https://github.com/codedpro/computer-vision-practices
This repository is a collection of mini projects and learning resources for computer vision.
https://github.com/codedpro/computer-vision-practices
Last synced: 19 days ago
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This repository is a collection of mini projects and learning resources for computer vision.
- Host: GitHub
- URL: https://github.com/codedpro/computer-vision-practices
- Owner: codedpro
- Created: 2025-06-28T14:32:08.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-07-06T07:31:48.000Z (10 months ago)
- Last Synced: 2025-07-06T08:35:05.065Z (10 months ago)
- Language: Python
- Homepage:
- Size: 4.88 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
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README
## Computer Vision Mini Projects & Learning Courses
This repository is a collection of mini projects and learning resources for computer vision. Each folder contains a self-contained project or course module, designed to help you learn and apply computer vision techniques using Python and popular libraries.
---
### Projects Overview
- **Color Detection** (`Color Detection/`):
- Detect and classify colors in images using OpenCV.
- Includes utility functions and a main script for demonstration.
- **Image DC** (`image dc/`):
- General image processing tools and scripts for various computer vision tasks.
- **Parking iC** (`Parking iC/`):
- Detects empty and occupied parking spaces using image classification.
- Includes a pre-trained model and sample parking lot images.
- **Pneumonia iC** (`Pneumonia iC/`):
- Classifies chest X-ray images to detect pneumonia using deep learning.
- Contains a trained Keras model and label files.
- **Weather iC** (`Weather iC/`):
- Classifies weather conditions (cloudy, rain, shine, sunrise) from images.
- Includes organized datasets for training and validation.
---
## How to Use
1. Choose a project folder of interest.
2. Review the `main.py` file and any supporting scripts or data.
3. Install required dependencies (see code or add your own `requirements.txt`).
4. Run the project using Python 3.
## Requirements
Most projects require Python 3 and libraries such as OpenCV, NumPy, TensorFlow, or Keras. Check each folder for specific dependencies.
## Purpose
This repository is intended for:
- Practicing and learning computer vision concepts
- Experimenting with real-world datasets and models
- Building a portfolio of mini projects
## License
For educational and personal learning use only.