https://github.com/mustafaozvardar/object-detection-opencv

This project implements a real-time object detection system using OpenCV and a pre-trained SSD MobileNet model. The application captures video from your webcam and detects objects in the video feed, labeling them with their corresponding names and confidence scores.
https://github.com/mustafaozvardar/object-detection-opencv

artificial-intelligence computer-science computer-vision object-detection opencv python

Last synced: 4 days ago
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This project implements a real-time object detection system using OpenCV and a pre-trained SSD MobileNet model. The application captures video from your webcam and detects objects in the video feed, labeling them with their corresponding names and confidence scores.

• Host: GitHub
• URL: https://github.com/mustafaozvardar/object-detection-opencv
• Owner: mustafaozvardar
• License: mit
• Created: 2024-08-10T12:13:17.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-08-12T21:43:04.000Z (3 months ago)
• Last Synced: 2024-08-13T00:30:11.890Z (3 months ago)
• Topics: artificial-intelligence, computer-science, computer-vision, object-detection, opencv, python
• Language: Python
• Homepage:
• Size: 11.9 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# 🎯 **Real-Time Object Detection with OpenCV**

This project implements a real-time object detection system using OpenCV and a pre-trained SSD MobileNet model. The application captures video from your webcam and detects objects in the video feed, labeling them with their corresponding names and confidence scores.

## **🛠️ Requirements**

To run this project, you'll need to install the following libraries:

- **OpenCV** `opencv-python`

You can install the library using **pip**. 

**opencv-python==4.6.0.66**

**Then, you need to download these files and upload them into your project:**

**--> Link: Object_Detection_Files**

## **Model and Config Files**

**Model Weights:** frozen_inference_graph.pb - The pre-trained model weights file.

**Model Config:** ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt - The configuration file for the SSD MobileNet model.

## **COCO Names**

**coco.names:** Contains the names of the 80 object categories used by the COCO dataset. These are the classes that the model can detect.

## **🎮 How to Use**

**Prepare Files:** Ensure the model files (frozen_inference_graph.pb, ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt) and coco.names are located in the same directory as your script.

**Run the Script:** Start the script using Python. Make sure your webcam is active.

**--> python main.py**

**Object Detection:** The script will display the video feed with bounding boxes around detected objects, along with labels showing the object names and confidence scores.

**Exit:** Press the q key to close the video feed window and stop the script.

## **📄 License**

This project is licensed under the MIT License. Feel free to use, modify, and distribute this project as you wish.