QMedia vs SentrySearch

QMedia is an open-source multimedia AI search engine for content creators. It searches and extracts information from text, images, and short videos, combining those formats in a multimodal retrieval and question-answering system. Its web service displays content and sources as cards with image, text, and short-video breakdowns. The project can run locally for offline search and question answering over private data. The web service, RAG search and Q&A service, and image, text, and video model service can be deployed separately. The standalone model service offers an API for image and text encoding, video transcription, and image OCR. Documented model options include CLIP, BGE, Qanything OCR, LLaVA, and Faster Whisper, with local Ollama model switching. Google content search is configurable but disabled by default, as is video service use in the RAG server configuration. The RAG service depends on a separate mm_server service. QMedia is self-hosted, available through its web service, and licensed under MIT.

SentrySearch searches video footage by text or reference image and can return trimmed matching clips. It splits videos into overlapping chunks, embeds footage and queries into a shared vector space, and stores video vectors in a local ChromaDB database. Search options include text, image, anomaly highlights, and optional reranking of candidate clips. The project documents embedding backends including Gemini, Alibaba DashScope Qwen Cloud, LiteLLM, local Qwen3-VL, and MLX for Apple Silicon. Its local backend runs on the user's machine without an API key and is described as private and offline-capable. With Qwen Cloud, local video chunks are uploaded by the official SDK to DashScope-managed temporary object storage for processing. The scanner recursively finds MP4 and MOV files, including footage not from Tesla Sentry Mode. An optional Tesla overlay can use supported footage metadata for speed, GPS, and time information. The project requires Python 3.11 or later and FFmpeg or imageio-ffmpeg. It is open source under Apache-2.0 and supports Linux, macOS, Windows, and self-hosting.