FaceCheck.ID vs LocalLens

FaceCheck.ID is an investigative search engine that accepts a face photo and returns links to public webpages containing the same or similar-looking people. Its stated uses include finding social profiles and appearances in blogs, videos, news, mugshot sites, and sex-offender websites. The service says its AI detects faces, measures similarity, and searches large data collections. Results receive scores from 0 to 100, grouped by colors from weak matches at 50–69 through certain matches at 90–100. Red flags may identify news, scam-reporting, mugshot, registry, most-wanted, or detected AI-generated-face sources. Access is provided through the web, a REST API, and a Chrome extension; examples cover Python, C#, Node.js, TypeScript, Java, C++, Kotlin, and Rust. Search images are not added to the database, history is deleted within 24 hours, and IP addresses and HTTP access are not logged. The service warns similarity is not identity determination and bans credit, employment, insurance, and tenant-screening decisions.

LocalLens is an offline visual search engine for image and video collections stored locally. It indexes directories recursively into ChromaDB, then searches indexed media using text descriptions and ranks results by similarity. Users can upload an image to find visually similar files, or combine image and text inputs to refine a search. A duplicate finder surfaces duplicate and near-duplicate image pairs using a similarity threshold. Listed formats include JPG, PNG, WebP, MP4 and MKV. The project provides a Gradio web interface and a command-line interface, and can sync indexed folders when files are added or deleted. Supported vision embedding backbones include SigLIP 2, MetaCLIP, DFN-CLIP and CLIP. LocalLens is open-source under Apache-2.0 and has a free plan, with no paid plans or usage limits stated. Portable builds are available for Windows, Linux and macOS; Linux and macOS require Python 3.10 or later and Git. The documented baseline is a 4-core CPU, 8 GB RAM, 0 GB VRAM and 20 MB storage; higher CPU, RAM and VRAM are recommended.