Showing 1-19 of 19 projects
Offline OCR software with batch processing, PDF support, and multi-language recognition.
Open-Sora is an open-source video generation platform enabling efficient, high-quality video creation with various models and tools.
互联网公司技术架构合集,包含微信/淘宝/微博等平台的架构资料
A Python library for generating videos from text and images using large language models and AI tools.
This project aims to reproduce the Sora (Open AI T2V model) and invites the open-source community to contribute.
Curated collection of AI-generated images and prompts showcasing the advanced capabilities of GPT-4o and GPT-Image-1.
A comprehensive UI platform that integrates various AI tools like ChatGPT, Midjourney, and more for web, PWA, desktop, and mobile development.
A Python tool that uses GPT-4, FFmpeg, and OpenCV to automatically analyze videos, extract the most interesting sections, and crop them for an improved viewing experience.
An open-source web client that enables users to create videos from text using OpenAI's Sora model.
AI-powered film production tool supporting batch video generation from scripts with Sora 2.0 integration
Mora is a Python library for generalist video generation, allowing developers to create diverse AI-powered videos.
A C++ powered OCR tool that outputs JSON for easy integration with other programs.
A curated collection of resources for cloud-native, blockchain, and web3 development, including AI and Golang.
MagicTime is a diffusion-based time-lapse video generation model for metamorphic video simulation.
MiniSora is a community exploring the implementation and future development of the Sora video generation platform.
A Python library for accelerating inference of video diffusion models using timestep embedding caching.
A multifunctional Android code editor library with features like autocomplete and syntax highlighting.
Sora AI Video Generator is a TypeScript library for generating AI-powered videos for content creators and developers.
An official implementation of a system for improving video understanding and generation with better captions.
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