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The HF Pixel Classification deep learning package seamlessly integrates pretrained image segmentation models from the Hugging Face Hub with ArcGIS, allowing you to use a variety of Hugging Face image segmentation models directly from ArcGIS. With this deep learning package, you can perform pixel classification to extract features that the given pretrained Hugging Face model is designed to segment. The deep learning package is compatible with a wide range of Hugging Face models for image segmentation tasks.
Before running a model, ensure compliance with its licensing terms, which can be found on the Hugging Face model page. Run only trusted models, as they include weights and code that could impact system security. Since model sizes vary, ensure adequate CPU/GPU memory is available for inference.
Model details
This model has the following characteristics:
- Input—8-bit, 3-band RGB imagery.
- Output—A classified raster with the same classes as in the model description.
- Compute—This workflow is compute intensive, and a GPU with a minimum CUDA compute capability of 6.0 is recommended.
- Applicable geographies—The model is expected to work globally.
- Architecture—This deep learning package uses the architecture of the chosen Hugging Face Image Segmentation models.
Access and download the model
Download the HF Pixel Classification pretrained model from ArcGIS Living Atlas of the World. Alternatively, access the model directly from ArcGIS Pro, or consume it in ArcGIS Image for ArcGIS Online.
- Browse to ArcGIS Living Atlas of the World.
- Sign in with your ArcGIS Online credentials.
- Search for HF Pixel Classification and open the item page from the search results.
- Click the Download button to download the model.
You can use the downloaded .dlpk file directly in ArcGIS Pro, or upload and use it in ArcGIS Enterprise.
Release notes
The following are the release notes:
Date | Description |
---|---|
February 2025 | First release of HF Pixel Classification |