Dataset Open Access

Embrapa Wine Grape Instance Segmentation Dataset – Embrapa WGISD

Thiago Santos; de Souza, Leonardo; dos Santos Andreza; Avila, Sandra


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        <foaf:name>Avila, Sandra</foaf:name>
        <foaf:givenName>Sandra</foaf:givenName>
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    <dcat:keyword>instance segmentation</dcat:keyword>
    <dcat:keyword>object detection</dcat:keyword>
    <dcat:keyword>viticulture</dcat:keyword>
    <dcat:keyword>agriculture</dcat:keyword>
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    <dct:description>&lt;p&gt;&lt;strong&gt;Embrapa Wine Grape Instance Segmentation Dataset &amp;ndash; Embrapa WGISD&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;For a detailed description of this dataset, following the &lt;em&gt;datasheet for the datasets&lt;/em&gt; recommendation proposed by &lt;a href="https://arxiv.org/abs/1803.09010"&gt;Gebru et al.&lt;/a&gt;, check the &lt;strong&gt;README.md&lt;/strong&gt; file.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Motivation for Dataset Creation&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;&lt;em&gt;Why was the dataset created?&lt;/em&gt;&lt;/p&gt; &lt;p&gt;Embrapa WGISD (&lt;em&gt;Wine Grape Instance Segmentation Dataset&lt;/em&gt;) was created to provide images and annotation to study &lt;em&gt;object detection and instance segmentation&lt;/em&gt; for image-based monitoring and field robotics in viticulture. It provides instances from five different grape varieties taken on field. These instances shows variance in grape pose,&lt;br&gt; illumination and focus, including genetic and phenological variations such as shape, color and compactness.&lt;/p&gt; &lt;p&gt;&lt;em&gt;What (other) tasks could the dataset be used for?&lt;/em&gt;&lt;/p&gt; &lt;p&gt;Possible uses include relaxations of the instance segmentation problem: classification (Is a grape in the image?), semantic segmentation (What are the &amp;quot;grape pixels&amp;quot; in the image?), and object detection (Where are the grapes in the image?). The WGISD can also be used in grape variety identification.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;</dct:description>
    <dct:description>The building of the WGISD dataset was supported by the Embrapa SEG Project 01.14.09.001.05.04, Image-based metrology for Precision Agriculture and Phenotyping, and the CNPq PIBIC Program (grants 161165/2017-6 and 125044/2018-6).</dct:description>
    <dct:description>{"references": ["Santos, T.T., Souza, L.L., Santos, A.M., &amp; Avila, S.E. (2019). Grape detection, segmentation and tracking using deep neural networks and three-dimensional association. ArXiv, abs/1907.11819."]}</dct:description>
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