Project Setup Guide (Pip & Venv)

This guide explains how to set up your environment using Python's native venv module and pip. We have a python version 3.13, please make sure you have the same version.

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Step 1: Create a Virtual Environment

This creates a local folder (usually named .venv) that contains your isolated Python executable.

# Create the virtual environment
# Windows:
python -m venv .venv

# macOS/Linux:
python3 -m venv .venv

Step 2: Activate a Virtual Environment

.venv\Scripts\activate

# Windows (PowerShell):
.\.venv\Scripts\Activate.ps1

# macOS/Linux:
source .venv/bin/activate

Step 3: Install Libraries

pip install --upgrade pip

# Install requirements
pip install -r requirements.txt

# Ensure Jupyter Lab is installed in this environment
pip install jupyterlab

Step 4: Run Jupyter Lab

jupyter lab

Important:

To run the code, you need to add the dataset in the root folder. Also, we tried a few things during this assignment, the main file is assignment.ipynb, which is the file that was based to create our documentation and presentation.

crack_segmentation.ipynb was another attempt with tensorflow.