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CVML Lab - Computer Vision and Machine Learning

This repository contains all the code, experiments, and resources developed as part of the CVML (Computer Vision and Machine Learning) Lab at Dharmsinh Desai University. The structure follows a weekly format, with each subfolder corresponding to the work completed during a specific lab session.

The repository includes practical implementations of foundational and advanced techniques in image processing, computer vision, and machine learning using Python, OpenCV, and relevant libraries. These exercises are aligned with the official lab manual and are designed to promote hands-on learning.

You can find the complete lab manual here.

Repository Structure

Each folder contains well-commented code, sample inputs (images or datasets), and corresponding outputs.

  • week_01/: Basic image processing operations (e.g., resizing, cropping)
  • week_02/: fundamental image processing
  • week_03/: contrast enhancement techniques
  • week_04/: effect of sampling and quantization on an image
  • week_05/: smoothing filters in spatial domain
  • week_06/: restoration of images
  • week_07/: split and merge the R, G, B component from the color image.
  • week_08/: segmentation and morphological operations using binary immages
  • week_09/: usage of cv2.connectedcomponentswithstats function
  • week_10/: image classification using K-means clustering algorithm

Technologies Used

  • Python 3.x
  • OpenCV (cv2)
  • NumPy
  • Matplotlib
  • Scikit-learn (for ML parts)
  • (More libraries as the lab progresses...)

Getting Started

  1. Clone the repository: 
    git clone https://github.com/userofmeet/CVML.git
cd CVML

Notes

  • Code is modular, beginner-friendly, and well-commented.
  • Each week aligns with a specific section of the CVML Lab Manual.

Author

Meet Jain Electronics and Communication Engineering Dharmsinh Desai University

License

This project is open-source and available under the MIT License.