app.py

app.py

@@ -16,8 +16,6 @@ import cv2
 from IPython.display import Audio
 
 classes_names = ['Benjamin_Netanyau', 'Jens_Stoltenberg', 'Julia_Gillard', 'Magaret_Tarcher', 'Nelson_Mandela']
-labels = [0, 1, 2, 3, 4]
-class_labels = {0: 'Benjamin_Netanyau', 1: 'Jens_Stoltenberg', 2: 'Julia_Gillard', 3: 'Magaret_Tarcher', 4: 'Nelson_Mandela'}
 
 # Percentage of samples to use for validation
 # VALID_SPLIT = 0.1
@@ -91,13 +89,13 @@ input = [gr.inputs.Audio(source="upload", type="filepath", label="Take audio sam
 # the app outputs two segmented images
 output = [gr.outputs.Textbox(label="Predicted Speaker"), gr.outputs.Audio(label="Corresponding Audio")]
 # it's good practice to pass examples, description and a title to guide users
-examples = [['/content/drive/MyDrive/Downloads/16000_pcm_speeches/audio/Benjamin_Netanyau/260.wav', 'Benjamin_Netanyau'], 
-            ['/content/drive/MyDrive/Downloads/16000_pcm_speeches/audio/Jens_Stoltenberg/611.wav', 'Jens_Stoltenberg'], 
-            ['/content/drive/MyDrive/Downloads/16000_pcm_speeches/audio/Julia_Gillard/65.wav', 'Julia_Gillard'], 
-            ['/content/drive/MyDrive/Downloads/16000_pcm_speeches/audio/Magaret_Tarcher/1083.wav', 'Magaret_Tarcher'],
-            ['/content/drive/MyDrive/Downloads/16000_pcm_speeches/audio/Nelson_Mandela/605.wav', 'Nelson_Mandela']]
+examples = [['audios/260.wav', 'Benjamin_Netanyau'], 
+            ['audios/611.wav', 'Jens_Stoltenberg'], 
+            ['audios/65.wav', 'Julia_Gillard'], 
+            ['audios/1083.wav', 'Magaret_Tarcher'],
+            ['audios/605.wav', 'Nelson_Mandela']]
 title = "Speaker Recognition"
 description = "Select the noisy audio samples from examples to check whether the speaker recognised by the model is correct or not even in presence of noise !!!"
 
 gr.Interface(fn=predict, inputs = input, outputs = output, examples=examples, allow_flagging=False, analytics_enabled=False,
-  title=title, description=description, article="Space By: <u><a href="https://github.com/robotjellyzone"><b>Kavya Bisht</b></a></u> \n Based on <a href="https://keras.io/examples/audio/speaker_recognition_using_cnn/"><b>this notebook</b></a>").launch(enable_queue=True, debug=True)
+  title=title, description=description, article="Space By: <u><a href='https://github.com/robotjellyzone'><b>Kavya Bisht</b></a></u> \n Based on <a href='https://keras.io/examples/audio/speaker_recognition_using_cnn/'><b>this notebook</b></a>").launch(enable_queue=True, debug=True)