https://github.com/hamza-cpp/img-processing-labs
https://github.com/hamza-cpp/img-processing-labs
Last synced: 10 months ago
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- Host: GitHub
- URL: https://github.com/hamza-cpp/img-processing-labs
- Owner: Hamza-cpp
- Created: 2024-05-02T15:44:45.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-04T17:55:30.000Z (over 1 year ago)
- Last Synced: 2025-02-01T22:12:22.840Z (12 months ago)
- Language: Jupyter Notebook
- Size: 2.24 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Image Processing Labs
This project contains a series of Jupyter notebooks and Python scripts that demonstrate the use of Fourier Transform for image analysis. Each lab focuses on different aspects of Fourier Transform and image processing techniques.
## Project Structure
- `lab1/` - Contains the first lab notebook focusing on image contrast correction and histogram visualization.
- `lab2/` - Contains the second lab notebook which covers image noise analysis and filtering techniques.
- `lab3/` - Contains the third lab notebook and a `ressources.py` script. This lab introduces Fourier Transform analysis with functions such as `fourier2d_all`, `fourier2d_single_frenquency`, `fourier2d_many_frequencies`, and `fourier2d_vue3d_old`.
- `lab4/` - Contains the fourth lab notebook which delves into image segmentation techniques.
- `lab5/` - Contains the fifth lab notebook focusing on image segmentaation using ***Region Growing*** Algorithm
Each lab folder also contains a `resources/` directory with images and other files used in the lab exercises.
## Prerequisites
- Python 3.10 or higher
- pip
## Installation
1. Clone this repository to your local machine.
```sh
git clone https://github.com/Hamza-cpp/img-processing-labs
```
2. Navigate to the project directory.
```sh
cd ./path/to/img-processing-labs
```
3. Create and activate the virtual env:
```sh
python -m venv .venv && source .venv/bin/activate
```
4. Install the necessary dependencies using pip:
```sh
pip install -U pip
pip install -r requirements.txt
```
## Running the Notebooks
To run the notebooks, you need to have Jupyter installed. If not, you can install it with:
```bash
pip install jupyter
```
Then, you can start Jupyter by running:
```bash
jupyter notebook
```
This will open a web browser where you can navigate to the notebook files **.ipynb** and open them.
## Contributing
Contributions are welcome. Please open an issue to discuss your idea or submit a Pull Request.