Create app.py

app.py

@@ -0,0 +1,20 @@
+!pip install gradio
+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)