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Deep learning package to classify pixels using Hugging Face image segmentation models. A brief summary of the item is not available. Add a brief summary about the item.

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Item created: Dec 10, 2024 Item updated: Feb 4, 2025 Number of downloads: 66

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Description

The HF Pixel Classification deep learning package seamlessly integrates pretrained image segmentation models from the Hugging Face Hub with ArcGIS, enabling you to utilize 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. 


Using the model
Follow the guide to use the modelBefore using this model, ensure that the supported deep learning libraries are installed. For more details, check Deep Learning Libraries Installer for ArcGIS


Fine-tuning the model
This model cannot be fine-tuned using ArcGIS tools.

Input
8-bit, 3-band RGB imagery.

Output

Classified raster containing masks of various objects in the image.


Applicable geographies

The model is expected to work globally.


Model architecture

This deep learning package utilizes the model from the Hugging Face Image Segmentation Models page, given the model ID.

Sample results
Here are a few results from the model.

huggingface_id: ratnaonline1/segFormer-b4-city-satellite-segmentation-1024x1024


An in-depth description of the item is not available.

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Terms of Use

https://downloads.esri.com/blogs/arcgisonline/esrilogo_new.png This work is licensed under the Esri Master License Agreement.

No special restrictions or limitations on using the item's content have been provided.

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