Update app.py

app.py

@@ -2,25 +2,11 @@ import gradio as gr
 from keras.datasets import mnist
 from keras.models import Sequential
 from keras.layers import Conv2D,MaxPooling2D,Dense,Flatten,Dropout
+from tensorflow import keras
 
-import matplotlib.pyplot as plt
 import cv2
 
-
-model2 = Sequential()
-
-model2.add(Conv2D(128,kernel_size=(3,3),activation="relu",input_shape=(28,28,1)))
-model2.add(MaxPooling2D(pool_size=(2,2),strides=2))
-model2.add(Conv2D(64,kernel_size=(3,3),activation="relu"))
-model2.add(MaxPooling2D(pool_size=(2,2),strides=2))
-model2.add(Flatten())
-model2.add(Dense(32,activation="relu"))
-model2.add(Dropout(0.2))
-model2.add(Dense(10,activation="softmax"))
-
-model2.compile(loss="sparse_categorical_crossentropy",optimizer="adam",metrics=["accuracy"])
-
-history = model2.fit(X_train,y_train,epochs=10,validation_data=(X_test,y_test))
+model2 = keras.models.load_model("final_model.h5")
 
 def sketch_recognition(test_img):
   test_img = test_img/255