Computer vision workshop

Code for training and using AI models for computer vision tasks: classification, object detection and segmentation

We are going to introduce you to different Python libraries which can be used for training and using AI models for computer vision tasks. The Python libraries which we are going to use are PyTorch, TorchVision and OpenCV.

During the workshop we are going to train AI models for the following computer vision tasks:

• Classification
• Object detection
• Segmentation

How is this workshop structured?

Each task is divided into three different folders: 01_classification, 02_object_detection and 03_segmentation. You have been given some "boilerplate" code and some tasks to complete in each folder. The tasks can be found in the folders which all consists of their own README.md The tasks are designed to help you understand how to train and use AI models for computer vision tasks.

Please don't be afraid to ask questions if you are stuck or if you need help. We are here to help you and to make sure that you understand the concepts which are being presented.

Set-up

How to get the code

This will copy the files we have made to your home at jupyterhub.

cp /data/scratch/computer-vision-workshop ./ -r

How to run the code

Aka. how to set up the development environment.

Before we get started we must activate the correct Python environment. This is to ensure we have downloaded all the necessary Python libraries. We have already created a Python environment for you, so you don't have to worry about that.

1. Open a terminal in JupyterLab by clicking on the + sign in the top left corner and then click on Terminal.
2. Run the following command to activate the correct Python environment:

source /data/scratch/.computer-vision-ws-venv/bin/activate