TFODRPi Tensorflow Object Detection Walkthrough with Raspberry Pi

The following repository will allow you to leverage Tensorflow Object Detection models that have been converted to TFLite on a Raspberry Pi.

Steps

Step 1:

Walk through the TFOD tutorial up to step 12 to generate TFLite files:https://github.com/Vicky-Projects/object-detection

Step 2:

Clone the current repository onto your Raspberry Pi:https://github.com/Vicky-Projects/object-detection-Raspberry-Pi

Step 3:Install the required dependencies onto your Raspberry Pi

pip3 install opencv-python

sudo apt-get install libcblas-dev

sudo apt-get install libhdf5-dev

sudo apt-get install libhdf5-serial-dev

sudo apt-get install libatlas-base-dev

sudo apt-get install libjasper-dev

sudo apt-get install libqtgui4

sudo apt-get install libqt4-testv

echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" | sudo tee /etc/apt/sources.list.d/coral-edgetpu.list

curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -

sudo apt-get update

sudo apt-get install python3-tflite-runtime

Step 4:

Copy your detect.tflite model into the same repository and update the labels.txt file to represent your labels.

Step 5.

Run real time detections using the detect.py script

python3 detect.py