Update app.py

app.py

@@ -1,4 +1,16 @@
 import gradio as gr
+import pickle
+import matplotlib.pyplot as plt
+import numpy as np
+import os
+import PIL
+import tensorflow as tf
+from tensorflow import keras
+from tensorflow.keras import layers
+
+model_final = pickle.load(open('model_f.pkl','rb'))
+
+
 from tensorflow.keras.models import Sequential
 model = Sequential([
   layers.experimental.preprocessing.Rescaling(1./255, input_shape=(img_height, img_width, 3)),
@@ -15,7 +27,7 @@ model = Sequential([
 
 def predict_image(img):
   img_2d=img.reshape(-1,180,180,3)
-  prediction=model.predict(img_2d)[0]
+  prediction=model_final.predict(img_2d)[0]
   return {class_names[i]: float(prediction[i]) for i in range(5)}
 
 image = gr.inputs.Image(shape=(180,180))