Model ID: 68a51a726f7033bbfcf57c905f09b7ca
Model Name: general
Model Type ID: visual-segmenter
The General Visual Segmenter recognizes over 180 common concepts.
The General Visual Segmenter returns the pixels containing a given object, as well as the predicted concept that is represented by this object.
Gather valuable business insights from images, text and data using machine learning, natural language processing and computer vision.
Assign tags or categories to analyze text based on content. Build models for topic analysis, sentiment analysis, smart reply and more.
Identify unwanted content such as gore, drugs, explicit nudity or suggestive nudity.
Analyze images and return probability scores on the likelihood that the media contains the face(s) of over 10,000 recognized celebrities.
Analyze images and returns numerical vectors that represent each detected face in the image in a 1024-dimensional space.
Recognize textures and patterns in a two-dimensional image e.g., feathers, woodgrain, petrified wood, glacial ice and overarching descriptive concepts (veined, metallic).
Identify different levels of nudity in your visual data. Ideal for moderating and filtering offensive content from your platform.
Explore our pre-built, ready-to-use image recognition models to suit your specific needs.
The Room Type Model is an "embedding-classifier" which means that you will need to insert the model into a workflow and feed it embeddings from an embedding model for it to work. We recommend that you start with the embeddings from our general model.
Learn more about making Mesh Workflow predictions in our API Guide.