updating data

preprocessing

tts/StyleTTS2TrainOG/resample_all.py

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+import os
+import torchaudio
+
+def load_and_resample_audio(file_path, target_sample_rate=24000):
+    # Load audio file
+    waveform, sample_rate = torchaudio.load(file_path)
+
+    # Resample to target_sample_rate if necessary
+    if sample_rate != target_sample_rate:
+        resampler = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=target_sample_rate)
+        waveform = resampler(waveform)
+
+    # Convert to mono by averaging the channels if it's not already mono
+    if waveform.shape[0] > 1:
+        waveform = waveform.mean(dim=0, keepdim=True)
+
+    return waveform, target_sample_rate
+
+def process_and_overwrite_audio_files(folder_paths, target_sample_rate=24000):
+    for folder_path in folder_paths:
+        # Iterate through each file in the folder
+        for filename in os.listdir(folder_path):
+            file_path = os.path.join(folder_path, filename)
+            
+            # Check if the path is an actual file to prevent trying to load directories
+            if os.path.isfile(file_path):
+                try:
+                    # Load, resample, and convert to mono
+                    waveform, _ = load_and_resample_audio(file_path, target_sample_rate)
+                    
+                    # Overwrite the original file with the processed audio
+                    torchaudio.save(file_path, waveform, target_sample_rate)
+                    print(f"Processed and overwritten: {file_path}")
+                except Exception as e:
+                    print(f"Error processing {file_path}: {e}")
+
+# Example usage:
+# Replace these with the paths to your folders containing audio files
+folder_paths = ['ood', 'wavs','val']
+process_and_overwrite_audio_files(folder_paths)