- 07 Apr 2025
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Project Types
- Updated on 07 Apr 2025
- 1 Minute to read
- Print
- DarkLight
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This article applies to these versions of LandingLens:
LandingLens | LandingLens on Snowflake |
✓ | ✓ (see exceptions below) |
LandingLens offers these project types:
- Object Detection
- Classification
- Segmentation
- Anomaly Detection
- Visual Prompting (not available in LandingLens on Snowflake)

Object Detection
Use to identify one or more objects in an image. Object Detection can be used to identify one or more objects within an image. Object Detection trains based on the labeled pixels (pixels inside the bounding box).
For more information, go to Object Detection.
Classification
Use to categorize (or "classify") the content of an image. Classification identifies the image as a whole. Classification trains based on all pixels in an image.
For more information, go to Classification.
Segmentation
Use to specify exact pixels to identify one or more regions within an image.
For more information, go to Segmentation.
Anomaly Detection
Use to identify deviations from the norm, especially when you have few or no images of "abnormal" cases.
For more information, go to Anomaly Detection.
Visual Prompting
Use to identify objects or areas in an image. You only need to label a few small areas for the model to detect the whole object or area.
For more information, go to Visual Prompting.
When to Use Each Project Type
Each Project Type is also designed for different use cases:
Project Type | When to Use | Examples |
---|---|---|
Object Detection |
| Identify multiple objects in an image.
|
Classification |
| Identify all content within an image.
|
Segmentation |
|
|
Anomaly Detection |
|
|
Visual Prompting |
| Identify objects with distinct textures.
|