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https://github.com/ayu-ano/basic_object-detection
End to End Basic object Detection using Open CV
https://github.com/ayu-ano/basic_object-detection
background-substraction-algorithm cv2 masking math mixture-of-gaussians numpy python3
Last synced: about 1 month ago
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End to End Basic object Detection using Open CV
- Host: GitHub
- URL: https://github.com/ayu-ano/basic_object-detection
- Owner: ayu-ano
- Created: 2024-03-13T16:11:18.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-09-18T18:27:26.000Z (5 months ago)
- Last Synced: 2024-11-13T19:39:31.647Z (3 months ago)
- Topics: background-substraction-algorithm, cv2, masking, math, mixture-of-gaussians, numpy, python3
- Language: Python
- Homepage:
- Size: 10.6 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Basic Object Detection using OpenCV
This repository contains code for basic object detection using OpenCV in Python. The code uses a simple background subtraction technique along with Euclidean distance-based tracking to detect and track objects in a video stream.
## Prerequisites
Make sure you have the following dependencies installed:
- Python 3.x
- OpenCV
- NumPy## Vehicle Detection

## Output

This script will use a pre-recorded video (`highway2.mp4`), apply background subtraction, detect objects, and track them using Euclidean distance.## Customization
You can modify the following parameters in the `main.py` script:
- ROI (Region of Interest): Adjust the ROI to focus on a specific area in the video frame.
- Thresholds: Modify the thresholds used in background subtraction and contour detection to improve object detection accuracy.
- Keybindings: Press 'ESC' to exit the application.## Acknowledgments
- Inspired by the [OpenCV](https://opencv.org/) library.