Cars Dataset (Positive and Negative)

Published: 5 May 2021| Version 1 | DOI: 10.17632/dvnntk22h6.1
Contributor:

Description

The dataset is organized into 2 folders (positive and negative) which contains total 2,800 images. The data is split into 1,230 positive images (car images) and 1,570 negative images (background images). The dataset is arranged in such a way that HAAR Cascade Classifier training can be done with it. This structure is described in OpenCV docs (https://docs.opencv.org/3.4/dc/d88/tutorial_traincascade.html). Positive Directory structure: 'img' folder witch contains all positive images and 'info.dat' file which contains all positive image descriptions. The first element of the line is the filename, followed by the number of object annotations, followed by numbers describing the coordinates of the objects bounding rectangles (x, y, width, height). /img img1.jpg img2.jpg . . . . info.dat Inside the file info.dat: img/img1.jpg 1 140 100 45 45 img/img2.jpg 2 100 200 50 50 50 30 25 25 Negative Directory structure: 'img' folder witch contains all negative images and 'bg.txt' file witch contains all negative image directory list. /img -img1.jpg -img2.jpg . . . . bg.txt Inside the file bg.txt: img/img1.jpg img/img2.jpg . . . .

Files

Steps to reproduce

Made by cropping cars and negative images from various open source videos.

Institutions

Khulna University of Engineering and Technology

Categories

Arts and Humanities

Licence