Semantic Segmentation with Polygons for Sports Analytics

In sports analytics, Semantic Segmentation with Polygons labeled data is crucial for enabling AI models to accurately analyze player movements, recognize formations, and provide real-time insights during games. This level of precision aids in tasks such as tactical analysis, injury prediction, and performance optimization, which are essential for teams aiming to stay competitive.

However, labeling this complex data presents significant challenges, including time-intensive manual efforts, inconsistencies in label quality due to varying annotator skill levels, and the necessity of domain expertise to achieve reliable results. Label Studio effectively addresses these issues through its advanced AI-assisted pre-labeling capabilities, which expedite the initial labeling process and reduce the workload on human annotators. Our platform also facilitates expert validation to ensure high-quality output and offers collaborative tools that enhance communication and feedback among team members. With customizable templates tailored to sports analytics, Label Studio not only streamlines the labeling workflow but also provides measurable benefits such as improved model performance, reduced labeling times, heightened expert efficiency, and scalable operations that adapt to the shifting demands of the sports industry.

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Labeling configuration

<View>
  <Header value="Select label and click the image to start"/>
  <Image name="image" value="$image" zoom="true"/>
  <PolygonLabels name="label" toName="image"
                 strokeWidth="3" pointSize="small"
                 opacity="0.9">
    <Label value="Player" background="red"/>
    <Label value="Referee" background="blue"/>
    <Label value="Coach" background="green"/>
    <Label value="Ball" background="orange"/>
    <Label value="Goalpost" background="purple"/>
  </PolygonLabels>
</View>

This configuration enables annotators to select a label and then click on the sports image to begin annotating. The template uses polygons to outline regions related to sports individuals and objects such as players, referees, and equipment on the field.

All labeling configurations must be enclosed within <a href="https://labelstud.io/tags/view">View</a> tags.

You can add a <a href="https://labelstud.io/tags/header">header</a> to provide instructions to the annotator:

<Header value="Select label and click the image to start"/>

Use the <a href="https://labelstud.io/tags/image">Image</a> object tag to specify the sports image data and allow annotators to zoom the image:

<Image name="image" value="$image" zoom="true"/>

Use the <a href="https://labelstud.io/tags/polygonlabels">PolygonLabels</a> control tag to allow annotators to create polygons for specific sports-related labels.

<PolygonLabels name="label" toName="image"
               strokeWidth="3" pointSize="small"
               opacity="0.9">
  <Label value="Player" background="red"/>
  <Label value="Referee" background="blue"/>
  <Label value="Coach" background="green"/>
  <Label value="Ball" background="orange"/>
  <Label value="Goalpost" background="purple"/>
</PolygonLabels>

Annotators can adjust the opacity of the polygons using the opacity argument, and style the polygon tool using the pointSize and strokeWidth arguments. Use the background argument with the <a href="https://labelstud.io/tags/label">Label</a> control tag to set the color for each polygon corresponding to different sports elements.