ONNX Model Zoo

geobase/sparsemask

By geobase · ↓ 13 · ♥ 0 · Updated 2025-08-22

What's in this repo

This page lists the files in geobase/sparsemask, including model.onnx.

  • 1 ONNX models (.onnx files)
  • 5 files, including 2 .json, 1 .md, 1 .onnx
  • Last updated 2025-08-22

ONNX files

File Size Download
onnx/model.onnx — Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

GeoAi

task = land-cover-classification

🛠 Model Purpose

This model is part of the GeoAi javascript library.

GeoAi enables geospatial AI inference directly in the browser or Node.js without requiring a heavy backend.

GeoAi pipeline accepts geospatial polygons as input (in GeoJSON format) and outputs results as a GeoJSON FeatureCollection, ready for use with libraries like Leaflet and Mapbox GL.


🚀 Demo

Explore the model in action with the interactive Demo.

📦 Model Information

  • Architecture: SparseMask
  • Source Model: https://github.com/cliffbb/oem-lightweight
  • Quantization: Yes

Note: This model only works if the input imagery contains both RGB and NIR bands.

💡 Example Usage

import { geoai } from "geoai";

// Example polygon (GeoJSON)
const polygon = {
  type: "Feature",
  properties: {},
  geometry: {
    coordinates: [
      [
        [-99.98170823334205, 50.64318249608178],
        [-99.9806018185983, 50.6431476272638],
        [-99.9807117895183, 50.642403469489295],
        [-99.98256386074388, 50.64247150726101],
        [-99.98170823334205, 50.64318249608178]
      ],
    ],
    type: "Polygon",
  },
} as GeoJSON.Feature;

// Initialize pipeline
const pipeline = await geoai.pipeline(
  [{ task: "land-cover-classification" }],
  providerParams
);
 
// Run detection
const result = await pipeline.inference({
  inputs: { polygon }
});
 
// Sample output format
// {
//     "detections": [
//      {type: 'FeatureCollection', features: Array(6)},
//      {type: 'FeatureCollection', features: Array(43)},
//      {type: 'FeatureCollection', features: Array(6)},
//      {type: 'FeatureCollection', features: Array(3)},
//      {type: 'FeatureCollection', features: Array(11)},
//      {type: 'FeatureCollection', features: Array(36)},
//      {type: 'FeatureCollection', features: Array(0)},
//      {type: 'FeatureCollection', features: Array(9)}
//    ]
//     "outputimage": GeoRawImage {data: Uint8ClampedArray(1048576), width: 512, height: 512, channels: 4, bounds: {…}, …}
// }

📖 Documentation & Demo

  • GeoBase Docs: https://docs.geobase.app/geoai
  • NPM Package: https://www.npmjs.com/package/geoai
  • Demo Playground: https://docs.geobase.app/geoai-live/tasks/land-cover-classification
  • GitHub Repo: https://github.com/decision-labs/geoai.js

Model info

onnx geospatial geobase land-cover-classification license:mit region:us
↓ 13 ♥ 0

Created: 2025-03-19

Updated: 2025-08-22

View on Hugging Face

Files (5)

.gitattributes
README.md
config.json
onnx/model.onnx ONNX
preprocessor_config.json

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