Datasets:
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| #!/usr/bin/python3 | |
| # -*- coding: utf-8 -*- | |
| import argparse | |
| from pathlib import Path | |
| import cv2 as cv | |
| from glob import glob | |
| import pandas as pd | |
| import numpy as np | |
| from scipy.io import wavfile | |
| from tqdm import tqdm | |
| from project_settings import project_path | |
| from toolbox.python_speech_features.misc import wave2spectrum_image | |
| def get_args(): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument( | |
| "--template_dir", | |
| default=(project_path / "data/early_media/62/templates/").as_posix(), | |
| type=str | |
| ) | |
| parser.add_argument( | |
| "--wav_dir", | |
| default=(project_path / "data/early_media/62/wav/").as_posix(), | |
| type=str | |
| ) | |
| args = parser.parse_args() | |
| return args | |
| def main(): | |
| args = get_args() | |
| template_dir = Path(args.template_dir) | |
| wav_dir = Path(args.wav_dir) | |
| max_wave_value = 32768.0 | |
| result = list() | |
| for template_file in template_dir.glob("*/*.wav"): | |
| template_label = template_file.parts[-2] | |
| _, template = wavfile.read(template_file) | |
| template = template / max_wave_value | |
| template = wave2spectrum_image( | |
| wave=template, | |
| sample_rate=8000, | |
| # n_low_freq=100 | |
| ) | |
| template = template.T | |
| for wav_file in tqdm(wav_dir.glob("*/*.wav")): | |
| wav_label = wav_file.parts[-2] | |
| _, signal = wavfile.read(wav_file) | |
| signal = signal[:12 * 8000] | |
| signal = signal / max_wave_value | |
| spectrum = wave2spectrum_image( | |
| wave=signal, | |
| sample_rate=8000, | |
| # n_low_freq=100 | |
| ) | |
| spectrum = spectrum.T | |
| sqdiff_normed = cv.matchTemplate(image=spectrum, templ=template, method=cv.TM_SQDIFF_NORMED) | |
| min_val, _, min_loc, _ = cv.minMaxLoc(sqdiff_normed) | |
| # msg = "label1: {}; label2: {}; min_val: {}".format(label1, label2, min_val) | |
| # print(msg) | |
| row = { | |
| "template_label": template_label, | |
| "template_file": template_file.as_posix(), | |
| "wav_label": wav_label, | |
| "wav_file": wav_file.as_posix(), | |
| "min_val": min_val, | |
| } | |
| result.append(row) | |
| result = pd.DataFrame(result) | |
| result.to_excel("result.xlsx", index=False) | |
| return | |
| if __name__ == '__main__': | |
| main() | |