• AI Face Recognition Model

    Analyze images and returns numerical vectors that represent each detected face in the image in a 1024-dimensional space. Use to organize, filter and rank images according to visual similarity.

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  • Model Information

    Model ID: 240a8f047a6ef4328331b5c6fb3952ca

    Model Name: people-vehicle-detector-v1 Model

    Type ID: visual-detector

    Owner: Clarifai

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    5,000 free operations per month.

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    You can call the Predict API with the 'Face Embedding' model. Simply pass in an image input with a publicly accessible URL or by directly sending image bytes.

    Learn more about the Predict API.
    API Guide

  • Response

    The Predict API returns an array of regions. Each region element has bounding box coordinates for each face detected as well as a data object containing a ‘vector’ and ‘num_dimensions’.

    The returned ‘bounding_box’ values are the coordinates of the box outlining each face within the image. They are specified as float values between 0 and 1, relative to the image size; the top-left coordinate of the image is (0.0, 0.0), and the bottom-right of the image is (1.0, 1.0). If the original image size is (500 width, 333 height), then the box above corresponds to the box with top-left corner at (208 x, 83 y) and bottom-right corner at (175 x, 139 y). Note that if the image is rescaled (by the same amount in x and y), then box coordinates remain the same. To convert back to pixel values, multiply by the image size, width (for “left_col” and “right_col”) and height (for “top_row” and “bottom_row”).

    The ‘vector’ is a numerical vector that represents the face detected in a 1024-dimensional space. The numerical values within the vectors are between 0 and 1, inclusive. The vectors of visually similar faces will be close to each other in the 1024-dimensional space. The ‘num_dimensions’ for this model is set at 1024.

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