.
Both
and
are commonly used in computer vision projects. Below, we compare and contrast
and
A very fast and easy to use PyTorch model that achieves state of the art (or near state of the art) results.
How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion MatrixThis architecture provides good realtime results on limited compute. It's designed to run in realtime (30 frames per second) even on mobile devices.
How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix
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