This project is meant to give a concise overview of the YOLO models family. Following a series of projects, we'll go through YOLO's development history, technical breakthroughs, use cases, and practical projects. Although I plan to use several packages, our main focus will be the Ultralytics package and its API.
Although a requirements.txt is provided, it's recommended to install all packages individually due to the use of PyTorch and possible system requirements to use CUDA.
You can begin by creating a Python virtual environment using the tool of your choice:
# Using Python's virtualenv
python -m venv .venvInstall the common packages using pip.
pip install notebook opencv-python pytube imageio After that, proceed to install PyTorch using the official documentation page.
Next, proceed to install the Ultralytics package.
pip install ultralytics