https://github.com/ayeshathoi/vehicle-object-detection
SUST DLEnigma 1.0 computer vision X Vehicle Object Detection project
https://github.com/ayeshathoi/vehicle-object-detection
co-detr faster-rcnn rt-detr vehicle-detection yolov8
Last synced: 8 months ago
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SUST DLEnigma 1.0 computer vision X Vehicle Object Detection project
- Host: GitHub
- URL: https://github.com/ayeshathoi/vehicle-object-detection
- Owner: ayeshathoi
- Created: 2024-06-05T15:07:29.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-06-24T11:39:19.000Z (over 1 year ago)
- Last Synced: 2025-01-02T00:23:53.706Z (9 months ago)
- Topics: co-detr, faster-rcnn, rt-detr, vehicle-detection, yolov8
- Language: Jupyter Notebook
- Homepage:
- Size: 12.3 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Vehicle Object Detection in the context of Bangladesh Traffic
## Sust-DLenigma Kaggle Competition Solution
- Field : Computer Vision
---
## Dataset
The [dataset](https://www.kaggle.com/competitions/dl-enigma-10-sust-cse-carnival-2024/data) covers the following 9 districts in Bangladesh: Sylhet, Dhaka, Rajshahi, Mymensingh, Maowa, Chittagong, Sirajganj, Sherpur, and Khulna. This dataset contains 9825 images with 78,943 Objects with 13 different classes. It is annotated with rectangular bounding box.Participants will encounter a wide range of road types, including towns, expressways, highways, and village roads. This diversity in locations aims to challenge algorithms to perform well across various driving contexts commonly encountered on Bangladesh roads.
- Train Image Count: 5896
- Test Image Count: 1964
---
## Models
We employed transfer learning using three different approaches.
- YOLO configurations, ranging from YOLOv6L6 to the advanced YOLOv8
- Novel transformer-based models such as rtDETR and CoDETR.
- Faster R-CNN.
---
## Authors
- Ayesha Binte Mostofa (1805062)
- Sumonta Nandy Amit (1805069)
- Md. Asif Haider (1805112)
- Mashiyat Mahjabin Prapty (1805117)