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Computer Vision
- Semantic Segmentation with Polygons
- Semantic Segmentation with Masks
- Object Detection with Bounding Boxes
- Keypoint Labeling
- Image Captioning
- Optical Character Recognition
- Image Classification
- Visual Question Answering
- Object Detection with Ellipses
- Multi-Image Classification
Natural Language Processing
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Audio/Speech Processing
- Automatic Speech Recognition
- Sound Event Detection
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- Intent Classification
- Audio Classification
- Audio Classification with Segments
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Conversational AI
- Response Generation
- Response Selection
- Coreference Resolution and Entity Linking
- Slot Filling and Intent Classification
Ranking and Scoring
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- Document Retrieval
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Structured Data Parsing
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- HTML Entity Recognition
- HTML Classification
Time Series Analysis
- Time Series Forecasting
- Change Point Detection
- Activity Recognition
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- Outliers and Anomaly Detection
- Time Series Classification
- Time Series Labeling
Videos
- Video Classification
- Video Timeline Segmentation
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- Template Gallery - Computer Vision
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- Template Gallery - Conversational AI
- Template Gallery - Ranking & Scoring
- Template Gallery - Structured Data Parsing
- Template Gallery - Time Series Analysis
- Template Gallery - Videos
Object Detection with Bounding Boxes

If you want to perform object detection, you need to create a labeled dataset. Use this template to add rectangular bounding boxes to images, and label the contents of the bounding boxes.
Interactive Template Preview
Labeling Configuration
<View>
<Image name="image" value="$image"/>
<RectangleLabels name="label" toName="image">
<Label value="Airplane" background="green"/>
<Label value="Car" background="blue"/>
</RectangleLabels>
</View>
About the labeling configuration
All labeling configurations must be wrapped in View tags.
Use the Image object tag to specify the image to label:
<Image name="image" value="$image"/>
Use the RectangleLabels control tag to add labels and rectangular bounding boxes to your image at the same time. Use the Label tag to control the color of the boxes:
<RectangleLabels name="label" toName="image">
<Label value="Airplane" background="green"/>
<Label value="Car" background="blue"/>
</RectangleLabels>
Enhance this template
Add descriptions to detected objects
If you want to add further context to object detection tasks with bounding boxes, you can add some per-region conditional labeling parameters to your labeling configuration.
For example, to prompt annotators to add descriptions to detected objects, you can add the following to your labeling configuration:
<View visibleWhen="region-selected">
<Header value="Describe object" />
<TextArea name="answer" toName="image" editable="true"
perRegion="true" required="true" />
<Choices name="choices" toName="image"
perRegion="true">
<Choice value="Correct"/>
<Choice value="Broken"/>
</Choices>
</View>
The visibleWhen
parameter of the View tag hides the description prompt from annotators until a bounding box is selected.
After the annotator selects a bounding box, the Header appears and provides instructions to annotators.
The TextArea control tag displays an editable text box that applies to the selected bounding box, specified with the perRegion="true"
parameter. You can also add a placeholder
parameter to provide suggested text to annotators.
In addition, you can prompt annotators to provide additional feedback about the content of the bounding box, such as the status of the item in the box, using the Choices tag with the perRegion
parameter.
Related tags

If you found an error, you can file an issue on GitHub!