ONNX Model Zoo

geobase/wetland-segmentation

By geobase · ↓ 12 · ♥ 0 · Updated 2025-08-22

What's in this repo

This page lists the files in geobase/wetland-segmentation, including model_quantized.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_quantized.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 = wetland-segmentation

🛠 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: MaskRCNN
  • Source Model: https://opengeoai.org/examples/wetland_mapping/
  • 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: [
      [
        [-99.0983079371952, 46.60892272965549],
        [-99.0983079371952, 46.5949877901148],
        [-99.07778265091567, 46.5949877901148],
        [-99.07778265091567, 46.60892272965549],
        [-99.0983079371952, 46.60892272965549],
      ],
    ],
    type: "Polygon",
  },
} as GeoJSON.Feature;

// Initialize pipeline
const pipeline = await geoai.pipeline(
  [{ task: "wetland-segmentation" }],
  providerParams
);
 
// Run detection
const result = await pipeline.inference({
  inputs: { polygon }
});
 
// Sample output format
// {
//     "detections": {
//         "type": "FeatureCollection",
//         "features": [
//             {
//                 "type": "Feature",
//                 "properties": {
//                 },
//                 "geometry": {
//                     "type": "Polygon",
//                     "coordinates": [
//                         [
//                             [54.69479163045772, 24.766579711184693],
//                             [54.69521093930892, 24.766579711184693],
//                             [54.69521093930892, 24.766203991224682],
//                             [54.69479163045772, 24.766203991224682],
//                             [54.69479163045772, 24.766579711184693],
//                         ]
//                     ]
//                 }
//             },
//             {"type": 'Feature', "properties": {…}, "geometry": {…}}, 
//             {"type": 'Feature', "properties": {…}, "geometry": {…}},
//         ]
//     },
//     "geoRawImage": 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/wetland-segmentation
  • GitHub Repo: https://github.com/decision-labs/geoai.js

Model info

onnx geospatial geobase wetland-segmentation license:mit region:us
↓ 12 ♥ 0

Created: 2025-08-17

Updated: 2025-08-22

View on Hugging Face

Files (5)

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

Related models