prepare.py

import os
import json
import random
import logging

logger = logging.getLogger(__name__)

def prepare_data(data_original, save_json_train, save_json_valid, save_json_test, split_ratio=[80, 10, 10], seed=12):
    # Setting seeds for reproducible code.
    random.seed(seed)

    # Check if data preparation has already been done (skip if files exist)
    if os.path.exists(save_json_train) and os.path.exists(save_json_valid) and os.path.exists(save_json_test):
        logger.info("Preparation completed in previous run, skipping.")
        return

    # Collect audio files and labels
    wav_list = []
    labels = os.listdir(data_original)

    for label in labels:
        label_dir = os.path.join(data_original, label)
        if os.path.isdir(label_dir):
            for audio_file in os.listdir(label_dir):
                if audio_file.endswith('.wav'):
                    wav_file = os.path.join(label_dir, audio_file)
                    if os.path.isfile(wav_file):
                        wav_list.append((wav_file, label))
                    else:
                        logger.warning(f"Skipping invalid audio file: {wav_file}")

    # Shuffle and split the data
    random.shuffle(wav_list)
    n_total = len(wav_list)
    n_train = n_total * split_ratio[0] // 100
    n_valid = n_total * split_ratio[1] // 100

    train_set = wav_list[:n_train]
    valid_set = wav_list[n_train:n_train + n_valid]
    test_set = wav_list[n_train + n_valid:]

    # Create JSON files for train, valid, and test sets
    create_json(train_set, save_json_train)
    create_json(valid_set, save_json_valid)
    create_json(test_set, save_json_test)

    logger.info(f"Created {save_json_train}, {save_json_valid}, and {save_json_test}")

def create_json(data, json_file):
    data_dict = {str(idx): {'wav': wav, 'label': label} for idx, (wav, label) in enumerate(data)}
    with open(json_file, 'w') as f:
        json.dump(data_dict, f)