Windmill Detection on French Aerial Images

Introduction #

Marouane Zellou

The Windmill Detection on French Aerial Images Dataset was curated from 11 raster samples extracted from the latest French aerial images of 2021, each containing a minimum of 20 windmills per sample. These samples were cropped to a size of 2048*2048 pixels for training and validation purposes. During the selection of these areas, the authors delineated the regions of interest (ROI), defined as the union of the bounding boxes of the raster images. Initially, the raster images were in JPEG2000 format but were converted to JPEG to facilitate labeling using the YBAT tool. YBAT, an open-source labeling tool, was chosen due to its lack of size constraints and ease of installation, as it is built with pure HTML and JavaScript. Raster sampling was conducted using the sampling and generation functions of Odeon landcover, resulting in a training folder comprising the 11 raster samples divided into smaller patches. These patches were labeled and subsequently split into training and validation datasets.

The labelling is manually done with the YBAT tool. It helps producing the label files in YOLO V5 accepted format. The labelling was done following those principles :

Select the whole windmill in a box
If only a part of a windmill is visible, we also select it
The authors don’t select the shadow of the windmill

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Homepage

GitLab

Summary #

Windmill Detection on French Aerial Images Dataset is a dataset for an object detection task. Possible applications of the dataset could be in the energy industry.

The dataset consists of 1728 images with 217 labeled objects belonging to 1 single class (wind turbine).

Images in the Windmill Detection on French Aerial Images dataset have bounding box annotations. There are 1536 (89% of the total) unlabeled images (i.e. without annotations). There are 2 splits in the dataset: train (1384 images) and val (344 images). The dataset was released in 2022.

Explore #

Windmill Detection on French Aerial Images dataset has 1728 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.

Sample annotation mask from Windmill Detection on French Aerial Images

Sample image from Windmill Detection on French Aerial Images

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Have a look at 1728 images

Because of dataset's license preview is limited to 12 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.

Rows 1-1 of 1

Class ㅤ	Images ㅤ	Objects ㅤ	Count on image average	Area on image average
wind turbine➔ rectangle	192	217	1.13	1.57%

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.

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
wind turbine rectangle	217	1.39%	3.93%	0.09%	41px	2%	549px	26.81%	243px	11.88%	63px	3.08%	518px	25.29%

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.

Objects #

Table contains all 217 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.

Rows 1-10 of 217

Object ID ㅤ	Class ㅤ	Image name click row to open	Image size height x width	Height ㅤ	Height ㅤ	Width ㅤ	Width ㅤ	Area ㅤ
1➔	wind turbine rectangle	596877-9341_6994377-2150_1481.tif.tiff	2048 x 2048	291px	14.21%	250px	12.21%	1.73%
2➔	wind turbine rectangle	616461-3873_6962294-4809_681.tif.tiff	2048 x 2048	95px	4.64%	208px	10.16%	0.47%
3➔	wind turbine rectangle	616461-3873_6962294-4809_681.tif.tiff	2048 x 2048	183px	8.94%	403px	19.68%	1.76%
4➔	wind turbine rectangle	616461-3873_6960211-7468_592.tif.tiff	2048 x 2048	107px	5.22%	355px	17.33%	0.91%
5➔	wind turbine rectangle	616461-3873_6960211-7468_592.tif.tiff	2048 x 2048	200px	9.77%	422px	20.61%	2.01%
6➔	wind turbine rectangle	623127-5745_6963544-1213_354.tif.tiff	2048 x 2048	179px	8.74%	323px	15.77%	1.38%
7➔	wind turbine rectangle	623544-1213_6967711-0277_1020.tif.tiff	2048 x 2048	235px	11.47%	390px	19.04%	2.19%
8➔	wind turbine rectangle	682294-4809_6972711-0277_1265.tif.tiff	2048 x 2048	354px	17.29%	130px	6.35%	1.1%
9➔	wind turbine rectangle	666877-9341_6999377-2150_742.tif.tiff	2048 x 2048	386px	18.85%	81px	3.96%	0.75%
10➔	wind turbine rectangle	636044-8404_6995628-2936_911.tif.tiff	2048 x 2048	219px	10.69%	292px	14.26%	1.52%

License #

License is unknown for the Windmill Detection on French Aerial Images Dataset dataset.

Source

Citation #

If you make use of the Windmill detection on french aerial data, please cite the following reference:

@dataset{Windmill detection on french aerial,
  author={Marouane Zellou},
  title={Windmill Detection on French Aerial Images Dataset},
  year={2022},
  url={https://www.kaggle.com/datasets/mzellou/windmill-detection-on-french-aerial-images}
}

Source

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

@misc{ visualization-tools-for-windmill-detection-french-dataset,
  title = { Visualization Tools for Windmill Detection on French Aerial Images Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/windmill-detection-french } },
  url = { https://datasetninja.com/windmill-detection-french },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { nov },
  note = { visited on 2024-11-21 },
}

Download #

Please visit dataset homepage to download the data.

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