Python framework that facilitates the quick development of complex video analysis applications and other series-processing based applications in a multiprocessing environment.

A pipeline framework for developing video and image processing application. Supports multiple GPUs and Machine Learning tooklits

Director Agent + vision critic + image, video, music & voice models - all on a single AMD Instinct MI300X.

Open-source AI video pipeline. Text prompt → scenario → images → video clips → editor → MP4. Self-hosted, multi-provider, MCP-ready.

AI-assisted video editing pipeline — scene analysis, LLM edit planning, Shotstack rendering, and YouTube publishing.

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-powered speculative video content pipeline. Generates cinematic 'what if' matchup videos from concept to YouTube — research, script, voice, character-consistent video, publish. ~$1.43/video.

Perception receipts for AI video pipelines. Cross-writer bit-exact under default settings (SHA-256 stable across writers in any language). Zero runtime dependencies; pure stdlib core. ~1.1 KB per video; per-frame CRC32 + schema + versioning. Useful now, improving continuously.

Audio-reactive lyric visualization pipeline with subtitle alignment, rendering, and release automation.

Queue-based AI video rendering worker with voice, subtitles, ffmpeg and upload flow.

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.

AI-powered automated video reel generator · Python pipeline · input to output

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.

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.

One prompt -> full narrated MP4. Fully local AI video pipeline using ComfyUI (SD 1.5), FFmpeg, and Windows TTS. No SaaS APIs.

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.

Distributed AI video creation pipeline — orchestrate ComfyUI (FLUX + Wan2.2), Kokoro TTS, and audio tools across machines via SSH.

Multimodal video annotation pipeline — local GPU end-to-end (audio, vision, OCR, faces, brands, chat, music). Turns any long-form video with people into a time-aligned event corpus for synthetic-data construction, training-set curation, and analysis.