Python framework that facilitates the quick development of complex video analysis applications and other series-processing based applications in a multiprocessing environment.
-
Updated
Jan 20, 2022 - Python
Python framework that facilitates the quick development of complex video analysis applications and other series-processing based applications in a multiprocessing environment.
AI-powered video podcast creation skill for coding agents. Supports Bilibili & YouTube, multi-language (zh-CN/en-US), 6 TTS engines (Edge/Azure/ElevenLabs/OpenAI/Doubao/CosyVoice), 4K Remotion rendering.
A pipeline framework for developing video and image processing application. Supports multiple GPUs and Machine Learning tooklits
Open-source AI video pipeline. Text prompt → scenario → images → video clips → editor → MP4. Self-hosted, multi-provider, MCP-ready.
CPRE488 MP2 - 1080p HDMI video pipeline for Zynq using Vivado/Vitis—TPG→VDMA with GenLock→VTC→HDMI, plus YUV422 luminance processing and FMC I²C bring-up
AI-assisted video editing pipeline — scene analysis, LLM edit planning, Shotstack rendering, and YouTube publishing.
Audio-reactive lyric visualization pipeline with subtitle alignment, rendering, and release automation.
Production-grade AI video generation system that turns a movie title, concept, and duration into a storyboarded, narrated, lip-synced MP4 using Next.js, FastAPI, Redis workers, Runpod, ElevenLabs, and FFmpeg.
面向 OpenClaw 的课程/会议视频采集、Whisper 转写、关键帧/OCR、云端处理、飞书回传与笔记校验流水线。 / Window capture, Whisper transcription, keyframe/OCR extraction, cloud processing, Feishu delivery, and validated note generation pipeline for OpenClaw-powered course and meeting videos.
FFmpeg-powered desktop tool for automated video merging and batch processing. Supports folder-based workflows, random long-form generation (27–40 min), loop processing, and precise control over clip selection — optimized for scalable content production.
Demo: Automated content pipeline — listing intake to multi-platform video publishing
Automated short-form video content pipeline for micro-SaaS distribution. Ship products fast, kill fast — the pipeline is the business.
This project provides a video pipeline using event-based sensors to capture the vision process. It can run on PC and Xilinx Pynq-Z2, using an abstraction library between the user and the architecture. The repository contains the main codes and the designs of the complete system.
Add a description, image, and links to the video-pipeline topic page so that developers can more easily learn about it.
To associate your repository with the video-pipeline topic, visit your repo's landing page and select "manage topics."