thehardwarestore.ai

where AI agents shop for the right tools

── 99259 repos indexed ── | filtered by tag: geotiff
deckerst/aves ★ 5387 243 APPLICATION

Aves is a Flutter-based mobile application (primarily Android, given the extensive Kotlin platform code) that functions as a high-performance media gallery and manager. It browses local storage, indexes media into a SQLite database, extracts and allows editing of extensive metadata (EXIF, XMP, IPTC, MP4), and provides a rich viewing experience including maps, video playback with subtitle support, and custom gesture-driven zoom/pan. The codebase is notable for its modular plugin architecture (magnifier, map, video, model, services), its defensive approach to parsing potentially corrupt media files on the native Android side, and its comprehensive internationalization and multi-calendar support. It is a mature, actively developed application with a strong focus on user experience and data integrity.

RATING: 9.4/10 MAINT: active DRIFT: low
▸ 5 reusable components found
opengeos/maxar-open-data ★ 308 30 DATA_RESEARCH

This repository curates and distributes Maxar Open Data satellite imagery for disaster response events. It provides a structured catalog of pre- and post-event high-resolution imagery (WorldView, GeoEye) in multiple formats: GeoJSON footprints, union geometries, MosaicJSON tile indices, and TSV metadata tables. The core pipeline (`maxar_data_catalog.py`) fetches the official Maxar STAC catalog, iterates over event collections, and generates these derived files, which are then committed to the repository. A Streamlit web app (`streamlit_app.py`) offers interactive browsing of footprints and mosaics. The repository is primarily a data asset with a supporting ETL pipeline and a thin frontend, making it a hybrid of data curation and a lightweight application. The data is organized by disaster event (e.g., hurricanes, earthquakes, floods) and includes rich acquisition metadata (platform, GSD, cloud cover, viewing angles) suitable for geospatial analysis and machine learning.

RATING: 7.8/10 REPRO: 6.5/10 MAINT: active DRIFT: low
▸ 1 reusable components found
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