Update app.py

app.py

@@ -1,3 +1,5 @@
+from tensorflow.keras.applications.xception import Xception
+import keras.applications.xception as xception
 import gradio as gr
 import tensorflow as tf
 import numpy as np
@@ -7,14 +9,14 @@ import tensorflow.keras as keras
 
 from tensorflow.keras.models import load_model
 
-model=load_model("modeltobeadded")
+model=load_model("Model.h5")
 
 classnames=["Benign","Malignant"]
 
 def predict_image(img):
-  img_4d=img.reshape(-1,299, 299,3)
-  prediction=model.predict(img_4d)[0]
-  return {classnames[i]: float(prediction[i]) for i in range(2)}
+    img_4d=img.reshape(-1,299,299,3)
+    prediction=model.predict(img_4d)[0]
+    return {classnames[i]: float(prediction[i]) for i in range(2)}
 
 image=gr.inputs.Image(shape=(299,299))
 label=gr.outputs.Label(num_top_classes=2)    
@@ -22,5 +24,4 @@ label=gr.outputs.Label(num_top_classes=2)
 article="<p style='text-align: center'>Made by Team AAA</p>"
 
 
-gr.Interface(fn=predict_image,inputs=image,title="Skin Cancer Detection ",description="A Deep CNN Project using Xception Model to detect Skin Cancer ",outputs=label,article=article,enable_queue=True,interpretation='default').launch()
-
+gr.Interface(fn=predict_image,inputs=image,title="Skin Cancer Detection ",description="A Deep CNN Project using Xception Model to detect Skin Cancer ",outputs=label,article=article,enable_queue=True,interpretation='default').launch()