OpenCV-Masterclass

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OpenCV-Masterclass

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Description: A comprehensive repository of OpenCV functions, covering basics to advanced topics like image transformations, object detection, face recognition, and AR. Includes well-organized folders, examples, and tutorials to boost your computer vision projects. Perfect for beginners and experts alike!

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# OpenCV-Masterclass: Stunning Functions and Applications

This repository is a comprehensive collection of OpenCV-based functions, tutorials, and projects designed to unlock the power of computer vision. From basic operations to advanced tasks like object detection, face recognition, and augmented reality, this repository is perfect for both beginners and experienced developers.

---

## Features

- **Basic Operations**: Image reading, resizing, cropping, and color transformations, drawing and Annotation
- **Image Transformations**: Rotation, scaling, and perspective transformations.
- **Feature Detection**: Detecting keypoints using SIFT, SURF, and ORB.
- **Object Detection and Tracking**: Implementing YOLO, Haar cascades, and template matching.
- **Video Processing**: Frame extraction, video capture, and real-time processing.
- **Augmented Reality**: Overlaying AR elements on images and videos.

---

## Getting Started

### Prerequisites
- Python 3.6 or later
- OpenCV library (see installation below)

### Installing OpenCV
Follow these steps to install OpenCV:

1. **Install OpenCV via pip**:
```bash
   pip install opencv-python
```

2.	**(Optional) Install Additional Modules:**
    For more functionalities, such as reading advanced image/video formats:

```bash
    pip install opencv-python-headless 
```

3.	**Verify Installation:**
Run the following script to confirm OpenCV is installed:

```bash
import cv2
print(cv2.__version__)
```

4.	**For Conda Users:**
If you’re using Anaconda:
```bash
conda install -c conda-forge opencv
```

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