/Computer-Vision

This repository is related to all about Computer Vision - an A-Z guide to the world of Computer Vision. This supplement contains the implementation of algorithms, statistical methods, and techniques (in Python)

Primary LanguageJupyter Notebook

๐Ÿ‘๏ธ Welcome to the Computer Vision Compendium!๐Ÿ‘‹๐Ÿ›’

1-Introduction

๐Ÿš€ Explore the vast landscape of computer vision through our comprehensive repository, serving as your A-Z guide to this captivating field. Whether you're delving into image processing, object detection, or deep learning, you'll find a treasure trove of resources here to deepen your understanding and hone your skills.

๐Ÿ” What We Offer:

1-Algorithm Implementations: Dive into meticulously crafted implementations of key computer vision algorithms, from classic techniques to cutting-edge methods.

2-Statistical Methods: Harness the power of statistical analysis for robust image interpretation and feature extraction.

3-Pythonic Solutions: Our repository is entirely Python-based, offering clear and concise code snippets for seamless integration into your projects.

๐Ÿ’ก Why Choose Us?:

1-Comprehensive Coverage: We've curated a comprehensive collection of resources covering every aspect of computer vision, providing you with a holistic learning experience.

2-Hands-On Learning: Put theory into practice with hands-on examples and practical exercises designed to reinforce your understanding.

3-Accessible to All: Whether you're a beginner or an expert, our repository caters to learners of all levels, offering something valuable for everyone.

๐Ÿ‘ฅGet Involved:

Contribute: Help us expand our repository by contributing your own implementations, insights, and optimizations. Together, we can build a richer resource for the entire computer vision community.

Engage: Join the discussion, ask questions, and share your experiences on our forums. Connect with fellow enthusiasts and expand your network. Learn and Grow: Embark on your journey through the world of computer vision, and let our repository serve as your trusted companion along the way.

Also please subscribe to my youtube channel!

๐ŸŒŸ Join us as we unravel the mysteries of computer vision, one algorithm at a time. Let's empower each other to push the boundaries of what's possible in this fascinating domain!

Star this repo if you find it useful โญ

๐Ÿ“ฌContact

If you want to contact me, you can reach me through social handles.

๐Ÿ“•Course 01 - ๐Ÿ‘๏ธ Introduction of Computer Vision

๐Ÿ‘๏ธ Chapter1: - Introduction

Topic Name/Tutorial Video Code
๐ŸŒ1- What is computer Visionโญ๏ธ 1 Colab icon
๐ŸŒ2-Computer Vision Tasks and Applicationsโญ๏ธ 1-2 Colab icon
๐ŸŒBest Free Resources to Computer Visionโญ๏ธ --- ---

๐Ÿ“šChapter2: - Image As Function

Topic Name/Tutorial Video Notbook
๐ŸŒ1-Images as Functions Part 1?โญ๏ธ 1 Colab icon
๐ŸŒ2-Images as Functions Part 2?โญ๏ธ 1 Colab icon
๐ŸŒ3-Define an Image as a Function (Quiz)โญ๏ธ 1-2 Colab icon
๐ŸŒ4-Color Planes and Color Image as a Function(Quiz)โญ๏ธ 1-2-3 Colab icon
๐ŸŒ5- Digital Images 1-2 Colab icon
๐ŸŒ6-Compute Image Size Quiz --- Colab icon
๐ŸŒ7-Read image in Matlab and Python --- Colab icon
๐ŸŒ8-Image Size and Data Type Quiz/Solution 1 Colab icon
๐ŸŒ9-Crop an Image 1 Colab icon
๐ŸŒ10-Add 2 Images 1-2-3 Colab icon
๐ŸŒ11-Multiply image by a scaler and Blend 2 Images 1-2-3 Colab icon
๐ŸŒ12-Common Types of Noise 1 Colab icon
๐ŸŒ13-Image Difference 1-2-3 Colab icon
๐ŸŒ14-Generate Gaussian Noise 1 Colab icon
๐ŸŒ15-Effect of Sigma on Gaussian Noise 1-2-3 Colab icon
๐ŸŒ16-Apply Gaussian Noise 1-2 Colab icon
๐ŸŒ17-Displaying Images in Matlab and Python 1 Colab icon

๐Ÿ“šChapter3: - Filtering

Topic Name/Tutorial Video NoteBook
๐ŸŒ1- What is Filtering? 1 Colab icon
๐ŸŒ2- What is Gaussian Noise? 1-2 Colab icon
๐ŸŒ3- Weighted Moving Average? 1-2 Colab icon
๐ŸŒ4- Correlation Filtering? 1 Colab icon
๐ŸŒ5- Averaging Filter? 1 Colab icon
๐ŸŒ6- Gaussian Filter? 1-2 Colab icon
๐ŸŒ7- Gaussian Filter with Matlab and Python? 1 Colab icon
๐ŸŒ8- Remove Noise?(r) 1-2 Colab icon

๐Ÿ“šChapter4: - Linearity and Convolution '

Topic Name/Tutorial Video NoteBook
๐ŸŒ1- Introduction of linear intuition of filtering 1 Colab icon
๐ŸŒ2- Impulse Function and Response 1 Colab icon
๐ŸŒ4- Filtering an Impulse Signal 1 Colab icon
๐ŸŒ5- Correlation vs Convolution 1-2 Colab icon
๐ŸŒ5-Properties of Convolution 1 Colab icon
๐ŸŒ6-Computational Complexity and Separability 1 Colab icon
๐ŸŒ7-Boundary Issues 1 Colab icon
๐ŸŒ8-Methods 1 Colab icon
๐ŸŒ9-Explore Edge Options 1 Colab icon
๐ŸŒ10-Practicing with Linear Filters 1-2 Colab icon
๐ŸŒ11-Different Kinds of Noise 1-2-3 Colab icon

๐Ÿ“šChapter5: - Filters as Templates

Topic Name/Tutorial Video NoteBook
๐ŸŒ1- Introduction of Filters as templates, 1D correlation and 2D Correlations 1-2 -3 Colab icon
๐ŸŒ2- Find Tempalte ID 1-2 Colab icon
๐ŸŒ3- Template Matchingโญ๏ธ 1-2-3-4-5 Colab icon

๐Ÿ“šChapter6: - Edge detection: Gradients

Topic Name/Tutorial Video NoteBook
๐ŸŒ1- Pattern Finding and Feature Detection 1 Colab icon
๐ŸŒ2- Understanding Edges in Images: Why They Matter in Visual Perception 1-2 Colab icon
๐ŸŒ3- Edge Detectionโญ๏ธ 1 Colab icon
๐ŸŒ4-Derivatives and Edgesโญ๏ธ 1 Colab icon
๐ŸŒ5-What is Gradientsโญ๏ธ 1 Colab icon
๐ŸŒ6-Finite Differencesโญ๏ธ 1 Colab icon
๐ŸŒ7-Partial Derivatives of an Imageโญ๏ธ 1 Colab icon
๐ŸŒ8-The Discrete Gradientโญ๏ธ 1-2 Colab icon

๐Ÿ’ป Workflow:

  • Fork the repository

  • Clone your forked repository using terminal or gitbash.

  • Make changes to the cloned repository

  • Add, Commit and Push

  • Then in Github, in your cloned repository find the option to make a pull request

print("Start contributing for Computer Vision")

โš™๏ธ Things to Note

  • Anybody interested in learning and contributing to computer Vision repository
  • There are no hard prerequisites other than a dedication to learning
  • Some experience with the following will be beneficial:,C++ Programming, Basic of Computer
  • You can only work on issues that have been assigned to you.
  • If you want to contribute the algorithm, it's preferrable that you create a new issue before making a PR and link your PR to that issue.
  • If you have modified/added code work, make sure the code compiles before submitting.
  • Strictly use snake_case (underscore_separated) in your file_name and push it in correct folder.
  • Do not update the README.md.

๐Ÿ” Explore more

Explore cutting-edge tools and Python libraries, access insightful slides and source code, and tap into a wealth of free online courses from top universities and organizations. Connect with like-minded individuals on Reddit, Facebook, and beyond, and stay updated with our YouTube channel and GitHub repository. Donโ€™t wait โ€” enroll now and unleash your Computer Vision potential!โ€

โœจTop Contributors

We would love your help in making this repository even better! If you know of an amazing Computer Vision course or you know intrested Computer Vision related tutorial/Video that isn't listed here, or if you have any suggestions for improvement in any course content, feel free to open an issue or submit a course contribution request.

                   Together, let's make this the best AI learning hub website! ๐Ÿš€

Thanks goes to these Wonderful People. Contributions of any kind are welcome!๐Ÿš€