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Detector-Py is a real-time object detection project using the YOLOv8 model and the ultralytics library. The project captures real-time images from the webcam and detects objects present in the scene, displaying the result in a video window.

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Detector-Py

Detector-Py is a real-time object detection project using the YOLOv8 model and the ultralytics library. The project captures real-time images from the webcam and detects objects present in the scene, displaying the result in a video window.

imagem detectorpy

Technologies Used

  • Python 3.9.13
  • YOLOv8 (You Only Look Once, version 8)
  • Ultralytics

Prerequisites

Before running the project, you need to install the dependencies. It is recommended to use a virtual environment (such as venv or virtualenv).

1. Clone this repository:

git clone https://github.com/yourusername/detector-Py.git

2. Create and activate a virtual environment (optional, but recommended):

python -m venv venv
source venv/bin/activate  # For Linux/Mac
.\venv\Scripts\activate   # For Windows

3. Install the project dependencies:

pip install ultralytics

How to Run the Project

After installing the dependencies, you can run the code to start object detection:

python main.py

The script will open the webcam and start detecting objects in real-time, showing the results on the screen.

Project Features

  • Real-Time Object Detection: The project uses YOLOv8 to detect various objects in the scene captured by the webcam.
  • Immediate Visualization: The object detection results are displayed directly on the screen, highlighting the identified objects with bounding boxes.

Future Expansions

You can use this code as a foundation to expand your idea, whether to implement features like object tracking, detection in recorded videos, integration with other computer vision tools, or any other project related to real-time object detection.

About

Detector-Py is a real-time object detection project using the YOLOv8 model and the ultralytics library. The project captures real-time images from the webcam and detects objects present in the scene, displaying the result in a video window.

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