for a general scenario. It uses a whole body image as an input and outputs an embedding vector to match a pair of images by the Cosine distance. The model is based on RMNet backbone that was developed for fast inference. A single reidentification head from the 1/16 scale feature map outputs the embedding vector of 256 floats. The model is provided without last calibration layer, but can be used in the same way as the original model (with insignificant drop in accuracy).</p>
<h2 id="example">Example</h2>
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