Update app.py

app.py

@@ -120,7 +120,7 @@ cnn = NeuralNetClassifier(
     optimizer=torch.optim.Adam,  # You can set the optimizer used during training
     device='cpu'  # You can specify the device ('cpu' for CPU, 'cuda' for GPU, etc.)
 )
-
+cnn.fit(XCnn_train, y_train)
 stroke_width = st.sidebar.slider("Stroke width: ", 1, 35, 32)
 stroke_color = st.sidebar.color_picker("Stroke color hex: ")
 bg_color = st.sidebar.color_picker("Background color hex: ", "#eee")
@@ -149,9 +149,10 @@ if canvas_result.image_data is not None:
     #st.image(canvas_result.image_data)
     image = canvas_result.image_data
     image1 = image.copy()
-    image1 = image1.astype('uint8')
+    image1 = image1.astype('float32')
     image1 = cv2.cvtColor(image1,cv2.COLOR_BGR2GRAY)
     image1 = cv2.resize(image1,(28,28))
+    image1 = image1 / 255.0
     st.image(image1)
 
     image1.resize(1,1,28,28)