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Face-Detection/Face Detection using Yunet/README.md

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+# YuNet Face Detection Model
+
+YuNet is a highly efficient and accurate face detection model developed by the Intel OpenVINO team. It is designed for real-time face detection and can detect multiple faces in an image, along with their facial landmarks.
+
+## Key Features
+
+- **High Accuracy**: YuNet is known for its high detection accuracy and reliability in various environments and conditions.
+- **Real-time Performance**: Optimized for real-time performance, making it suitable for applications requiring fast processing.
+- **Facial Landmarks**: In addition to detecting faces, YuNet also provides precise facial landmarks, such as eyes, nose, and mouth corners.
+
+# Face Detection using YuNet
+
+This repository contains a simple face detection script using the YuNet model for detecting faces in images. The script is written in Python and utilizes OpenCV for image processing and face detection.
+
+## Prerequisites
+
+Ensure you have the following installed on your system:
+- Python 3.6+
+- OpenCV (including the `opencv-contrib-python` package)
+- NumPy
+
+## Installation
+
+
+1. Install the required Python packages.
+   ```sh
+   pip install opencv-python opencv-contrib-python numpy
+   ```
+
+2. Download the pre-trained YuNet model.
+   If the model is not available locally, the script will automatically download it.
+
+## Usage
+
+Run the face detection script with the following command:
+```sh
+python face_detection.py -p /path/to/your/image.jpg
+```
+
+Replace `/path/to/your/image.jpg` with the actual path to the image you want to process.
+
+## Script Overview
+
+### face_detection.py
+
+This is the main script for face detection. It includes the following key functionalities:
+
+- **Model Loading:** Downloads the YuNet model if not already available.
+- **Image Reading:** Reads the input image specified by the user.
+- **Face Detection:** Detects faces and facial landmarks in the image using the YuNet model.
+- **Visualization:** Draws bounding boxes and landmarks on detected faces and displays the results.
+
+### Key Functions
+
+- `visualize_face_detections(image_path, detections)`: Visualizes the face detections on the image.
+