Peking University and Rabbit Tech launch UniWorld-V2, an image editing model using the UniWorld-R1 RL framework. It excels in detail control, Chinese instruction understanding, and surpasses traditional supervised learning.....
CUHK MMLab, with Beihang & SJTU, introduces a structured image generation system, overcoming AI's limitations in charts & formulas. It advances data visualization where models like FLUX.1 & GPT-Image fall short.....
No description available
OpenAI has officially launched the gpt-image-1 API, marking the opening of its highly anticipated 4o image generation capabilities to developers. According to AIbase, this API is lauded by the community as the world's strongest 'image generation' tool due to its high-fidelity image generation, diverse visual styles, and powerful integration of world knowledge. The release announcement has generated significant excitement among AI developers and the creative community, with relevant documentation now publicly available via the OpenAI website and Playground platform. Core features: High-fidelity and diverse style generation
The Image Gen MCP Server is a general AI image generation service that provides cross - platform and multi - model image generation capabilities for various LLM chatbots through the Model Context Protocol (MCP) standard protocol. It supports multiple image models from OpenAI and Google, enabling seamless conversion from text conversations to visual content.
An image generation and editing tool based on the OpenAI GPT-4o/gpt-image-1 model, supporting image generation through text prompts, image editing (such as repair, extension, composition, etc.), and being compatible with multiple MCP clients.
An MCP server for image generation and editing based on the OpenAI gpt-image-1 model, supporting the creation and modification of images through text prompts, providing convenient integration methods and rich configuration options.
This project implements an MCP server that provides image generation and editing functions through OpenAI's gpt-image-1 model. It supports generating images based on text descriptions, editing or repairing images based on reference images, and saving the results locally.
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
