The early detection of damaged (partially broken) outdoor insulators in primary distribution systems is of paramount importance for continuous electricity supply and public safety. In this dataset, we present different images and videos for computer vision-based research. The dataset comprises images and videos taken from different sources such as a Drone, a DSLR camera, and a mobile phone camera.

Instructions: 

Please find the attached file for complete description

Categories:
115 Views

Parking Slot Detection dataset

angle, type, and location of each parking slot

Instructions: 

Parking Slot Detection dataset

angle, type, and location of each parking slot

Categories:
63 Views

Recently, self-driving vehicles have been introduced with several automated features including lane-keep assistance, queuing assistance in traffic-jam, parking assistance and crash avoidance. These self-driving vehicles and intelligent visual traffic surveillance systems mainly depend on cameras and sensors fusion systems.

Categories:
797 Views

This archive contains images and labels for the Idly-Dosa-Vada (IDV) dataset, for use with Yolo (and Tensorflow) object detection frameworks.

Instructions: 

This archive contains images and labels for the Idly-Dosa-Vada (IDV) dataset, for use with Yolo (and Tensorflow) object detection frameworks.

The dataset contains 1009 images, and corresponding labels.

The dataset was created by using euclidaug, using only 6 images per class.

 

Folder structure after extracting idv-dataset-files.zip:

out_images - contains all training images

out_labels - contains labels for each image, in Yolo format

 

For usage, refer to the IEEE-DL-TAP instructions, which are derived from https://github.com/prabindh/yolo-bins/tree/master/capacito

 

Step 1: Generate full list of image files, for use in the training process. In Windows, this is done using the below command:

 

dir /s/b *.jpg > trainingfile.txt

 

Step 2: Using the above file, and the labelled images and labels, start the training process with Yolo using instructions at https://github.com/prabindh/yolo-bins/tree/master/capacito

 

Step 3: Perform inference using Yolo

Categories:
226 Views

This is a reservoir dataset including a large number of figures. Reservoir simulation, an important part of the petroleum industry, a powerful tool helping oil companies understand the reservoir better.

In this dataset, there more than 10,000 figures are showing in different period oilfield development. From the beginning to the end, we keep some variables constant while some changes to make clear the influences of different parts.

Last Updated On: 
Wed, 10/30/2019 - 03:16

 We photographed Giemsa-stained thick blood smear slides from 150 P. falciparum infected patients at Chittagong Medical College Hospital, Bangladesh, using a smartphone camera for the different microscopic field of views. Images are captured with 100x magnification in RGB color space with a 3024×4032 pixel resolution. An expert slide reader manually annotated each image at the Mahidol-Oxford Tropical Medicine Research Unit (MORU), Bangkok, Thailand. We de-identified all images andtheir annotations, and archived them at the National Library of Medicine (IRB#12972).

Categories:
1340 Views