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db3f5a4
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6ca9fb4
Upload app.py
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app.py
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import gradio as gr
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import pickle
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filename = "Our_Trained_knn_model.pickle"
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def predict(inp):
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best_classifiers = pickle.load(open(filename, 'rb'))
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emotion = best_classifiers.predict(inp)
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return emotion
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if __name__ == "__main__":
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audio = gr.inputs.Audio(source="upload", type="numpy", label=None, optional=False)
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#gr.Interface(fn=emotion_recognizer, inputs=audio, outputs="text", capture_session=True).launch()
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iface = gr.Interface(fn=predict, inputs = "audio", outputs = "text")
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iface.launch(share=True)
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