https://github.com/kiritoind/autonomous-driving-object-detection
The ideas and methodologies implemented in this project are inspired by YOLO (You Only Look Once) version 8, a state-of-the-art object detection model known for its speed and accuracy. The system leverages YOLOv8 to detect and classify objects on the road
https://github.com/kiritoind/autonomous-driving-object-detection
algorithms bounding-boxes convolutional-neural-networks neural-network nonmaxima-suppression object-detection python3 tensorflow unet yolo
Last synced: about 5 hours ago
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The ideas and methodologies implemented in this project are inspired by YOLO (You Only Look Once) version 8, a state-of-the-art object detection model known for its speed and accuracy. The system leverages YOLOv8 to detect and classify objects on the road
- Host: GitHub
- URL: https://github.com/kiritoind/autonomous-driving-object-detection
- Owner: kiritoInd
- License: mit
- Created: 2024-04-12T11:55:09.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-12T12:24:44.000Z (about 1 year ago)
- Last Synced: 2025-01-05T23:26:55.854Z (5 months ago)
- Topics: algorithms, bounding-boxes, convolutional-neural-networks, neural-network, nonmaxima-suppression, object-detection, python3, tensorflow, unet, yolo
- Language: Jupyter Notebook
- Homepage:
- Size: 43.9 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
- License: LICENSE
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README
# Autonomous Driving System
Welcome to the Autonomous Driving System project! This repository contains the codebase for an autonomous vehicle system designed to detect and respond to road conditions, objects, and traffic signs using machine learning and computer vision technologies.
```Final ouput```
https://github.com/kiritoInd/Autonomous-Driving-Object-Detection/assets/96108214/0af7c4af-4065-4dfb-abe3-6388ce385099
```Input```
https://github.com/kiritoInd/Autonomous-Driving-Object-Detection/assets/96108214/23086dbc-df78-42b8-be9e-91670269de72
## Acknowledgments
The ideas presented in this notebook came primarily from the two YOLO papers. The implementation here also took significant inspiration and used many components from Allan Zelener's GitHub repository. The pre-trained weights used in this exercise came from the official YOLO website.
- Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi - [You Only Look Once: Unified, Real-Time Object Detection](https://arxiv.org/abs/1506.02640) (2015)
- Joseph Redmon, Ali Farhadi - [YOLO9000: Better, Faster, Stronger](https://arxiv.org/abs/1612.08242) (2016)
- Allan Zelener - [YAD2K: Yet Another Darknet 2 Keras](https://github.com/allanzelener/YAD2K)
- The official YOLO website (https://pjreddie.com/darknet/yolo/)