Learning Computer Vision in Robot Flow and Oak D Lite

Oak D Lite Set up:

Why should you care about Python Virtual Environment:

For example: Software A only supports up to OpenCV 1.0.0

But software B only supports OpenCV version > 2.0.0

Python Venv can help manage multiple dependencies.

Oak D set up with Python Virtual Environment:

Here’s the file architecture:

my_OAKD_project
└── folder_for_GitHub_examples
    ├── run this in your terminal: git clone https://github.com/luxonis/depthai-experiments
└── name_of_the_virtual_env_folder
    ├── bin
    │   ├── activate

1. Create an empty folder called my_OAKD_project

2. change directory to my_OAKD_project and run commands:

python3 -m venv name_of_the_virtual_env_folder
source tutorial-env/bin/activate

3. change directory to folder_for_GitHub_examples and run command:

git clone https://medium.com/r/?url=https%3A%2F%2Fgithub.com%2Fluxonis%2Fdepthai-experiments

4. depending on which example you want to run:

cd ~/Desktop/code/depthAI/depthai-experiments/gen2-blur-faces/

python3 -m pip install -r requirements.txt

python3 main.py

Sample results:

Have not finished yet. Will be added more staff : )

references:

https://stackoverflow.com/questions/51499950/where-do-i-put-my-python-files-in-the-venv-folder