rustom/Audio_plot_Streamlit

1import streamlit as st2import librosa3import librosa.display4import matplotlib.pyplot as plt5import numpy as np6 7 8def LIBROSA_LOAD(data):9    y,sr = librosa.load(data,sr = None)10    11    return y,sr12    13def TWO_PLOT_TIME_DOMAIN(signal1,signal2):14    y_1,sr = LIBROSA_LOAD(signal1)15    y_2,sr = LIBROSA_LOAD(signal2)16 17    fig, ax = plt.subplots(nrows=2, sharex=True, sharey=True)18    librosa.display.waveshow(y_1, sr=sr, ax=ax[0])19    ax[0].set(title='Time domain plot of {}'.format(signal1))20    ax[0].label_outer()21 22    librosa.display.waveshow(y_2, sr=sr, ax=ax[1])23    ax[1].set(title='Time domain plot of {}'.format(signal2))24    plt.plot()25 26    # Render the Matplotlib figure in Streamlit27    st.pyplot(fig)28 29 30def DIFF_TWO_PLOT_TIME_DOMAIN(y_1,sr_1,y_2,sr_2):31    #y_1,sr = LIBROSA_LOAD(signal1)32    #y_2,sr = LIBROSA_LOAD(signal2)33 34    fig, ax = plt.subplots(nrows=2, sharex=True, sharey=True)35    librosa.display.waveshow(y_1, sr=sr_1, ax=ax[0])36    ax[0].set(title='Time domain plot of Expert')37    ax[0].label_outer()38 39    librosa.display.waveshow(y_2, sr=sr_2, ax=ax[1])40    ax[1].set(title='Time domain plot of  Learner')41    plt.plot()42 43    # Render the Matplotlib figure in Streamlit44    st.pyplot(fig)45 46def TWO_PLOT_MEL_SPECTROGRAM(signal1,signal2):47    # Load the first audio file and compute its mel spectrogram48    y1,sr1 = LIBROSA_LOAD(signal1)49    y2,sr2 = LIBROSA_LOAD(signal2)50    51    #y1, sr1 = librosa.load(signal1)52    S1 = librosa.feature.melspectrogram(y = y1, sr=sr1)53 54    # Load the second audio file and compute its mel spectrogram55    #y2, sr2 = librosa.load(signal2)56    S2 = librosa.feature.melspectrogram(y = y2, sr=sr2)57 58    # Create a figure with two subplots59    fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(8, 10))60 61    # Plot the first mel spectrogram on the first subplot62    img1 = librosa.display.specshow(librosa.power_to_db(S1, ref=np.max), y_axis='mel', x_axis='time', ax=ax1, cmap='viridis')63    ax1.set(title='Mel Spectrogram of {}'.format(signal1))64    #ax1.set_title('Mel spectrogram of audio file 1')65    fig.colorbar(img1, ax=ax1, format='%+2.0f dB')66 67    # Plot the second mel spectrogram on the second subplot68    img2 = librosa.display.specshow(librosa.power_to_db(S2, ref=np.max), y_axis='mel', x_axis='time', ax=ax2, cmap='viridis')69    #ax2.set_title('Mel spectrogram of audio file 2')70    ax2.set(title='Mel Spectrogram of {}'.format(signal2))71    fig.colorbar(img2, ax=ax2, format='%+2.0f dB')72 73    # Adjust the layout of the subplots74    plt.tight_layout()75 76    # Show the plot77    #plt.show()78    st.pyplot(fig)79 80 81 82def DIFF_TWO_PLOT_MEL_SPECTROGRAM(y1, sr1, y2, sr2):83    # Load the first audio file and compute its mel spectrogram84    # y1,sr1 = LIBROSA_LOAD(signal1)85    # y2,sr2 = LIBROSA_LOAD(signal2)86    87    #y1, sr1 = librosa.load(signal1)88    S1 = librosa.feature.melspectrogram(y = y1, sr=sr1)89 90    # Load the second audio file and compute its mel spectrogram91    #y2, sr2 = librosa.load(signal2)92    S2 = librosa.feature.melspectrogram(y = y2, sr=sr2)93 94    # Create a figure with two subplots95    fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(8, 10))96 97    # Plot the first mel spectrogram on the first subplot98    img1 = librosa.display.specshow(librosa.power_to_db(S1, ref=np.max), y_axis='mel', x_axis='time', ax=ax1, cmap='viridis')99    ax1.set(title='Mel Spectrogram of Expert')100    #ax1.set_title('Mel spectrogram of audio file 1')101    fig.colorbar(img1, ax=ax1, format='%+2.0f dB')102 103    # Plot the second mel spectrogram on the second subplot104    img2 = librosa.display.specshow(librosa.power_to_db(S2, ref=np.max), y_axis='mel', x_axis='time', ax=ax2, cmap='viridis')105    #ax2.set_title('Mel spectrogram of audio file 2')106    ax2.set(title='Mel Spectrogram of Learner')107    fig.colorbar(img2, ax=ax2, format='%+2.0f dB')108 109    # Adjust the layout of the subplots110    plt.tight_layout()111 112    # Show the plot113    #plt.show()114    st.pyplot(fig)115 116 117st.set_page_config(118    page_title="Hello Carnatic Music",119    page_icon="👋",120)121 122st.write("# Drop your files here! 👋")123 124 125 126# Streamlit app127#st.title('Audio Signal Visualization')128 129# File upload130uploaded_file_T = st.file_uploader('Upload an audio file lvl Expert', type=['mp3'])131 132uploaded_file_S = st.file_uploader('Upload an audio file lvl learner', type=['mp3'])133 134# signal_T = uploaded_file_T135 136# signal_S = uploaded_file_S137 138 139 140# Assuming you have the audio data in `y` and the sample rate in `sr`141 142#output_path_T = 'data/output_teacher.wav'  # Specify the output file path143#output_path_S = 'data/output_student.wav'144# Convert and save the audio file145#librosa.output.write_wav(output_path, y, sr)146 147 148if uploaded_file_T is not None:149    if uploaded_file_S is not None:150        y_1, sr_1 = LIBROSA_LOAD(uploaded_file_T)151        y_2, sr_2 = LIBROSA_LOAD(uploaded_file_S)152        #librosa.output.write_wav(output_path_T, y_1, sr_1)153        #librosa.output.write_wav(output_path_S, y_2, sr_2)154        #st.write(y_1,y_2)155        #st.write("Done")156        st.title('Audio Signal Visualization Time Domain')157        # TWO_PLOT_T(uploaded_file_T,uploaded_file_S)158        DIFF_TWO_PLOT_TIME_DOMAIN(y_1,sr_1,y_2,sr_2)159 160        st.title('Audio Signal Visualization Frequency Domain')161        DIFF_TWO_PLOT_MEL_SPECTROGRAM(y_1,sr_1,y_2,sr_2)162 163        164 165 166 167 168        # st.title('Audio Signal Visualization Time Domain')169        # TWO_PLOT_T(uploaded_file_T,uploaded_file_S)170 171 172 173        # st.title('Audio Signal Visualization Frequency Domain')174        # TWO_PLOT_MEL_SPECTROGRAM(uploaded_file_T,uploaded_file_S)175 176        177 178 179 180 181# if uploaded_file_T is not None:182#     if uploaded_file_S is not None:183#         st.title('Audio Signal Visualization Time Domain')184        #TWO_PLOT_T(uploaded_file_T,uploaded_file_S)185 186        #st.title('Audio Signal Visualization Frequency Domain')187        #TWO_PLOT_MEL_SPECTROGRAM(uploaded_file_T,uploaded_file_S)188 189 190         #TWO_PLOT_MEL_SPECTROGRAM(uploaded_file_T,uploaded_file_S)191 192 193# if signal_T is not None:194#     if signal_S is not None:195#         st.title('Audio Signal Visualization Frequency Domain')196#         #TWO_PLOT_TIME_DOMAIN(uploaded_file_T,uploaded_file_S)197#         TWO_PLOT_MEL_SPECTROGRAM(signal_T,signal_S)198 199 200# if uploaded_file_T is not None:201#     if uploaded_file_S is not None:202#         TWO_PLOT_MEL_SPECTROGRAM(uploaded_file_T,uploaded_file_S)203 204 205 206# for i,j in zip(uploaded_file_T,uploaded_file_S):207#     if i is not None and  j is not None:208#         TWO_PLOT_TIME_DOMAIN(i,j)209 210# if uploaded_file_T is not None:211#     audio_data, sr = librosa.load(uploaded_file_T, sr=None)212#     plot_audio_signal(audio_data, sr)213 214    215# if uploaded_file_S is not None:216#     audio_data, sr = librosa.load(uploaded_file_S, sr=None)217#     plot_audio_signal(audio_data, sr)218 219 220 221 222 223 224 225 226