*.jpg *.txt

This dataset was collected with the goal of providing researchers with access to a collection of hundreds of images for efficient classification of plant attributes and multi-instance plant localisation and detection. There are two folders, i.e. Side view and Top View.Each folder includes label files and image files in the.jpg format (.txt format). Images of 30 plants grown in 5 hydroponic systems have been collected for 66 days. Thirty plants of three species (Petunia, Pansy and Calendula) were grown in a hydroponic system for the purpose of collecting and analysing images.


Semi-supervised video object segmentation aims to leverage the ground truth object masks given for the first frame to segment video sequences at the pixel level. OVOS is a dataset to evaluate the performance of video object segmentation under occlusions.


Accurate fire load (combustible objects) information is crucial for safety design and resilience assessment of buildings. Traditional fire load acquisition methods, such as fire load survey, which are time-consuming, tedious, and error-prone, failed to adapt to dynamic changed indoor scenes. As a starting point of automatic fire load estimation, fast recognition and detection of indoor fire load are important. Thus, A dataset containing images of indoor scenes and annotations of instance segmentation is developed in this research.


A dataset with more comprehensive category labels, richer data scenes, and more diverse image sizes were constructed. All images had been labeled.
The num of all annotations is 8232. This dataset is openly accessible to all future research workers for rapid deployment of mask detection subtasks during the New Crown out- break and in all possible future scenarios.


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.


Parking Slot Detection dataset

angle, type, and location of each parking slot


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.


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


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).