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Pi inferences

This repository contains scripts to run inferences on embedded device. The scripts firstly perform insect detection on images, followed by species classification of the insect crops.

Set-up on Pi

Install Python3.9

sudo apt-get update
sudo apt-get install -y build-essential tk-dev libncurses5-dev libncursesw5-dev libreadline6-dev libdb5.3-dev libgdbm-dev libsqlite3-dev libssl-dev libbz2-dev libexpat1-dev liblzma-dev zlib1g-dev libffi-dev

wget https://www.python.org/ftp/python/3.9.0/Python-3.9.0.tar.xz
tar xf Python-3.9.0.tar.xz
cd Python-3.9.0
./configure --enable-optimizations --prefix=/usr
make

sudo make altinstall

cd ..
sudo rm -r Python-3.9.0
rm Python-3.9.0.tar.xz
. ~/.bashrc

Create venv

python3.9 -m venv ./venv_3.9
source venv_3.9/bin/activate

Update pip

/home/pi/Documents/model_data_bookworm/venv_3.9/bin/python3.9 -m pip install --upgrade pip

pip install -r requirements.txt

Run the Inference

There are several scripts which serve the following purpose:

  • auto_models.py: is an automated script which runs the insect detection and species classification when images are added to the watch_folder directory
  • test_models.py: runs the insect detection and species classification on given images
  • memory_recorder.py: records the memory usage of the Pi and saves the output to plots

The primary usecase on the Pi is therefore using auto_models.py. To run the script, use the following commands:

source venv_3.9/bin/activate
python auto_models.py
  • Add: and image to the watch_folder directory *

Then the script will run the insect detection and species classification on the image. The inference results will be saved to a csv in results directory, and an annotated version of the image, with labelled bounding boxes, will be added to annotated_images.

Run on Boot

To run the inference automatically on boot, add the following line to the end of your user crontab (using the crontab -e command).

@reboot bash -c "cd /home/pi/Desktop/model_data_bookworm && source venv_3.9/bin/activate && python auto_models.py"