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