Init app.py

Initial app.py code

app.py

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+import streamlit as st
+import matplotlib.pyplot as matplotlib
+import numpy as np
+import torchaudio
+import sonogram_utility as su
+import time
+
+st.title("Lecturer Support Tool")
+
+file_name = st.file_uploader("Upload an audio of classroom activity to analyze")
+
+supported_file_types = ['.wav','.mp3','.mp4']
+
+if file_name is not None:
+    if not file_name.endswith(supported_file_types):
+        st.error('File must be of type: {}'.format(supported_file_types))
+        file_name = st.empty()
+    else:
+        st.audio(file_name)
+if st.button("Analyze Audio"):
+    if file_name is None:
+        st.error('Upload a file first!')
+    else:
+        # Process
+        # Pretend to take time as an example
+        with st.spinner(text='NOT ACTUALLY ANALYZING, JUST A FILLER ANIMATION'):
+            time.sleep(5)
+            st.success('Done')
+            
+        # RTTM load as filler
+        speakerList, annotations = su.loadAudioRTTM("24F CHEM1402 Night Class Week 4.rttm")
+        
+        # Display breakdowns
+        #--------------------------------------------------------------------------
+        
+        # Prepare data
+        sortedSpeakerList = sorted([[row for row in speaker if row[1] > 0.25] for speaker in speakerList if len([row for row in speaker if row[1] > 0.25]) > 0],
+               key=lambda e: min(e)[0])
+        pred_count = len(sortedSpeakerList)
+        lecturer_speaker_list = su.twoClassExtendAnnotation(sortedSpeakerList)
+        lecturer_pred_count = len(lecturer_speaker_list)
+        
+        # Lecturer vs. Audience
+        #---------------------------------------------------------------------------
+        
+        f, ax1 =plt.subplots()    
+        
+        # Setting Y-axis limits
+        ax1.set_ylim(0, lecturer_pred_count*5 + 5)
+         
+        # Setting X-axis limits
+        #gnt.set_xlim(0, 160)
+         
+        # Setting labels for x-axis and y-axis
+        ax1.set_title('Recording Results')
+        ax1.set_xlabel('Minutes since start')
+        ax1.set_ylabel('Speaker ID')
+    
+        
+        # Setting ticks on y-axis (5,10,15,...)
+        step = 5
+        ax1.set_yticks(list(range(step,(lecturer_pred_count+1)*step,step)))
+        # Labelling tickes of y-axis ('1','2','3',...)
+        pred_tick_list = [1,2]
+        ax1.set_yticklabels(["Lectuerer","Audience"]))
+        x_tick_list = range(0,6000,60)
+        ax1.set_xticks(x_tick_list)
+        ax1.set_xticklabels([str(int(element/60)) for element in x_tick_list])
+        ax1.tick_params(axis='x', labelrotation=90)
+        # Setting graph attribute
+        ax1.grid(True)
+        
+        pred_colors = su.colors(lecturer_pred_count)
+        for j, row in enumerate(lecturer_speaker_list):
+            ax1.broken_barh(row, ((j+1)*5-1, 3), facecolors =(pred_colors[j]))
+        
+        f.set_figheight(5)
+        f.set_figwidth(15)
+        
+        st.pyplot(f)
+        
+        # Experimental Speaker Breakdown
+        #------------------------------------------------------------------------------
+        
+        f, ax1 =plt.subplots()    
+        
+        # Setting Y-axis limits
+        ax1.set_ylim(0, pred_count*5 + 5)
+         
+        # Setting X-axis limits
+        #gnt.set_xlim(0, 160)
+         
+        # Setting labels for x-axis and y-axis
+        ax1.set_title('Recording Results')
+        ax1.set_xlabel('Minutes since start')
+        ax1.set_ylabel('Speaker ID')
+    
+        
+        # Setting ticks on y-axis (5,10,15,...)
+        step = 5
+        ax1.set_yticks(list(range(step,(pred_count+1)*step,step)))
+        # Labelling tickes of y-axis ('1','2','3',...)
+        pred_tick_list = range(1,pred_count+1)
+        ax1.set_yticklabels([str(element) for element in pred_tick_list])
+        x_tick_list = range(0,6000,60)
+        ax1.set_xticks(x_tick_list)
+        ax1.set_xticklabels([str(int(element/60)) for element in x_tick_list])
+        ax1.tick_params(axis='x', labelrotation=90)
+        # Setting graph attribute
+        ax1.grid(True)
+        
+        pred_colors = su.colors(pred_count)
+        for j, row in enumerate(sortedSpeakerList):
+            ax1.broken_barh(row, ((j+1)*5-1, 3), facecolors =(pred_colors[j]))
+        
+        f.set_figheight(5)
+        f.set_figwidth(15)
+        
+        st.pyplot(f)
+