Task 1 - Fingerprint recognition / Rozpoznávání otisku prstu

Zadání úlohy / EN assignment

Python toolbox:

Toolbox - Python

Note: Python installation guide is in the zip file 'python_installation_guide.pdf'. The function that has to be edited are in the 'to_do.py' file. This file includes all the data, so you don't have to download it separately.

MatlaB toolbox:

Toolbox
Data

Note: Put both the toolbox and the data in a single main directory so that the final structure is preprocessing, comparison and data. Pozn.: Obě části toolboxu i data dejte do jednoho hlavniho adresáře, aby výsledná struktura byla předzpracovani, porovnaní a data.

Fingerprint database for the final task / Databáze otisků pro finální úkol:

DataBase

Zadání 2022

Assigned fingerprints / Přiřazení otisků

According to your number + 10 in the course list of students Student list / Podle vašeho čísla + 10 v rámci seznamu k cvičení předmětu Seznam studentů

The assigned fingerprint can be found based on the number in Zadání 2020/2022. Use the DataBase to search for the matching fingerprints. / Přiřazený otisk naleznete ve složce Zadání 2020/2022 dle svého čísla. Odpovídající otisky hledejte ve DataBase databázi otisků.

Python Installation Guide

Conda

Install Anaconda on your PC. You can download it from: Anaconda Download
Create a new Conda environment called bio (all packages are installed just inside the Conda environment, not to interfere with other packages/Python versions that might exist on your PC)
```
 conda create --name bio python=3.11 
```
Activate the environment
```
 conda activate bio 
```

Install the following packages into the environment

 conda install numpy=1.24 matplotlib=3.7 jupyter ipywidgets scipy pyyaml=6.0 scikit-image

Test everything is installed properly

 python -c "import numpy as np; print(np.ones(4))"

Expected output
```
 [1. 1. 1. 1.]  
```

Pip

Install Python on your PC. The version used is 3.11; we strongly recommend using the same version. You can download Python from www.python.org/downloads
(Recommended) It is a good practice to set up a virtual environment, such as virtualenv, to keep the installed Python packages separate. This is especially useful when you work on several Python projects at the same time during the semester, and each one has different package versions.

Install the following packages using pip

 pip install numpy=1.24 matplotlib=3.7 jupyter ipywidgets scipy pyyaml=6.0 scikit-image