Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/rcode879/haar-cascade-detector
A human recognition program that can detect human faces and bodies.
https://github.com/rcode879/haar-cascade-detector
Last synced: about 1 month ago
JSON representation
A human recognition program that can detect human faces and bodies.
- Host: GitHub
- URL: https://github.com/rcode879/haar-cascade-detector
- Owner: Rcode879
- Created: 2024-08-27T00:10:45.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-08-27T00:20:53.000Z (5 months ago)
- Last Synced: 2024-08-28T02:31:51.306Z (5 months ago)
- Language: Python
- Size: 9.77 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Face and Body Detection using OpenCV
This Python script utilizes OpenCV to perform real-time detection of frontal faces, side faces, and full bodies using a webcam. The program captures video frames, processes them to detect various features, and displays the results with visual annotations.
## Features
- **Real-time face and body detection**: Detects frontal faces, side faces, and full bodies using Haar Cascade classifiers.
- **Visual annotations**: Draws rectangles, lines, and text around detected faces and bodies.
- **Midpoint calculation**: Computes and displays the midpoint of detected frontal faces.
- **Dynamic updates**: Continuously processes the video stream and updates the display in real-time.
## Installation
1. **Clone the repository**:
```bash
git clone https://github.com/Rcode879/Haar-cascade-detector.git
cd Haar-cascade-detector
```
2. **Install the required libraries**:
Ensure you have Python installed (preferably Python 3.6 or higher) and install the required dependencies:
```bash
pip install opencv-python
```
## Usage
1. **Run the script**:
Execute the script to start the webcam and begin detecting faces and bodies:
```bash
python detector.py
```
2. **Interact with the application**:
- The webcam feed will open in a window named `frame`.
- The program will highlight detected faces and bodies with annotations.
- To stop the program, press the `q` key.
## How It Works
- **Capture Video**: Initializes the video capture from the default webcam.
- **Set Resolution**: Configures the capture to HD resolution (1280x720).
- **Load Haar Cascades**: Loads pre-trained Haar Cascade classifiers for detecting frontal faces, side faces, and full bodies.
- **Process Each Frame**:
- Converts each frame to grayscale for efficient detection.
- Uses the Haar Cascade classifiers to detect frontal faces, side faces, and bodies.
- Draws rectangles, lines, and text annotations around the detected objects.
- Displays the annotated frame in a window.
- **Exit on Key Press**: Ends the loop and releases resources when the `q` key is pressed.
## Dependencies
- [OpenCV](https://opencv.org/) (cv2)
## Acknowledgements
This project utilizes the OpenCV library for image processing and computer vision tasks. Haar Cascade classifiers are provided by OpenCV's pre-trained models.