microsoft/visual-chatgpt
Visual Chatgpt
Visual-ChatGPT is a visual orchestration framework and multimodal AI pipeline designed to coordinate large language models with visual foundation models. It functions as an integration layer that enables the exchange of text and images between different AI models to automate image analysis and editing tasks without requiring additional model training.
The system differentiates itself through model-chain orchestration and prompt-based task dispatching, allowing natural language instructions to trigger specific vision models or tools. It utilizes coordinate-based region mapping and iterative mask-based inpainting to isolate image segments and apply generative fills based on textual descriptions.
The framework covers a broad capability surface including automated visual analysis for object detection and captioning, as well as a suite for text-guided image editing. These tools are organized into multi-step visual workflows that maintain a feedback loop between visual embeddings and text tokens.
Features
- Multimodal AI Orchestrators - Coordinates large language models with visual foundation models to manage complex tasks across text and image inputs.
- Foundation Models - Links pre-trained visual and linguistic foundation models via a shared interface to process multimodal inputs.
- LLM Model Integrations - Integrates large language models with visual foundation models to enable multimodal communication and image exchange.
- Image Editing - Creates and modifies images using a combination of text-guided bounding boxes, segmentation masks, and inpainting.
- Language Model Orchestration - Coordinates a sequence of different large language and vision models to execute complex multi-step visual tasks.
- Multimodal AI Pipelines - Implements a workflow for exchanging text and images between AI models to generate captions and detect objects.
- Visual Content Analysis - Generates captions, answers questions about visual elements, and detects objects within images using vision models.
- Visual Task Coordinations - Executes pre-defined flows that coordinate multiple models to complete multi-step visual operations.
- Model Dispatchers - Uses natural language instructions to select and trigger specific vision models or editing tools from a library.
- AI Image Editing - Provides a suite for modifying imagery using text-guided bounding boxes, segmentation masks, and inpainting.
- Pixel Coordinate Mappings - Maps text-guided bounding boxes to specific pixel coordinates to isolate image segments for targeted editing.
- Visual-Textual Alignments - Exchanges image embeddings and text tokens between models to refine visual analysis and generation.
- Visual Model Integration Layers - Links LLMs with visual models to perform complex visual operations without requiring additional model training.
- Visual Workflow Orchestration - Executes sequences of visual operations using pre-defined flows to complete complex tasks.
- Mask-Based Area Replacement - Uses spatial segmentation masks to replace specific image regions with new generative content based on text.
- Computer Vision Models - Visual foundation model for image generation and editing.
- Tool Use And Integration - Integrates visual foundation models for image-based interaction.
- Web Applications - Web interface connecting chat with visual foundation models.
- Web Interfaces - Web tool adding image generation and editing capabilities to chat.
- Educational Resources - Project adding visual capabilities to the standard chat interface.
