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Drone Dataset (UAV) Dataset

135913
Tagdrones
Taskobject detection
Release YearMade in 2019
LicenseMIT
Download364 MB

Introduction #

Released 2019-09-26 ·Mehdi Özel

Authors introduce the Drone Dataset (UAV), a comprehensive collection of 1,359 images, all belonging to a single class: drone. This dataset is meticulously split into train and valid subsets, comprising 1,012 and 347 images, respectively. The primary purpose of creating this dataset is to facilitate the training of Unmanned Aerial Vehicles (UAVs) in the critical tasks of guidance and collision avoidance as they navigate through the increasingly crowded skies alongside other UAVs.

This dataset collected by author in Istanbul (Turkey) for a UAV Competition. Most Images downloaded from Google and Yandex with image scrapers. Also, some YouTube videos used to scrap some images.

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Dataset LinkHomepageDataset LinkGitHub

Summary #

Drone Dataset (UAV) is a dataset for an object detection task. Possible applications of the dataset could be in the drone inspection domain.

The dataset consists of 1359 images with 1486 labeled objects belonging to 1 single class (drone).

Images in the Drone Dataset (UAV) dataset have bounding box annotations. All images are labeled (i.e. with annotations). There are 2 splits in the dataset: train (1012 images) and valid (347 images). The dataset was released in 2019.

Dataset Poster

Explore #

Drone Dataset (UAV) dataset has 1359 images. Click on one of the examples below or open "Explore" tool anytime you need to view dataset images with annotations. This tool has extended visualization capabilities like zoom, translation, objects table, custom filters and more. Hover the mouse over the images to hide or show annotations.

OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
OpenSample annotation mask from Drone Dataset (UAV)Sample image from Drone Dataset (UAV)
👀
Have a look at 1359 images
View images along with annotations and tags, search and filter by various parameters

Class balance #

There are 1 annotation classes in the dataset. Find the general statistics and balances for every class in the table below. Click any row to preview images that have labels of the selected class. Sort by column to find the most rare or prevalent classes.

Search
Rows 1-1 of 1
Class
Images
Objects
Count on image
average
Area on image
average
drone
rectangle
1359
1486
1.09
37.75%

Images #

Explore every single image in the dataset with respect to the number of annotations of each class it has. Click a row to preview selected image. Sort by any column to find anomalies and edge cases. Use horizontal scroll if the table has many columns for a large number of classes in the dataset.

Object distribution #

Interactive heatmap chart for every class with object distribution shows how many images are in the dataset with a certain number of objects of a specific class. Users can click cell and see the list of all corresponding images.

Class sizes #

The table below gives various size properties of objects for every class. Click a row to see the image with annotations of the selected class. Sort columns to find classes with the smallest or largest objects or understand the size differences between classes.

Search
Rows 1-1 of 1
Class
Object count
Avg area
Max area
Min area
Min height
Min height
Max height
Max height
Avg height
Avg height
Min width
Min width
Max width
Max width
drone
rectangle
1486
34.57%
98.81%
0.02%
14px
1.94%
2364px
99.91%
312px
47.68%
15px
1.17%
4975px
100%

Spatial Heatmap #

The heatmaps below give the spatial distributions of all objects for every class. These visualizations provide insights into the most probable and rare object locations on the image. It helps analyze objects' placements in a dataset.

Spatial Heatmap

Objects #

Table contains all 1486 objects. Click a row to preview an image with annotations, and use search or pagination to navigate. Sort columns to find outliers in the dataset.

Search
Rows 1-10 of 1486
Object ID
Class
Image name
click row to open
Image size
height x width
Height
Height
Width
Width
Area
1
drone
rectangle
0219.jpg
2001 x 3101
1155px
57.72%
2041px
65.82%
37.99%
2
drone
rectangle
0004.jpg
1334 x 2000
643px
48.2%
1471px
73.55%
35.45%
3
drone
rectangle
0290.jpg
550 x 900
311px
56.55%
632px
70.22%
39.71%
4
drone
rectangle
0305.jpg
540 x 800
457px
84.63%
745px
93.12%
78.81%
5
drone
rectangle
foto05047.jpg.png
720 x 1280
291px
40.42%
550px
42.97%
17.37%
6
drone
rectangle
foto01306.jpg.png
720 x 1280
352px
48.89%
487px
38.05%
18.6%
7
drone
rectangle
0028.jpg
183 x 275
100px
54.64%
210px
76.36%
41.73%
8
drone
rectangle
0028.jpg
183 x 275
36px
19.67%
102px
37.09%
7.3%
9
drone
rectangle
0056.jpg
225 x 225
136px
60.44%
208px
92.44%
55.88%
10
drone
rectangle
0312.jpg
604 x 907
191px
31.62%
419px
46.2%
14.61%

License #

Drone Dataset (UAV) is under MIT license.

Source

Citation #

If you make use of the Drone Dataset (UAV) data, please cite the following reference:

@dataset{Drone Dataset (UAV),
  author={Mehdi Özel},
  title={Drone Dataset (UAV)},
  year={2019},
  url={https://www.kaggle.com/datasets/dasmehdixtr/drone-dataset-uav?select=drone_dataset_yolo}
}

Source

If you are happy with Dataset Ninja and use provided visualizations and tools in your work, please cite us:

@misc{ visualization-tools-for-drone-dataset-uav-dataset,
  title = { Visualization Tools for Drone Dataset (UAV) Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/drone-dataset-uav } },
  url = { https://datasetninja.com/drone-dataset-uav },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { jun },
  note = { visited on 2024-06-25 },
}

Download #

Dataset Drone Dataset (UAV) can be downloaded in Supervisely format:

As an alternative, it can be downloaded with dataset-tools package:

pip install --upgrade dataset-tools

… using following python code:

import dataset_tools as dtools

dtools.download(dataset='Drone Dataset (UAV)', dst_dir='~/dataset-ninja/')

Make sure not to overlook the python code example available on the Supervisely Developer Portal. It will give you a clear idea of how to effortlessly work with the downloaded dataset.

. . .

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