Update app.py

app.py

@@ -41,12 +41,7 @@ def get_chunk_times(in_filename, silence_threshold, silence_duration=1):
 
         logging.info(f"TS audio {os.path.basename(in_filename)} = {ts}")
         return ts, chunks
-
-def get_plot(a):
-    x = [1, 2, 3]
-    y = np.array([[1, 2], [3, 4], [5, 6]])
-    plt.plot(x, y)
-    return plt.gcf()
+        
 
 def get_audio_plot(filename, chunks):    
     fig, ax = plt.subplots()
@@ -70,9 +65,9 @@ def get_audio_plot(filename, chunks):
     plt.xlabel('Time [s]')
     plt.ylabel('Amplitude')
     plt.title(os.path.basename(filename))
-    
-    #plt.show()
+
     return plt.gcf()
+    
 
 def get_audio_info(audio):
     ts, chunks = get_chunk_times(audio.name, 30, 1)
@@ -94,47 +89,4 @@ iface = gr.Interface(
     description="Enter .WAV audio to view silence areas",
 )
 
-iface.test_launch()
-iface.launch()
-
-# import matplotlib.pyplot as plt
-# import numpy as np
-# import pandas as pd
-
-# import gradio as gr
-# import matplotlib
-
-# matplotlib.use('Agg')
-
-
-# iaudio = gr.inputs.Audio(source="upload", type="file", label=None)
-
-# def sales_projections(employee_data):
-#     sales_data = employee_data.iloc[:, 1:4].astype("int").to_numpy()
-#     regression_values = np.apply_along_axis(
-#         lambda row: np.array(np.poly1d(np.polyfit([0, 1, 2], row, 2))), 0, sales_data
-#     )
-#     projected_months = np.repeat(
-#         np.expand_dims(np.arange(3, 12), 0), len(sales_data), axis=0
-#     )
-#     projected_values = np.array(
-#         [
-#             month * month * regression[0] + month * regression[1] + regression[2]
-#             for month, regression in zip(projected_months, regression_values)
-#         ]
-#     )
-#     # x = [1, 2, 3]
-#     # y = np.array([[1, 2], [3, 4], [5, 6]])
-#     # plt.plot(x, y)
-#     #plt.plot(projected_values.T)
-#     #plt.legend(employee_data["Name"])
-#     return employee_data, get_plot(1), regression_values
-
-
-# iface = gr.Interface(
-#     get_plot,
-#     iaudio,
-#     ["plot"],
-#     description="Enter sales figures for employees to predict sales trajectory over year.",
-# )
-# iface.launch()
+iface.launch()