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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Fooocus is a user-friendly, open-source image generation tool that operates offline, built on Gradio and utilizing Stable Diffusion XL (SDXL) technology. It is crafted for ease of use, allowing users to concentrate on crafting prompts while the software manages the intricate details. Additionally, Fooocus features an offline prompt enhancement engine based on GPT-2 and incorporates sampling upgrades, which guarantee high-quality results for both concise and extensive prompts. The software also boasts functionalities such as inpainting, outpainting, upscaling, and image prompting, employing its proprietary algorithms to deliver better performance than conventional SDXL techniques. Users can choose from various presets, including anime and realistic styles, while also benefiting from an intuitive interface that supports advanced customization options. The installation process is quick and straightforward, requiring only a few clicks, and Fooocus is compatible with systems featuring a minimum of 4GB NVIDIA GPU memory. Currently, Fooocus is in a phase of limited long-term support, primarily concentrating on addressing bugs, and there are no immediate intentions to transition to newer model architectures, which may affect long-term enhancements. This combination of features makes Fooocus a compelling choice for those interested in image generation.

Description

Recent advancements in text-based 3D object generation have yielded encouraging outcomes; however, leading methods generally need several GPU hours to create a single sample, which is a stark contrast to the latest generative image models capable of producing samples within seconds or minutes. In this study, we present a different approach to generating 3D objects that enables the creation of models in just 1-2 minutes using a single GPU. Our technique initiates by generating a synthetic view through a text-to-image diffusion model, followed by the development of a 3D point cloud using a second diffusion model that relies on the generated image for conditioning. Although our approach does not yet match the top-tier quality of existing methods, it offers a significantly faster sampling process, making it a valuable alternative for specific applications. Furthermore, we provide access to our pre-trained point cloud diffusion models, along with the evaluation code and additional models, available at this https URL. This contribution aims to facilitate further exploration and development in the realm of efficient 3D object generation.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

NVIDIA DRIVE Yes 
Stable Diffusion XL (SDXL) Yes 

Integrations

NVIDIA DRIVE No 
Stable Diffusion XL (SDXL) No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

lllyasviel

Country

China

Website

github.com/lllyasviel/Fooocus

Vendor Details

Company Name

OpenAI

Founded

2015

Country

United States

Website

openai.com/research/point-e

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