update app.py

app.py

@@ -27,11 +27,26 @@ from pytorch_grad_cam.utils.image import show_cam_on_image
 import gradio as gr
 import misclas_helper
 import gradcam_helper
+import lightningmodel
 from misclas_helper import display_cifar_misclassified_data
 from gradcam_helper import display_gradcam_output
+from misclas_helper import get_misclassified_data2
+from lightningmodel import LitResnet
 
 fileName = None
 
+targets = None
+device = torch.device("cpu")
+classes = ('plane', 'car', 'bird', 'cat', 'deer',
+           'dog', 'frog', 'horse', 'ship', 'truck')
+
+model = LitResnet(lr=0.05).load_from_checkpoint("/content/weights.ckpt")
+
+device = torch.device("cpu")
+
+# Get the misclassified data from test dataset
+misclassified_data = get_misclassified_data2(model, device, 20)
+
 def hello(DoYouWantToShowMisClassifiedImages, HowManyImages):
   if(DoYouWantToShowMisClassifiedImages.lower() == "yes"):
     fileName = misclas_helper.display_cifar_misclassified_data(misclassified_data, classes, inv_normalize, number_of_samples=HowManyImages)
@@ -49,11 +64,6 @@ misClass_demo = gr.Interface(
 
 ############
 
-targets = None
-device = torch.device("cpu")
-classes = ('plane', 'car', 'bird', 'cat', 'deer',
-           'dog', 'frog', 'horse', 'ship', 'truck')
-
 
 def inference(DoYouWantToShowGradCAMMedImages, HowManyImages, WhichLayer, transparency):
   if(DoYouWantToShowGradCAMMedImages.lower() == "yes"):