Visual Layer Documentation: Visual Intelligence, At Scale

Available Enrichment Models

Visual Layer provides a range of built-in models designed for diverse enrichment tasks:

Model Name	Task Type	Description
VL-Object-Detector	Object Detection	Identifies and localizes objects within images or videos by drawing bounding boxes and classifying each detected object.
VL-Image-Tagger	Image Classification	Assigns labels or tags to an entire image, categorizing its content for identification and analysis.
VL-Face-Detector	Face Detection	Detects faces and extracts facial landmarks for accurate face alignment and recognition workflows.
VL-Image-Captioner	Image to Text	Generates descriptive text that summarizes the content and context of the entire image input.
VL Advanced Captioner	Image to Text	A state-of-the-art Vision-Language model that generates detailed captions and answers questions about image content (VQA).
VL-Object-Captioner	Object to Text	Generates descriptive text that summarizes detected objects and their interactions in the image.
NVILA-Lite-2B	Image to Text	A family of open VLMs designed to optimize both efficiency and accuracy for video understanding and multi-image tasks.
VL-Image-Semantic-Search	Semantic Image Search	Enhances image search with conceptual queries, identifying content that matches search intent and improving discovery by understanding visual context.
Advanced-Object-Search	Semantic Object Search	Finds objects in images or videos based on meaning and context, beyond simple tags. Quickly retrieves relevant objects using natural language queries.
Radiology-Image-Search	Semantic Image Search	Enhances image search with radiology understanding, improving discovery by understanding radiology images and terms.

Some models require pre-existing enrichments before they can be applied. These dependencies include:

VL-Object-Captioner requires Object Detection to be applied first.
Semantic Search models require captions or embeddings from a prior enrichment step.

Labels may come from user annotations, the VL-Object-Detector, or the VL-Image-Tagger.

Coming Soon

These models are in development and will be available in the enrichment catalog:

Model Name	Task Type	Description
Nv-grounding dino	Object Detection	An open vocabulary zero-shot object detection model with natural language prompts.
Advanced-Image-Search	Semantic Image Search	Enhanced conceptual image retrieval using complex queries, identifying content that matches search intent.
yolov9	Object Detection	Object detection model for fast and accurate bounding box predictions.

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Available Enrichment Models

Coming Soon

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​Available Enrichment Models

​Coming Soon

​Want Early Access?

Get in Touch

Available Enrichment Models

Coming Soon

Want Early Access?