DOI: 10.7910/dvn/95hyki
title: Cauliflower centre detection and 3-dimensional tracking for robotic intrarow weeding

description: &lt;h1&gt;Cauliflower Center Dataset&lt;/h1&gt;
&lt;p&gt;The dataset is used for autonomous intrarow weeding as described in the paper of Willekens et al. (2025).&lt;/p&gt;

&lt;blockquote&gt;
Willekens, A., Callens, B., Pieters, J., Wyffels, F., & Cool, S. (2025).&lt;br&gt;
&lt;i&gt;Cauliflower centre detection and 3-dimensional tracking for robotic intrarow weeding. Precision Agriculture. Springer.
&lt;/blockquote&gt;

&lt;h2&gt;Center&lt;/h2&gt;
&lt;p&gt;The cauliflower centers in the images (PNG files) are provided in JSON files with the same name as the corresponding image. Each JSON file follows this structure:&lt;/p&gt;

&lt;pre&gt;&lt;code class="json"&gt;
{
 "centers": [
 [
 &lt;x pixel 1&gt;,
 &lt;y pixel 1&gt;
 ],
 [
 &lt;x pixel 2&gt;,
 &lt;y pixel 2&gt;
 ],
 ...
 ]
}
&lt;/code&gt;&lt;/pre&gt;

 &lt;p&gt;The &lt;code&gt;.pkl&lt;/code&gt; files contain the same information as the JSON files but in a binary format.&lt;/p&gt;

 &lt;h2&gt;Segmentation&lt;/h2&gt;
 &lt;p&gt;Many of the images are also segmented. The segmentation masks are stored in files with the &lt;code&gt;.sam.png&lt;/code&gt; extension.&lt;/p&gt;

&lt;h2&gt;Dataset Overview&lt;/h2&gt;
&lt;p&gt;The dataset file &lt;code&gt;db_dump.sql&lt;/code&gt; provides the content of a PostgreSQL database that was used in the study of Willekens et al. (2025). When recovering this dataset, the PostGIS extension must be installed.&lt;/p&gt;

&lt;ol&gt;
 &lt;li&gt;Create a database in PostgreSQL &lt;code&gt;CREATE DATABASE cauliflower_db;&lt;/code&gt;&lt;/li&gt;
 &lt;li&gt;Connect to the new database and install the PostGIS plugin &lt;code&gt;CREATE EXTENSION postgis;&lt;/code&gt;. See the
&lt;a href="https://postgis.net/documentation/getting_started/"&gt;PostGIS installation instructions&lt;/a&gt; if PostGIS is not yet installed.&lt;/li&gt;
 &lt;li&gt;Recover the database &lt;code&gt;psql -U your_username -d cauliflower_db -f db_dump.sql&lt;/code&gt;&lt;/li&gt;
&lt;/ol&gt;

&lt;p&gt;The tables contain the following information.&lt;/p&gt;

&lt;ul&gt;
 &lt;li&gt;
 &lt;strong&gt;dataset&lt;/strong&gt;&lt;br&gt;
 The datasets correspond to the different folders (e.g., &lt;code&gt;20230809.zip&lt;/code&gt;, &lt;code&gt;20230810.zip&lt;/code&gt;, &lt;code&gt;20230811.zip&lt;/code&gt;), with the folder name representing the date of data collection (&lt;code&gt;YYYYMMDD&lt;/code&gt;).
 &lt;/li&gt;
 &lt;li&gt;
 &lt;strong&gt;calibration&lt;/strong&gt;&lt;br&gt;
 Refers to the calibration files stored in &lt;code&gt;calib.zip&lt;/code&gt;.
 &lt;/li&gt;
 &lt;li&gt;
 &lt;strong&gt;image&lt;/strong&gt;&lt;br&gt;
 Holds metadata for individual images, such as geometry, time, and the associated dataset.
 &lt;/li&gt;
 &lt;li&gt;
 &lt;strong&gt;label&lt;/strong&gt;&lt;br&gt;
 Stores the references of the labels for each image.
 &lt;/li&gt;
 &lt;li&gt;
 &lt;strong&gt;label_set&lt;/strong&gt;&lt;br&gt;
 Bundles different labels into one &lt;code&gt;label_set&lt;/code&gt; used for training, validation, or testing.
 &lt;/li&gt;
 &lt;li&gt;
 &lt;strong&gt;label_set_entry&lt;/strong&gt;&lt;br&gt;
 Serves as a junction table associating labels with label sets.
 &lt;/li&gt;
 &lt;li&gt;
 &lt;strong&gt;sensor&lt;/strong&gt;&lt;br&gt;
 Lists the sensors used during data collection.
 &lt;/li&gt;
 &lt;li&gt;
 &lt;strong&gt;training&lt;/strong&gt;&lt;br&gt;
 Describes the training sessions that were initiated. It refers to a validation and training &lt;code&gt;label_set&lt;/code&gt; and specifies the training hyperparameters.
 &lt;/li&gt;
&lt;/ul&gt;