Model ID: 31025e019a18970a1acc55ba6a184dc6
Model Name: face-sentiment
Model Type ID: visual-classifier
The Face Sentiment Model returns the predicted sentiment concept along with a confidence score.
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.