Dataset Open Access

Pollen Video Library for Benchmarking Detection, Classification, Tracking and Novelty Detection Tasks

Nam Cao; Matthias Meyer; Lothar Thiele; Olga Saukh


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    <subfield code="u">Institute of Technical Informatics, Graz University of Technology, Austria</subfield>
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    <subfield code="a">Nam Cao</subfield>
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    <subfield code="a">&lt;p&gt;&lt;strong&gt;Dataset description&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;This dataset contains microscopic images and videos of pollen gathered between Feb. and Aug. 2020 in Graz, Austria.&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;
	&lt;p&gt;Pollen images of 16 types:&amp;nbsp;&lt;code&gt;...images_16_types.zip&lt;/code&gt;&lt;/p&gt;

	&lt;ul&gt;
		&lt;li&gt;Acer Pseudoplatanus&lt;/li&gt;
		&lt;li&gt;Aesculus Carnea&lt;/li&gt;
		&lt;li&gt;Alnus&lt;/li&gt;
		&lt;li&gt;Anthoxanthum&lt;/li&gt;
		&lt;li&gt;Betula Pendula&lt;/li&gt;
		&lt;li&gt;Brassica&lt;/li&gt;
		&lt;li&gt;Carpinus&lt;/li&gt;
		&lt;li&gt;Corylus&lt;/li&gt;
		&lt;li&gt;Dactylis Glomerata&lt;/li&gt;
		&lt;li&gt;Fraxinus&lt;/li&gt;
		&lt;li&gt;Pinus Nigra&lt;/li&gt;
		&lt;li&gt;Platanus&lt;/li&gt;
		&lt;li&gt;Populus Nigra&lt;/li&gt;
		&lt;li&gt;Prunus Avium&lt;/li&gt;
		&lt;li&gt;Sequoiadendron Giganteum&lt;/li&gt;
		&lt;li&gt;Taxus Baccata&lt;/li&gt;
	&lt;/ul&gt;
	&lt;/li&gt;
	&lt;li&gt;
	&lt;p&gt;Pollen video library&amp;nbsp;&lt;code&gt;...pollen_video_library.zip&lt;/code&gt;&lt;/p&gt;

	&lt;ul&gt;
		&lt;li&gt;Each type of pollen is in a separate folder, there may be multiple videos per type.&lt;/li&gt;
		&lt;li&gt;In each pollen folder, we included images cropped from the videos by YOLO object detection algorithm trained on a subset of pollen images as described in [1].&lt;/li&gt;
		&lt;li&gt;Cropped file name structure&amp;nbsp;&lt;code&gt;[Video file name]_[TrackingID]_[Image index of a grain]_[Frame index in video]&lt;/code&gt;
		&lt;ul&gt;
			&lt;li&gt;Example, if a grain has 5 images, the file name would be:
			&lt;pre&gt;&lt;code&gt; Anthoxanthum-grass-20200530-122652_0000000_001_00001.jpg
 Anthoxanthum-grass-20200530-122652_0000000_002_00002.jpg
 ...
 Anthoxanthum-grass-20200530-122652_0000000_005_00005.jpg
&lt;/code&gt;&lt;/pre&gt;
			&lt;/li&gt;
		&lt;/ul&gt;
		&lt;/li&gt;
	&lt;/ul&gt;
	&lt;/li&gt;
	&lt;li&gt;
	&lt;p&gt;Field data over 3 days are gathered in Graz in spring 2020.&amp;nbsp;&lt;code&gt;...pollen_field_data.zip&lt;/code&gt;&lt;/p&gt;
	&lt;/li&gt;
	&lt;li&gt;
	&lt;p&gt;Sample code to load the data and visualize the images is in&amp;nbsp;&lt;code&gt;...plot_pollen_sample.py&lt;/code&gt;. Download and extract the file&amp;nbsp;&lt;code&gt;...images_16_types.zip&lt;/code&gt;&amp;nbsp;in the same folder as&amp;nbsp;&lt;code&gt;...plot_pollen_sample.py&lt;/code&gt;&amp;nbsp;to run the example.&lt;/p&gt;
	&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;strong&gt;Dependecies:&lt;/strong&gt;&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;opencv&lt;/li&gt;
	&lt;li&gt;numpy&lt;/li&gt;
	&lt;li&gt;matplotlib&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;&lt;strong&gt;Credit&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;[1] N. Cao, M. Meyer, L. Thiele, and O. Saukh. 2020. Automated Pollen Detection with an Affordable Technology. In Proceedings of the International Conference on Embedded Wireless Systems and Networks (EWSN). 108&amp;ndash;119.&lt;/p&gt;

&lt;pre&gt;&lt;code&gt;@inproceedings{namcao2020pollen,
  title = {Automated Pollen Detection with an Affordable Technology},
  author = {Nam Cao and Matthias Meyer and Lothar Thiele and Olga Saukh},
  booktitle = {Proceedings of the International Conference on Embedded Wireless Systems and Networks (EWSN)},
  pages={108–119}
  month = {2},	
  year = {2020},
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