https://github.com/ozogxyz/swath
Georeferenced raster inference in C over GDAL, PROJ, and ONNX Runtime.
https://github.com/ozogxyz/swath
c earth-observation gdal gdal-api geospatial inference onnx-runtime proj remote-sensing
Last synced: 6 days ago
JSON representation
Georeferenced raster inference in C over GDAL, PROJ, and ONNX Runtime.
- Host: GitHub
- URL: https://github.com/ozogxyz/swath
- Owner: ozogxyz
- Created: 2026-06-23T12:48:47.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2026-06-23T14:47:37.000Z (about 1 month ago)
- Last Synced: 2026-06-23T15:29:08.211Z (about 1 month ago)
- Topics: c, earth-observation, gdal, gdal-api, geospatial, inference, onnx-runtime, proj, remote-sensing
- Language: C++
- Homepage:
- Size: 32.2 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Swath for Earth Observation ML
Rationale:
- We need a quick way to load ONNX models and make inference on edge devices. These devices often require low power. Solafune's precipitation competition penalizes the expense of using big models, for example.
- Managing virtual environments, geopandas and python etc is a nightmare on edge devices. Idea is to have a self contained executable that will leverage GDAL and load the rasters, make the transformations, load the ONNX model and run the inference.
Roadmap:
- Ideally this project would be written in Jai as a self contained program from compilation to configuration. Generate bindings for GDAL, ONNX and make an end-to-end one unit of EO-ML.
- Add NVIDIA Jetson CUDA support and/or bindings for fast inference on edge devices.