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Sheep Detection Dataset

20311
Taglivestock
Taskobject detection
Release YearMade in 2020
LicenseCC0 1.0
Download41 MB

Summary #

Dataset LinkHomepage

Sheep Detection is a dataset for an object detection task. Possible applications of the dataset could be in the livestock industry.

The dataset consists of 203 images with 331 labeled objects belonging to 1 single class (sheep).

Images in the Sheep Detection dataset have bounding box annotations. All images are labeled (i.e. with annotations). There are no pre-defined train/val/test splits in the dataset. The dataset was released in 2020.

Dataset Poster

Explore #

Sheep Detection dataset has 203 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 Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
OpenSample annotation mask from Sheep DetectionSample image from Sheep Detection
👀
Have a look at 203 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
sheep
rectangle
203
331
1.63
51.47%

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
sheep
rectangle
331
32.74%
96.25%
0.54%
14px
6.67%
444px
100%
171px
64.9%
22px
5.5%
499px
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 331 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 331
Object ID
Class
Image name
click row to open
Image size
height x width
Height
Height
Width
Width
Area
1
sheep
rectangle
sheep0.png
195 x 259
138px
70.77%
159px
61.39%
43.45%
2
sheep
rectangle
sheep112.png
342 x 400
258px
75.44%
326px
81.5%
61.48%
3
sheep
rectangle
sheep189.png
225 x 300
102px
45.33%
68px
22.67%
10.28%
4
sheep
rectangle
sheep189.png
225 x 300
83px
36.89%
128px
42.67%
15.74%
5
sheep
rectangle
sheep189.png
225 x 300
19px
8.44%
28px
9.33%
0.79%
6
sheep
rectangle
sheep50.png
315 x 400
222px
70.48%
241px
60.25%
42.46%
7
sheep
rectangle
sheep10.png
209 x 241
152px
72.73%
183px
75.93%
55.22%
8
sheep
rectangle
sheep60.png
267 x 400
102px
38.2%
109px
27.25%
10.41%
9
sheep
rectangle
sheep60.png
267 x 400
112px
41.95%
139px
34.75%
14.58%
10
sheep
rectangle
sheep159.png
177 x 284
144px
81.36%
128px
45.07%
36.67%

License #

Sheep Detection is under CC0 1.0 license.

Source

Citation #

If you make use of the Sheep Detection data, please cite the following reference:

@misc{make ml,
    title={Sheeps Dataset},
    url={https://makeml.app/datasets/sheep},
    journal={Make ML}
}

Source

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

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

Download #

Dataset Sheep Detection 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='Sheep Detection', 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.

The data in original format can be downloaded here.

. . .

Disclaimer #

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