Update app.py

app.py

@@ -41,10 +41,13 @@ model=load_model('Models/best_model1.h5')
 #     return result
 
 def classify_image(inp):
-  inp = inp.reshape((-1, IMG_SIZE, IMG_SIZE, 3))
-  inp = tf.keras.applications.vgg16.preprocess_input(inp)
-  prediction = model.predict(inp).flatten()
-  return {labels[i]: float(prediction[i]) for i in range(NUM_CLASSES)}
+    # Resize the image to the required size
+    inp = tf.image.resize(inp, [IMG_SIZE, IMG_SIZE])
+    inp = inp.numpy()
+    inp = inp.reshape((-1, IMG_SIZE, IMG_SIZE, 3))
+    inp = tf.keras.applications.vgg16.preprocess_input(inp)
+    prediction = model.predict(inp).flatten()
+    return {labels[i]: float(prediction[i]) for i in range(NUM_CLASSES)}
 
 # image = gr.inputs.Image(shape=(IMG_SIZE, IMG_SIZE))
 # label = gr.outputs.Label(num_top_classes=2)