Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Creating visual content that aligns with user requirements often necessitates a high degree of flexibility and precision in managing the pose, shape, expression, and arrangement of the generated elements. Traditional methods enhance the controllability of generative adversarial networks (GANs) by relying on manually labeled training datasets or pre-existing 3D models, which frequently fall short in terms of flexibility, accuracy, and adaptability. In this research, we explore a powerful yet relatively underutilized technique for controlling GANs, which allows users to "drag" specific points in an image to accurately reach designated target locations through interactive engagement, as illustrated in Fig.1. Our proposed solution, DragGAN, comprises two primary components: first, a feature-based motion supervision system that guides the handle point toward the intended position; and second, an innovative point tracking method that utilizes the discriminative features of GANs to continuously identify the handle points' locations. With DragGAN, users gain the capability to manipulate images with exceptional precision in directing pixel movements, thereby facilitating a more intuitive and user-centered design process. This approach not only enhances creative possibilities but also empowers users to achieve their desired visual outcomes more effectively.
Description
FLUX 3 Image is an AI image generation and editing model from Black Forest Labs built for detailed control over composition, image elements, and localized edits. Users can generate images from standard text prompts or define the placement of individual elements with bounding boxes. Bounding boxes operate on a 0-to-1000 coordinate grid regardless of the selected aspect ratio, providing a structured way to specify where subjects and objects should appear. For conventional text-to-image generation, the model provides prompt following and a native understanding of image composition without requiring users to manually create a layout. Its editing capabilities allow several elements to be modified within an image while other designated elements and the surrounding composition remain unchanged. FLUX 3 Image can use up to 10 reference images and combine their specified elements into a newly composed scene. Native 2K and 4K rendering is available for preserving fine details, textures, faces, and colors at high resolutions. Pixel-perfect editing enables users to change selected areas while preserving the rest of an existing image. The model is natively trained to understand image layout and composition, making it suitable for AI agents that need to plan and generate well-composed visuals from text instructions. Organizations operating image generation at scale can also license commercial model weights to fine-tune FLUX 3 Image and deploy it on their own infrastructure.
API Access
Has API
No
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
Collart AI
No
FLUX 3
No
FLUX Upscale
No
Pricing Details
Free
Open source
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
No
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
DragGAN
Founded
2023
Website
vcai.mpi-inf.mpg.de/projects/DragGAN/
Vendor Details
Company Name
Black Forest Labs
Founded
2024
Country
Germany
Website
bfl.ai/models/flux-3-image