https://github.com/bettenoch/yolo_real_time_object_detector
The YOLO Real-Time Object Detector leverages the ultralytics package to provide robust object detection capabilities. This project is designed to identify and classify objects in images, video streams, and live webcam feeds with high accuracy and efficiency.
https://github.com/bettenoch/yolo_real_time_object_detector
numpy object-detection object-tracking pandas python3 real-time-processing ultralytics yolov8
Last synced: 2 months ago
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The YOLO Real-Time Object Detector leverages the ultralytics package to provide robust object detection capabilities. This project is designed to identify and classify objects in images, video streams, and live webcam feeds with high accuracy and efficiency.
- Host: GitHub
- URL: https://github.com/bettenoch/yolo_real_time_object_detector
- Owner: Bettenoch
- License: mit
- Created: 2024-08-12T09:00:51.000Z (almost 2 years ago)
- Default Branch: master
- Last Pushed: 2024-08-13T10:40:34.000Z (almost 2 years ago)
- Last Synced: 2025-04-14T00:49:58.837Z (about 1 year ago)
- Topics: numpy, object-detection, object-tracking, pandas, python3, real-time-processing, ultralytics, yolov8
- Language: Python
- Homepage:
- Size: 7.08 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# YOLO Real-Time Object Detector
YOLO Real-Time Object Detection with Ultralytics
## Table of Contents
1. [Project Titles and Internal Titles](#project-titles-and-internal-titles)
2. [Introduction](#introduction)
3. [Technologies Used](#technologies-used)
4. [Launch](#launch)
5. [Illustrations](#illustrations)
6. [Scope of Functions](#scope-of-functions)
7. [Use Examples](#use-examples)
8. [Project Status](#project-status)
9. [Sources](#sources)
## Project Titles and Internal Titles
- **Project Name**: YOLO Real-Time Object Detector
- **Repository Link**: [GitHub Repository](https://github.com/yourusername/yolo-object-detector)
- **Internal Title**: Real-Time Object Detection with YOLO
## Introduction
The YOLO Real-Time Object Detector utilizes the ultralytics package to deliver high-performance object detection capabilities. This project enables real-time object detection in images, video streams, and webcam feeds using the YOLO (You Only Look Once) algorithm. The system is designed for applications requiring immediate and accurate object recognition, making it suitable for use in various fields such as surveillance, autonomous vehicles, and interactive systems.
## Technologies Used
- **Python**: 3.x
- **Ultralytics YOLO**: For state-of-the-art object detection
- **OpenCV**: For image and video processing
- **NumPy**: For numerical operations
- **Dependencies**:
- `ultralytics` = "^8.0.0"
- `opencv-python` = "^4.6.0"
- `numpy` = "^1.23.0"
## Launch
To launch the YOLO Real-Time Object Detector, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/yourusername/yolo-object-detector.git
cd yolo-object-detector
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Run the object detection script:
```bash
python detect.py --source
```
- Replace `` with the path to an image file, a video file, or `0` for webcam.
## Illustrations
- **Real-Time Detection**: Displays real-time object detection in a video stream or webcam feed.
- **Detection Results**: Annotated images showing detected objects and their bounding boxes.
## Scope of Functions
- **Real-Time Object Detection**: Detects and classifies objects in real-time from video streams or live webcam feeds.
- **Object Tracking**: Keeps track of detected objects across frames in video feeds.
- **Customizable Detection**: Allows configuration for different YOLO models and detection parameters.
## Use Examples
- **Webcam Detection**: Run the script with `python detect.py --source 0` to use your webcam for live object detection.
- **Image File Detection**: Use `python detect.py --source path/to/image.jpg` to detect objects in a static image file.
- **Video File Detection**: Apply detection to a video file with `python detect.py --source path/to/video.mp4`.
## Project Status
The YOLO Real-Time Object Detector is actively developed with ongoing improvements to detection accuracy and performance. Future updates will include additional features such as enhanced tracking capabilities and support for more object detection models.
## Sources
- [YOLO Documentation](https://github.com/ultralytics/yolov5)
- [Ultralytics GitHub Repository](https://github.com/ultralytics/yolov5)
- [OpenCV Documentation](https://docs.opencv.org/)