Mendeley Link : https://data.mendeley.com/datasets/pwyyg8zmk5/2

Poribohon-BD is a vehicle dataset of 15 native vehicles of Bangladesh. The vehicles are: i) Bicycle, ii) Boat, iii) Bus, iv) Car, v) CNG, vi) Easy-bike, vii) Horse-cart, viii) Launch, ix) Leguna, x) Motorbike, xi) Rickshaw, xii) Tractor, xiii) Truck, xiv) Van, xv) Wheelbarrow. The dataset contains a total of 9058 images with a high diversity of poses, angles, lighting conditions, weather conditions, backgrounds. All of the images are in JPG format. The dataset also contains 9058 image annotation files. These files state the exact positions of the objects with labels in the corresponding image. The annotation has been performed manually and the annotated values are stored in XML files. LabelImg tool by Tzuta Lin has been used to label the images. Moreover, data augmentation techniques have been applied to keep the number of images comparable to each type of vehicle. Human faces have also been blurred to maintain privacy and confidentiality. The data files are divided into 15 individual folders. Each folder contains images and annotation files of one vehicle type. The 16th folder titled ‘Multi-class Vehicles’ contains images and annotation files of different types of vehicles. Poribohon-BD is compatible with various CNN architectures such as YOLO, VGG-16, R-CNN, DPM.

Vehicle Detection Poribohon BD

## Overview

Vehicle Detection Poribohon BD is a dataset for object detection tasks - it contains Vehicle annotations for 9,085 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

A Bangladeshi local vehicle image dataset with annotation for classification.

Poribohon-BD is an object detection dataset published in Data in Brief journal (Q2) in 2020. The original dataset is meant for object detection. This dataset, however, is prepared for classification by deleting 2 classes

Paper Details: Tabassum, Shaira; Ullah, Md. Sabbir ; Al-nur, Nakib Hossain; Shatabda, Swakkhar (2020), “Poribohon-BD”, Mendeley Data, V2, doi: 10.17632/pwyyg8zmk5.2

Some vehicle images were generated using Big GAN which is available in the generated directory. Notebook link: https://www.kaggle.com/naifislam/vehicle-image-generation

Poribohon

## Overview

Poribohon is a dataset for object detection tasks - it contains Vehicles annotations for 8,962 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Dataset

This dataset was created by Md. Jahidul Islam

Released under Database: Open Database, Contents: Database Contents

Contents

Poribohon BD 2sets

## Overview

Poribohon BD 2sets is a dataset for object detection tasks - it contains Vehicles annotations for 687 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [Public Domain license](https://creativecommons.org/licenses/Public Domain).

The combined dataset was constructed by merging real-world images from Sorokh-Poth and Poribohon-BD, focusing exclusively on authentic, high-quality visuals of Bangladeshi road vehicles. Ten common vehicle categories were standardized and uniformly annotated to ensure consistency. With rigorous augmentation techniques applied—such as rotation, flipping, scaling, and brightness adjustments—the dataset achieved balance across all classes. It comprises 35,320 images (36.8 GB), divided into 70% training, 20% validation, and 10% testing, ensuring robustness and diversity for deep learning-based vehicle classification tasks.