This package is a one-stop solution for downloading, cleaning, analyzing street view imagery
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Updated
Jul 1, 2026 - Python
This package is a one-stop solution for downloading, cleaning, analyzing street view imagery
A machine learning framework for road safety risk assessment using street-level imagery. It retrieves road networks from OpenStreetMap, downloads imagery through the Mapillary API, extracts road characteristics using image segmentation models, and predicts segment-level road safety risk scores.
Urban sampling and extraction of Google Street View imagery using Selenium and OpenCV for panorama generation and geospatial analysis.
RAPID: A Reproducible Multi-Agent Pipeline for Interpretable Disaster Damage Assessment from Satellite and Street-View Imagery
Perceiving Multidimensional Disaster Damages from Street-View Images Using Visual-Language Models https://doi.org/10.5194/ica-abs-10-310-2025, 2025.
Rubric-guided MLLM scoring and GRACE calibration for locally grounded streetscape perception.
Estimates visible tree coverage from Google Street View imagery via semantic/panoptic segmentation.
Extracts metrically-scaled facade textures from Mapillary panoramas using OSM footprints and SfM point clouds as the rectification target. No GPU, no model weights.
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