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.

• 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.

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.

Most projects require Python 3 and libraries such as OpenCV, NumPy, TensorFlow, or Keras. Check each folder for specific dependencies.

This repository is intended for:

• Practicing and learning computer vision concepts
• Experimenting with real-world datasets and models
• Building a portfolio of mini projects

For educational and personal learning use only.