Classify sample

Classify a complete file against the current impulse. This will move the sliding window (dependent on
the sliding window length and the sliding window increase parameters in the impulse) over the complete
file, and classify for every window that is extracted. Depending on the size of your file, whether your
sample is resampled, and whether the result is cached you'll get either the result or a job back. If
you receive a job, then wait for the completion of the job, and then call this function again to receive
the results. The unoptimized (float32) model is used by default, and classification with an optimized
(int8) model can be slower.

Click Try It! to start a request and see the response here!