
updated
a
dataset
4 days ago
elismasilva
posted
an
update
5 days ago
Post
236
Hey everyone,
I've built and deployed Panorama FLUX, a Gradio app for creating ultra-wide panoramic images from three different text prompts using the FLUX.1-schnell model.
It uses a custom "Mixture of Diffusers" pipeline to generate and seamlessly blend each section of the image.
Key Features:
- Multi-Prompt Input: Control the left, center, and right of the scene with unique prompts.
- Seamless Blending: Choose between Cosine and Gaussian blending methods to eliminate seams between tiles.
- Optimized for FLUX.1-schnell: Designed for fast, 4-step generation with embedded guidance.
- Multi-Language Support: On-the-fly translation for prompts written in Korean and Chinese.
- Memory Efficient: Supports both custom (mmgp) and standard diffusers offloading for use on consumer GPUs or in Spaces.
This was a fun project that involved deep-diving into the FLUX architecture to get the tiling, guidance, and positional embeddings right.
Try it out!
🚀 Live Demo on Hugging Face Spaces:
elismasilva/flux-1-panorama
I've built and deployed Panorama FLUX, a Gradio app for creating ultra-wide panoramic images from three different text prompts using the FLUX.1-schnell model.
It uses a custom "Mixture of Diffusers" pipeline to generate and seamlessly blend each section of the image.
Key Features:
- Multi-Prompt Input: Control the left, center, and right of the scene with unique prompts.
- Seamless Blending: Choose between Cosine and Gaussian blending methods to eliminate seams between tiles.
- Optimized for FLUX.1-schnell: Designed for fast, 4-step generation with embedded guidance.
- Multi-Language Support: On-the-fly translation for prompts written in Korean and Chinese.
- Memory Efficient: Supports both custom (mmgp) and standard diffusers offloading for use on consumer GPUs or in Spaces.
This was a fun project that involved deep-diving into the FLUX architecture to get the tiling, guidance, and positional embeddings right.
Try it out!
🚀 Live Demo on Hugging Face Spaces:
elismasilva/flux-1-panorama
elismasilva
posted
an
update
26 days ago
Post
2559
I'm thrilled to launch SUP Toolbox! An AI tool for image restoration & upscaling using SUPIR, FaithDiff & ControlUnion. Built with Diffusers and Gradio UI featuring 14 custom components I developed.
Space Demo: elismasilva/sup-toolbox-app
App repository: https://github.com/DEVAIEXP/sup-toolbox-app
CLI repository: https://github.com/DEVAIEXP/sup-toolbox
Feedback is welcome!
Space Demo: elismasilva/sup-toolbox-app
App repository: https://github.com/DEVAIEXP/sup-toolbox-app
CLI repository: https://github.com/DEVAIEXP/sup-toolbox
Feedback is welcome!
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- 2 replies
elismasilva
updated
a
model
28 days ago
elismasilva
updated
a
model
about 1 month ago
elismasilva
published
3
models
about 1 month ago
elismasilva
updated
3
models
2 months ago
elismasilva
published
a
model
2 months ago
elismasilva
posted
an
update
5 months ago
Post
390
Building settings panels in? I created "PropertySheet", a new gradio component that turns your Python dataclass into a full UI! ⚡️
✅ Sliders, dropdowns, color pickers & more
✅ Collapsible groups
✅ Reset buttons & tooltips
elismasilva/gradio_propertysheet
✅ Sliders, dropdowns, color pickers & more
✅ Collapsible groups
✅ Reset buttons & tooltips
elismasilva/gradio_propertysheet
elismasilva
posted
an
update
5 months ago
Post
322
hi guys i created this gradio component based on Xenova's tokenizer playground application. This will help me in an application I'm building, I hope it will be useful for you too.
elismasilva/gradio_tokenizertextbox
gradio_tokenizertextbox - a Hugging Face Space by elismasilva
elismasilva/gradio_tokenizertextbox
gradio_tokenizertextbox - a Hugging Face Space by elismasilva
elismasilva
posted
an
update
9 months ago
Post
3070
MoD ControlNet Tile Upscaler for SDXL: Upscale Your Images with Ease! 🚀
Meet the MoD ControlNet Tile Upscaler for SDXL, a powerful tool that uses advanced technology to upscale your images without losing quality! Our app is designed to process images in tiles without leaving them blurry or with visible lines between the tiles. The result? Upscaled images with preserved details and smooth, natural transitions—all through a user-friendly interface. ✨
What MoD Upscaler Offers:
🔍 Preserved Details: Unlike traditional upscalers, the MoD ControlNet Tile Upscaler enlarges your images while maintaining clarity and adding details that might otherwise be lost. Your photos gain more definition without sacrificing original quality.
🧩 Advanced Tiling Technology: We use a smart combination of techniques to ensure natural and smooth transitions between tiles. This means your upscaled images remain consistent and high-quality, even at higher resolutions. No more visible lines or imperfections!
⚡ Fast and Efficient: You don’t need a super-powered computer! Our app is optimized to run quickly and smoothly, even on simpler machines.
🎨 Easy-to-Use Interface: You don’t have to be an expert to use the MoD ControlNet Tile Upscaler. The interface is simple, intuitive, and designed so anyone can achieve professional-quality results without hassle.
Upscale your images without losing quality and with details preserved. Try the MoD ControlNet Tile Upscaler today! 👍
Demo App: elismasilva/mod-control-tile-upscaler-sdxl
Github Code: https://github.com/DEVAIEXP/mod-control-tile-upscaler-sdxl
We use Gradio amazing interfaces.
We use Hugging Face Diffusers to build this tool and Hugging Face Spaces to run this demo.
Thank you all! 🙏
Meet the MoD ControlNet Tile Upscaler for SDXL, a powerful tool that uses advanced technology to upscale your images without losing quality! Our app is designed to process images in tiles without leaving them blurry or with visible lines between the tiles. The result? Upscaled images with preserved details and smooth, natural transitions—all through a user-friendly interface. ✨
What MoD Upscaler Offers:
🔍 Preserved Details: Unlike traditional upscalers, the MoD ControlNet Tile Upscaler enlarges your images while maintaining clarity and adding details that might otherwise be lost. Your photos gain more definition without sacrificing original quality.
🧩 Advanced Tiling Technology: We use a smart combination of techniques to ensure natural and smooth transitions between tiles. This means your upscaled images remain consistent and high-quality, even at higher resolutions. No more visible lines or imperfections!
⚡ Fast and Efficient: You don’t need a super-powered computer! Our app is optimized to run quickly and smoothly, even on simpler machines.
🎨 Easy-to-Use Interface: You don’t have to be an expert to use the MoD ControlNet Tile Upscaler. The interface is simple, intuitive, and designed so anyone can achieve professional-quality results without hassle.
Upscale your images without losing quality and with details preserved. Try the MoD ControlNet Tile Upscaler today! 👍
Demo App: elismasilva/mod-control-tile-upscaler-sdxl
Github Code: https://github.com/DEVAIEXP/mod-control-tile-upscaler-sdxl
We use Gradio amazing interfaces.
We use Hugging Face Diffusers to build this tool and Hugging Face Spaces to run this demo.
Thank you all! 🙏
elismasilva
published
a
dataset
9 months ago
elismasilva
posted
an
update
10 months ago
Post
3708
Mixture-of-Diffusers pipeline tiling for SDXL
This strives to provide a better tool for image composition by using several diffusion processes in parallel, each configured with a specific prompt and settings, and focused on a particular region of the image. The mixture of diffusion processes is done in a way that harmonizes the generation process, preventing "seam" effects in the generated image. Using several diffusion processes in parallel has also practical advantages when generating very large images, as the GPU memory requirements are similar to that of generating an image of the size of a single tile.
elismasilva/mixture-of-diffusers-sdxl-tiling
This strives to provide a better tool for image composition by using several diffusion processes in parallel, each configured with a specific prompt and settings, and focused on a particular region of the image. The mixture of diffusion processes is done in a way that harmonizes the generation process, preventing "seam" effects in the generated image. Using several diffusion processes in parallel has also practical advantages when generating very large images, as the GPU memory requirements are similar to that of generating an image of the size of a single tile.
elismasilva/mixture-of-diffusers-sdxl-tiling
elismasilva
updated
a
model
11 months ago
elismasilva
updated
2
datasets
12 months ago