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import gradio as gr |
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import tensorflow as tf |
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model = tf.keras.models.load_model('best_model.h5') |
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categories = ["Normal","Pneumonia", "Tubercolosis"] |
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def classify(img): |
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img = img.reshape((-1, 224, 224, 3)) |
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pred = model.predict(img)[0] |
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return {categories[i]: float(pred[i]) for i in range(3)} |
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image = gr.inputs.Image(shape=(224, 224)) |
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label = gr.outputs.Label(num_top_classes=3) |
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examples = ["Normal.png", "Tuberculosis.png", "Pneumonia.jpeg"] |
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intf = gr.Interface(classify,inputs=image, outputs=label, examples=examples, capture_session=True) |
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intf.launch(inline=False) |
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