Image Processing Course 🚀

Welcome to the Image-Processing-Course repository!
This collection is a comprehensive compilation of practical and advanced image processing projects implemented in Python using OpenCV, TensorFlow, PyTorch, and other relevant libraries. It serves as a hands-on guide for learning, experimenting, and mastering computer vision techniques.

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🧠 Purpose

The goal of this repository is to provide a rich set of mini-projects and notebooks that teach fundamental to advanced concepts in image processing and computer vision. Ideal for students, researchers, and engineers.

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🗂️ Project Structure

Each project is self-contained in its own directory or notebook. Here's an overview of the available modules:

Project	Description
Adaptive Threshold for Image/Webcam	Dynamic binarization for images and real-time streams
Advanced Histogram Equalization	CLAHE and other histogram improvement techniques
Basic Yolov8n and MTCNN for Face Recognition	Simple implementation of YOLO and MTCNN for detecting and recognizing faces
Better Coin Detection	Improved contour-based coin recognition
Cartooning Image	Convert photos to cartoon-style images
Dominant Colors	K-Means-based dominant color extraction
Homography	Perspective transformation between images
Image Compression	Image compression using K-Means clustering
Image Cropping	Manual and automatic image cropping tools
Image Deblurring	Restore blurred images using filters
Image Denoising	Noise reduction using Gaussian and median filters
Image Inpainting	Restore missing regions of images
Image Restoration	Degradation + restoration pipeline
Image Rotation	Image rotation using affine transforms
Image Segmentation with GrabCut	Foreground-background segmentation with GrabCut
Otsu Binarization for Car Plate	License plate binarization with Otsu's method
Pose Estimation	Skeleton pose detection using pre-trained models
Simple BoundingBox	Draw bounding boxes on detected objects
Simple Coin Counter	Count circular objects (coins) in images
Simple Color Tracker	Real-time color tracking using HSV thresholding
Simple Deep Face Detection	Deep learning model to detect faces
Simple Deep Face Recognition	Deep learning-based facial recognition
Simple Mask RCNN	Instance segmentation using Mask R-CNN
Simple Open Pose	Body joint detection using OpenPose
Simple Parking Space Counter	Detect and count parking spaces
Simple Skin Detection	Detect skin areas in images
Simple Tensorflow Object Detection	Basic object detection using TensorFlow models
Simple Word Detection	Text recognition using image pre-processing

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📦 Requirements

Most projects use the following packages:

opencv-python
numpy
matplotlib
scikit-image
scikit-learn
tensorflow
torch
mediapipe
ultralytics

Install all dependencies:

pip install -r requirements.txt

Some projects may require specific versions. Check each notebook or .py file for details.

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🧪 Usage

You can run each .ipynb notebook directly in Jupyter or Colab.

For Python scripts:

python project_name.py

For real-time webcam-based projects, make sure your system has an accessible camera.

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📝 License

This repository is licensed under the MIT License.

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🙋‍♂️ Author

Awrsha Follow me on GitHub for more machine learning and image processing projects.

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⭐️ Show Your Support

If you find this repository useful, please consider giving it a ⭐️ and sharing it with your peers.

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🔗 Contributions

Feel free to open issues or pull requests to improve or add more projects!