trailbehind/DeepOSM

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1330 stars · 184 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DeepOSM is a Python application that trains neural networks with TensorFlow to classify roads and features in satellite imagery using OpenStreetMap data as training labels. It downloads NAIP satellite imagery and OSM PBF extracts, generates training data, and renders predictions of mis-registered roads as JPEGs.

Use cases

• train a neural network to detect roads in satellite imagery
• find errors in OpenStreetMap road data
• generate training data from OSM and NAIP imagery
• classify features in aerial photos with deep learning
• compare OSM data against satellite imagery predictions

When to choose

• you want to train a deep learning model on OpenStreetMap labels and satellite imagery
• you need to identify mis-registered or missing roads in OSM data
• you want a ready-made TensorFlow pipeline for geospatial imagery classification

When to avoid

• you need actively maintained software or recent TensorFlow compatibility
• you want general-purpose satellite image analysis beyond road/feature classification
• you cannot provide AWS credentials to download requester-pays NAIP imagery

Facets

application · maturity abandoned

machine-learning deep-learning computer-vision image-processing geospatial machine-learning computer-vision python openstreetmap satellite-imagery tensorflow naip road-detection neural-networks maps geospatial linux macos docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="trailbehind/DeepOSM")