initial upload attempt

initial upload attempt

system/tts_engines/rvc/lib/tools/analyzer.py

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+import numpy as np
+import matplotlib.pyplot as plt
+import librosa.display
+import librosa
+
+
+def calculate_features(y, sr):
+    stft = np.abs(librosa.stft(y))
+    duration = librosa.get_duration(y=y, sr=sr)
+    cent = librosa.feature.spectral_centroid(S=stft, sr=sr)[0]
+    bw = librosa.feature.spectral_bandwidth(S=stft, sr=sr)[0]
+    rolloff = librosa.feature.spectral_rolloff(S=stft, sr=sr)[0]
+    return stft, duration, cent, bw, rolloff
+
+
+def plot_title(title):
+    plt.suptitle(title, fontsize=16, fontweight="bold")
+
+
+def plot_spectrogram(y, sr, stft, duration, cmap="inferno"):
+    plt.subplot(3, 1, 1)
+    plt.imshow(
+        librosa.amplitude_to_db(stft, ref=np.max),
+        origin="lower",
+        extent=[0, duration, 0, sr / 1000],
+        aspect="auto",
+        cmap=cmap,  # Change the colormap here
+    )
+    plt.colorbar(format="%+2.0f dB")
+    plt.xlabel("Time (s)")
+    plt.ylabel("Frequency (kHz)")
+    plt.title("Spectrogram")
+
+
+def plot_waveform(y, sr, duration):
+    plt.subplot(3, 1, 2)
+    librosa.display.waveshow(y, sr=sr)
+    plt.xlabel("Time (s)")
+    plt.ylabel("Amplitude")
+    plt.title("Waveform")
+
+
+def plot_features(times, cent, bw, rolloff, duration):
+    plt.subplot(3, 1, 3)
+    plt.plot(times, cent, label="Spectral Centroid (kHz)", color="b")
+    plt.plot(times, bw, label="Spectral Bandwidth (kHz)", color="g")
+    plt.plot(times, rolloff, label="Spectral Rolloff (kHz)", color="r")
+    plt.xlabel("Time (s)")
+    plt.title("Spectral Features")
+    plt.legend()
+
+
+def analyze_audio(audio_file, save_plot_path="logs/audio_analysis.png"):
+    y, sr = librosa.load(audio_file)
+    stft, duration, cent, bw, rolloff = calculate_features(y, sr)
+
+    plt.figure(figsize=(12, 10))
+
+    plot_title("Audio Analysis" + " - " + audio_file.split("/")[-1])
+    plot_spectrogram(y, sr, stft, duration)
+    plot_waveform(y, sr, duration)
+    plot_features(librosa.times_like(cent), cent, bw, rolloff, duration)
+
+    plt.tight_layout()
+
+    if save_plot_path:
+        plt.savefig(save_plot_path, bbox_inches="tight", dpi=300)
+    plt.close()
+
+    audio_info = f"""Sample Rate: {sr}\nDuration: {(
+            str(round(duration, 2)) + " seconds"
+            if duration < 60
+            else str(round(duration / 60, 2)) + " minutes"
+    )}\nNumber of Samples: {len(y)}\nBits per Sample: {librosa.get_samplerate(audio_file)}\nChannels: {"Mono (1)" if y.ndim == 1 else "Stereo (2)"}"""
+
+    return audio_info, save_plot_path