rename new model to google_perch_lite

3dc55b1 over 2 years ago

2.24 kB

import numpy as np
import iSparrow.preprocessor_base as ppb


class Preprocessor(ppb.PreprocessorBase):

    def __init__(
        self,
        sample_rate: int = 32000,
        sample_secs: float = 5.0,
        resample_type: str = "kaiser_fast",
        **kwargs
    ):

        super().__init__(
            "google_perch_lite",
            sample_rate=sample_rate,
            sample_secs=sample_secs,
            resample_type=resample_type,
            **kwargs
        )

    def process_audio_data(self, rawdata: np.array) -> np.array:

        # raise when sampling rate is unequal.
        if self.actual_sampling_rate != self.sample_rate:
            raise RuntimeError(
                "Sampling rate is not the desired one. Desired sampling rate: {self.sample_rate}, actual sampling rate: {self.actual_sampling_rate}"
            )

        seconds = self.sample_secs
        minlen = 1.5

        self.chunks = []

        for i in range(
            0, len(rawdata), int((seconds - self.overlap) * self.sample_rate)
        ):

            split = rawdata[i : (i + int(seconds * self.actual_sampling_rate))]

            # End of signal?
            if len(split) < int(minlen * self.actual_sampling_rate):
                break

            # Signal chunk too short? Fill with zeros.
            if len(split) < int(self.actual_sampling_rate * seconds):
                temp = np.zeros((int(self.actual_sampling_rate * seconds)))
                temp[: len(split)] = split
                split = temp

            self.chunks.append(split)

        print(
            "process audio data google: complete, read ",
            str(len(self.chunks)),
            "chunks.",
            flush=True,
        )

        return self.chunks

    @classmethod
    def from_cfg(cls, cfg: dict):

        # make sure there are no more than the allowed keyword arguments in the cfg
        allowed = [
            "sample_rate",
            "sample_secs",
            "resample_type",
            "duration",
            "actual_sampling_rate",
        ]

        if len([key for key in cfg if key not in allowed]) > 0:
            raise RuntimeError("Erroneous keyword arguments in preprocessor config")

        return cls(**cfg)

	import numpy as np
	import iSparrow.preprocessor_base as ppb


	class Preprocessor(ppb.PreprocessorBase):

	def __init__(
	self,
	sample_rate: int = 32000,
	sample_secs: float = 5.0,
	resample_type: str = "kaiser_fast",
	**kwargs
	):

	super().__init__(
	"google_perch_lite",
	sample_rate=sample_rate,
	sample_secs=sample_secs,
	resample_type=resample_type,
	**kwargs
	)

	def process_audio_data(self, rawdata: np.array) -> np.array:

	# raise when sampling rate is unequal.
	if self.actual_sampling_rate != self.sample_rate:
	raise RuntimeError(
	"Sampling rate is not the desired one. Desired sampling rate: {self.sample_rate}, actual sampling rate: {self.actual_sampling_rate}"
	)

	seconds = self.sample_secs
	minlen = 1.5

	self.chunks = []

	for i in range(
	0, len(rawdata), int((seconds - self.overlap) * self.sample_rate)
	):

	split = rawdata[i : (i + int(seconds * self.actual_sampling_rate))]

	# End of signal?
	if len(split) < int(minlen * self.actual_sampling_rate):
	break

	# Signal chunk too short? Fill with zeros.
	if len(split) < int(self.actual_sampling_rate * seconds):
	temp = np.zeros((int(self.actual_sampling_rate * seconds)))
	temp[: len(split)] = split
	split = temp

	self.chunks.append(split)

	print(
	"process audio data google: complete, read ",
	str(len(self.chunks)),
	"chunks.",
	flush=True,
	)

	return self.chunks

	@classmethod
	def from_cfg(cls, cfg: dict):

	# make sure there are no more than the allowed keyword arguments in the cfg
	allowed = [
	"sample_rate",
	"sample_secs",
	"resample_type",
	"duration",
	"actual_sampling_rate",
	]

	if len([key for key in cfg if key not in allowed]) > 0:
	raise RuntimeError("Erroneous keyword arguments in preprocessor config")

	return cls(**cfg)