muka / TPU-MobilenetSSD

Edge TPU Accelerator + MobileNet-SSD v2 + Python + Async + LattePandaAlpha/RaspberryPi3/LaptopPC

TPU-MobilenetSSD

Environment

1. LattePanda Alpha (Ubuntu16.04) / RaspberryPi3 (Raspbian) / LaptopPC (Ubuntu16.04)
2. Edge TPU Accelerator
3. USB Camera (Playstationeye)

My articles

1.I tested the operating speed of MobileNet-SSD v2 using Google Edge TPU Accelerator with RaspberryPi3 (USB2.0) and LaptopPC (USB3.1) (MS-COCO)

2.Structure visualization of Tensorflow Lite model files (.tflite)

3.I wanted to speed up the operation of the Edge TPU Accelerator as little as possible, so I tried to generate a .tflite of MobileNetv2-SSDLite (Pascal VOC) and compile it into a TPU model. Part 1

4.Since I wanted to speed up the operation of the Edge TPU Accelerator as little as possible, I transferred and learned MobileNetv2-SSD / MobileNetv1-SSD + MS-COCO with Pascal VOC and generated .tflite. Docker Part 2

5.Since we wanted to speed up the operation of the Edge TPU Accelerator as little as possible, I transferred and learned MS-COCO with Pascal VOC and generated .tflite, Google Colaboratory [GPU]. Part 3

6.Edge TPU Accelerator + custom model MobileNetv2-SSDLite .tflite generation 【Success】 Docker compilation Part.4

LattePanda Alpha Core m3 + USB 3.0 + Google Edge TPU Accelerator + MobileNet-SSD v2 + Async mode

320x240
about 80 - 90 FPS
https://youtu.be/LERXuDXn0kY

LattePanda Alpha Core m3 + USB 3.0 + Google Edge TPU Accelerator + MobileNet-SSD v2 + Async mode

640x480
about 60 - 80 FPS
https://youtu.be/OFEQHCQ5MsM

Environment construction procedure

$ wget http://storage.googleapis.com/cloud-iot-edge-pretrained-models/edgetpu_api.tar.gz
$ tar xzf edgetpu_api.tar.gz
$ cd python-tflite-source
$ bash ./install.sh

Usage

MobileNet-SSD-TPU-async.py -> USB camera animation and inference are asynchronous (The frame is slightly off.)
MobileNet-SSD-TPU-sync.py -> USB camera animation and inference are synchronous (The frame does not shift greatly.)

$ git clone https://github.com/PINTO0309/TPU-MobilenetSSD.git
$ cd TPU-MobilenetSSD
$ python3 MobileNet-SSD-TPU-async.py

Reference

• Get started with the USB Accelerator https://coral.withgoogle.com/tutorials/accelerator
• Models https://coral.withgoogle.com/models/
• Edge TPU Model Compiler https://coral.withgoogle.com/web-compiler/
• API demos https://coral.withgoogle.com/tutorials/edgetpu-api/#api-demos
• Edge TPU Benchmark https://coral.withgoogle.com/tutorials/edgetpu-faq/