a PyTorch Collaborative Deep Learning Framework for Conservation.
Project description
PyTorchWildlife: An Animal Detection and Classification Package
PyTorchWildlife is a collaborative Deep Learning Framework for conservation that provides pre-trained models for animal detection and classification. This README will guide you through the steps to run a demo of the package using the Gradio interface.
Table of Contents
Prerequisites
- Python 3.x
- NVIDIA GPU (for CUDA support, although the demo can run on CPU)
Installation
1. Install through pip:
```bash pip install PyTorchWildlife ```
Running the Demo
Once the setup is complete, execute:
```bash python demo_gradio.py ```
This will launch a Gradio interface where you can:
- Perform Single Image Detection: Upload an image and set a confidence threshold to get detections.
- Perform Batch Image Detection: Upload a zip file containing multiple images to get detections in a JSON format.
- Perform Video Detection: Upload a video and get a processed video with detected animals.
License
This project is licensed under the MIT License. Refer to the LICENSE file for more details.
Copyright
Copyright (c) Microsoft Corporation. All rights reserved.
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