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Deep learning package to detect objects using Hugging Face object detection models. A brief summary of the item is not available. Add a brief summary about the item.

‎Deep learning package by

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Item created: Dec 10, 2024 Item updated: Feb 17, 2025 Number of downloads: 104

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Description

The HF Object Detection deep learning package seamlessly integrates pretrained object detection models from the Hugging Face Hub with ArcGIS, enabling you to utilize a variety of Hugging Face object detection models directly from ArcGIS. With this deep learning package, you can detect objects that the given pretrained Hugging Face model is designed to detect. The deep learning package is compatible with a wide range of Hugging Face models for Object Detection 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

Feature class containing bounding boxes 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 Object Detection Models page, given the model ID.

Sample results
Here are a few results from the model.

huggingface_id: savioratharv/pothole_detection


huggingface_id: hilmantm/detr-traffic-accident-detection



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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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