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Commit 51b6a452 authored by Sachin Joglekar's avatar Sachin Joglekar Committed by TF Object Detection Team
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Add an end-to-end Colab for leveraging CenterNet on mobile 

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research/object_detection/g3doc/running_on_mobile_tf2.md
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# Running TF2 Detection API Models on mobile # Running TF2 Detection API Models on mobile
[![TensorFlow 2.3](https://img.shields.io/badge/TensorFlow-2.3-FF6F00?logo=tensorflow)](https://github.com/tensorflow/tensorflow/releases/tag/v2.3.0) [![TensorFlow 2.4](https://img.shields.io/badge/TensorFlow-2.4-FF6F00?logo=tensorflow)](https://github.com/tensorflow/tensorflow/releases/tag/v2.4.0)
[![Python 3.6](https://img.shields.io/badge/Python-3.6-3776AB)](https://www.python.org/downloads/release/python-360/) [![Python 3.6](https://img.shields.io/badge/Python-3.6-3776AB)](https://www.python.org/downloads/release/python-360/)
**NOTE:** This support was added *after* TF2.3, so please use the latest nightly **NOTE:** This document talks about the *SSD* models in the detection zoo. For
for the TensorFlow Lite Converter for this to work. details on our (experimental) CenterNet support, see
[this notebook](../colab_tutorials/centernet_on_device.ipynb).
[TensorFlow Lite](https://www.tensorflow.org/mobile/tflite/)(TFLite) is [TensorFlow Lite](https://www.tensorflow.org/mobile/tflite/)(TFLite) is
TensorFlow’s lightweight solution for mobile and embedded devices. It enables TensorFlow’s lightweight solution for mobile and embedded devices. It enables
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