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https://github.com/TannerGilbert/Google-Coral-Edge-TPU

Use the Google Coral USB Accelerator for deep learning.
https://github.com/TannerGilbert/Google-Coral-Edge-TPU

coral-edge-tpu coral-tpu google-coral

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Use the Google Coral USB Accelerator for deep learning.

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# Google Coral Edge TPU Examples
![](https://lh3.googleusercontent.com/83lPm0ffoxJZX63HX9EzMDKKtgLhzR4ym4iKOpudD5LuMQd329olIfkV3gcGRSb71NrPabWyKpo52YZpzO5_4Iic1AGYvFp9l7tAnGk=w1000-rw)

Google Coral edge devices allow us to run deep learning models on edge devices like the Raspberry Pi. This repository shows you how to use a Coral Edge TPU for different applications including Image Classification and Object Detection.

## Installation

To use the EdgeTPU you need the [EdgeTPU API](https://coral.withgoogle.com/software/#debian-packages) as well as the [Tensorflow Lite Runtime](https://www.tensorflow.org/lite/guide/python#install_just_the_tensorflow_lite_interpreter).

## Image Classification

* [Image Classification with pycoral](pycoral_image_classification.py)
* [Image Classification with the Tensorflow Lite Runtime](tflite_image_classification.py)
* [Image Classification with the EdgeTPU API (deprecated)](edgetpu_api_image_classification.py)

## Object Detection

* [Object Detection with pycoral](pycoral_object_detection.py)
* [Object Detection with the Tensorflow Lite Runtime](tflite_object_detection.py)
* [Object Detection with the EdgeTPU API (deprecated)](edgetpu_api_object_detection.py)

## Author
**Gilbert Tanner**

## Support me

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## License

This project is licensed under the MIT License - see the [LICENSE.md](LICENSE) file for details