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import gradio as gr |
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from tensorflow.keras.models import load_model |
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def classify_pcos(image): |
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preprocessed_image = preprocess_image(image) |
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prediction = model.predict(preprocessed_image) |
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class_index = np.argmax(prediction) |
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class_label = class_labels[class_index] |
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return class_label |
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def preprocess_image(image): |
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return preprocessed_image |
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model = load_model('FightOS_CNN_Models.h5') |
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class_labels = ['positive', 'negative'] |
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iface = gr.Interface( |
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fn=classify_pcos, |
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inputs="image", |
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outputs="text", |
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title="Detecção de PCOS usando imagens de ultrassom", |
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description="Faça upload de uma imagem de ultrassom para classificar se possui PCOS ou não." |
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) |
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iface.launch() |
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