The vector representation is computed by using Clarifai’s ‘General’ model. The vectors of visually similar images will be close to each other in the 1024-dimensional space. The ‘General Embedding’ model can be used for filtering, indexing, ranking, and organizing images according to visual similarity.
The Predict API returns ‘vector’ and ‘num_dimensions’. The ‘vector’ is a numerical vector that represents the input image in a 1024-dimensional space. The numerical values within the vectors are between 0 and 1, inclusive. The vectors of visually similar images will be close to each other in the 1024-dimensional space. The ‘num_dimensions’ for this model is set at 1024.
Detect toxic, obscene, racist, or threatening language, or your own custom moderation models.
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.