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!pip install gradio |
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import gradio as gr |
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import tensorflow |
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from tensorflow.keras.models import load_model |
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model = load_model('../input/cnn-model/cnn_model.h5') # هنا احمل المودل بعد ما دربته وخزنتة حته اشوف قدرته على التصنيف |
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class_names=['benign','malignant','normal'] |
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def predict_image(img): |
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img_4d=img.reshape(-1,128,128,3) |
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img_4d=img_4d/255 |
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prediction=model.predict(img_4d)[0] |
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return {class_names[i]: float(prediction[i]) for i in range(3)}# range 1 if sigmoid , range=number of class if softmax |
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image = gr.inputs.Image(shape=(128,128)) |
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label = gr.outputs.Label(num_top_classes=3) |
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gr.Interface(fn=predict_image, inputs=image, |
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outputs=label).launch(debug='False',share=True) |