GlobalMLBuildingFootprints
SeaGOAT
GlobalMLBuildingFootprints | SeaGOAT | |
---|---|---|
9 | 7 | |
1,270 | 910 | |
1.8% | - | |
6.0 | 9.7 | |
about 1 month ago | 3 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
GlobalMLBuildingFootprints
- FLaNK Stack for 25 September 2023
- Anyone know where can I find building footprint data for Chile?
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Does anyone know where to find the global raster set of buildings??
Well, that is simply wrong. In the course of trying to find the source of my raster, I have discovered Google's Open Buildings project which covers the whole of Africa and part of Asia, and Microsoft's global ML building footprints which has much more extensive coverage.
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Does anyone know where to find the global raster set of buildings?
What you describe is exactly what Microsoft's Global ML Building Footprints repository on Github https://github.com/microsoft/GlobalMLBuildingFootprints
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Laminar Research should bringing open source MS Building Foot Print into XP12 in future patch
It’s not public domain, it’s licensed under the ODbL
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3D OpenStreetMap
A large majority of the elevations and building footprints donated to OpenStreetMap worldwide were contributed by Microsoft over the past 5 years from Bing Maps. Microsoft now also incorporates OpenStreetMap data into Bing Maps.
https://github.com/microsoft/GlobalMLBuildingFootprints/
- Global Building Footprints: Worldwide building footprints derived from satellite imagery
- Worldwide building footprints derived from satellite imagery from Microsoft
SeaGOAT
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Reviewing AI Code Search Tools
In this blog post, I’ll be comparing 3 distinct AI-first code search tools I recently came across: Cody (developed by late-stage startup, Sourcegraph), SeaGOAT (an open-source project that was trending on HN last week), and Bloop (an early-stage YC startup). I’ll be evaluating them along the dimensions of user-friendliness as well as their accuracy.
- FLaNK Stack for 25 September 2023
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Show HN: SeaGOAT – local, “AI-based” grep for semantic code search
Ruby (.rb)
https://github.com/kantord/SeaGOAT#what-programming-langauge...
What are some alternatives?
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
pyobd - open source program for OBD2 car diagnostics
every-breath-you-take - Heart Rate Variability Training with the Polar H10 Monitor
leafmap - A Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment
hyperdx - Resolve production issues, fast. An open source observability platform unifying session replays, logs, metrics, traces and errors powered by Clickhouse and OpenTelemetry.
tinyfeed - Generate a static HTML page from a collection of feeds.
Rerender_A_Video - [SIGGRAPH Asia 2023] Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation
USBuildingFootprints - Computer generated building footprints for the United States
FLaNK-Halifax - Community over Code, Apache NiFi, Apache Kafka, Apache Flink, Python, GTFS, Transit, Open Source, Open Data