PyTorch implementation of some learning rate schedulers for deep learning researcher.
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Updated
Sep 6, 2022 - Python
PyTorch implementation of some learning rate schedulers for deep learning researcher.
Python library and utility for PLATEAU datasets by MLIT Japan
Turn Japan's PLATEAU 3D city models into a queryable, hazard-aware buildings.parquet. Pre-built bundles for 29 cities; SQL via DuckDB; 3D Tiles + PMTiles + FlatGeobuf out of the box.
CityGML parsing and STEP conversion toolkit extracted from Paper-CAD
Print-quality city visualizations from Project PLATEAU (Japan's national 3D urban dataset). Posters, prints, social — PNG / SVG / PDF / mp4, with mandatory CC BY 4.0 attribution.
新宿駅周辺屋内3Dマップ
Learn geospatial data analysis with DuckDB using real Kyoto City POI data (23,111 points). Interactive browser-based tutorials with OpenStreetMap & PLATEAU datasets.
3D都市モデル(Project PLATEAU)建築物モデルPMTiles
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