Portable Computer Vision: TensorFlow 2.0 on a Raspberry Pi
Tiny, low-cost object detection and classification.
For roughly $100 USD, you can add deep learning to an embedded system or your next internet-of-things project.
Are you just getting started with machine/deep learning, TensorFlow, or Raspberry Pi? Perfect, this blog series is for you!
In this series, you will read :
- Deploy a pre-trained image classification model (MobileNetV2) using TensorFlow 2.0 and Keras.
- Convert a model to TensorFlow Lite, a model format optimized for embedded and mobile devices.
- Accelerate inferences of any TensorFlow Lite model with Coral’s USB Edge TPU Accelerator and Edge TPU Compiler.
- Employ transfer learning to re-train MobileNetV2 with a custom image classifier.
The first post in this series will walk you through build materials, installation, and deploying MobileNetV2 to your Raspberry Pi.
you can read this blog series on https://towardsdatascience.com/portable-computer-vision-tensorflow-2-0-on-a-raspberry-pi-part-1-of-2-84e318798ce9