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https://github.com/hamza-cpp/computer_vision_labs
This repository contains a collection of lab assignments, projects, and experiments related to the Computer Vision course.
https://github.com/hamza-cpp/computer_vision_labs
camera-calibration computer-vision labs opencv
Last synced: 4 days ago
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This repository contains a collection of lab assignments, projects, and experiments related to the Computer Vision course.
- Host: GitHub
- URL: https://github.com/hamza-cpp/computer_vision_labs
- Owner: Hamza-cpp
- License: mit
- Created: 2024-10-24T15:31:49.000Z (21 days ago)
- Default Branch: main
- Last Pushed: 2024-11-07T08:55:14.000Z (8 days ago)
- Last Synced: 2024-11-07T09:42:36.602Z (8 days ago)
- Topics: camera-calibration, computer-vision, labs, opencv
- Language: Jupyter Notebook
- Homepage:
- Size: 8.81 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Computer Vision labs
This repository contains a collection of laboratory exercises for my university course in **Computer Vision**. Each lab explores key concepts and techniques in computer vision, implemented using **Python 3.10** and **OpenCV**.
## Introduction
In this course, we explore foundational techniques in computer vision, from camera calibration to advanced image processing and feature extraction.
This repository will be updated continuously as new labs are added throughout the semester.
## Lab List
### Lab 1: Camera Calibration
**Objective**: Calibrate a camera to determine intrinsic and extrinsic parameters, and correct for lens distortion.
**Topics Covered**:
- Camera intrinsic and extrinsic parameters
- Distortion coefficients
- Projection matrix
- Re-projection error
## Getting Started
To run the code in this repository, you need Python and several packages installed. You can use the following commands to set up your environment:
1. **Clone the repository**
```bash
git clone https://github.com/Hamza-cpp/Coputer_Vision_Labs.git
cd Coputer_Vision_Labs
```
2. **Create and activate a python virtual environment** (recommended)
```bash
python -m venv .venv # creation
source .venv/bin/activate # Linux & macOS
.venv\Scripts\activate # Windows
```
3. **Install the required dependencies**
```bash
pip install -r requirements.txt
```
> **Note**: If you're using Kaggle or Google Colab, you can upload and run these files directly without setting up a virtual environment.
## License
This repository is licensed under the [MIT](https://choosealicense.com/licenses/mit/) License. See the [LICENSE](LICENCE) file for more details.