| 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, |
| ) |
| 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 |
|
|
