xxx

app.py

@@ -0,0 +1,11 @@
+def predict_image(img):
+    img_4d=img.reshape(-1,299,299,3)
+    img_4d=img_4d/255
+    prediction=model.predict(img_4d)[0]
+    #prediction = [1 if x>0.5 else 0 for x in prediction]
+    return {class_names[i]: float(prediction[i]) for i in range(1)}
+    import gradio as gr
+image = gr.inputs.Image(shape=(299,299))
+label = gr.outputs.Label(num_top_classes=1)
+gr.Interface(fn=predict_image, inputs=image,
+             outputs=label).launch(debug='False',share=True)