app.py

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)