---
title: Semantic Segmentation with Polygons for Wildlife Conservation
type: templates
hide_menu: true
category: Computer Vision
cat: computer-vision
order: 1103

meta_description: Template for using Label Studio to perform semantic segmentation with polygons.

In wildlife conservation, Semantic Segmentation with Polygons labeled data is critical for accurately identifying and classifying species in diverse environments, enabling AI models to perform tasks such as habitat analysis, population monitoring, and threat detection. High-quality labeled datasets empower these models to discern intricate patterns within complex ecosystems, driving effective conservation strategies.

However, the process of labeling wildlife images can be fraught with challenges, including time-intensive efforts, inconsistent annotation quality due to varied expertise, and the necessity for integrative reviews by domain specialists. Label Studio addresses these hurdles through its AI-assisted pre-labeling capabilities, significantly reducing the time needed to initiate the labeling process. With expert validation, each pre-labeled dataset is meticulously reviewed, ensuring accuracy and consistency. Additionally, our collaboration tools allow teams to work together seamlessly, while customizable templates streamline the labeling workflow specific to wildlife conservation needs. Together, these features result in improved model performance, enhanced operational efficiency, and the scalability required to tackle large datasets crucial for preserving our planet's biodiversity.

Open in Label Studio

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="0.5">
    <Label value="Elephant" background="green"/>
    <Label value="Lion" background="orange"/>
    <Label value="Rhinoceros" background="gray"/>
    <Label value="Zebra" background="blue"/>
    <Label value="Giraffe" background="yellow"/>
  </PolygonLabels>
</View>

This configuration allows annotators to select a label relevant to wildlife conservation and mark areas of the image by drawing polygons around animals or features. The interface includes an image viewer with zoom enabled for detailed identification, along with polygon tools styled to improve visibility and usability.

All labeling configurations must be wrapped in View tags.

You can add a header to provide instructions to the annotator:

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

Use the Image object tag to specify the image data and allow annotators to zoom the image:

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

Use the PolygonLabels control tag to allow annotators to create polygons for specific labels.

<PolygonLabels name="label" toName="image"
               strokeWidth="3" pointSize="small"
               opacity="0.9">
  <Label value="Elephant" background="green"/>
  <Label value="Lion" background="orange"/>
  <Label value="Rhinoceros" background="gray"/>
  <Label value="Zebra" background="black"/>
  <Label value="Giraffe" background="yellow"/>
</PolygonLabels>

Annotators can control the opacity of the polygons using the opacity argument, and the styling of the polygon tool using the pointSize and strokeWidth arguments. Use the background argument with the Label control tag to control the color of each polygon.