Personal Python project with the aim to learn more about OpenCV and Computer Vision to support my current**Self-Driving Car Engineer ND** in the School of Autonomous Systems studies. Code is based on examples accompanying this book.
This project is made with
$ python --version
Python 3.8.9$ pip --version
pip 21.0.1 from /Users/joustava/.asdf/installs/python/3.8.9/lib/python3.8/site-packages/pip (python 3.8)and dependencies are managed with poetry
$ poetry --version
Poetry version 1.1.5
$ poetry completions fish > ~/.config/fish/completions/poetry.fishI use fish as my default shell and had to edit my PATH env to make it work, like
When all the above has been done succesfully the project dependencies need to be installed
$ Then before starting to hack away, run the tests to see if everything works as expected.
make testRun it with
make runPython version 3.8.9 asdf install python 3.8.9
https://github.com/justinmayer/virtualfish
The project layout is based on chapter Structuring Your Project of the book The Hitchhiker’s Guide to Python!.
On my developing environments I use either docker or asdf (with the required plugins) to be able to run several versions of each language I work with.
Documentation is generated with sphinx, on a mac you can install it by running
brew install sphinx-do (assuming you have homebrew installed).
Testing is awesome, checkout Testing Your Code for basics.
Follow these instructions to prepare a RPI with sd card and wifi connection.
find rpi on your network: e.g nmap -sP 192.168.2.0/24
ssh to the rpi and install these deps:
- sudo apt install pipenv
- create project folder and init pipenv sudo apt install libatlas3-base # numpy?
- install pipenv install imagezmq imutils picamera
- sudo apt install python3-opencv
until: https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/install.html
- From within /TensorFlow/models/research/ protoc object_detection/protos/*.proto --python_out=.