local links updated

app.py

@@ -22,14 +22,14 @@ import pandas as pd
 import io
 import base64
 
-# checking the mounted drive and mounting if not done
-if not os.path.exists('/content/gdrive'):
-  from google.colab import drive
-  drive.mount('/content/gdrive')
-else:
-    print("Google Drive is already mounted.")
+# # checking the mounted drive and mounting if not done
+# if not os.path.exists('/content/gdrive'):
+#   from google.colab import drive
+#   drive.mount('/content/gdrive')
+# else:
+#     print("Google Drive is already mounted.")
 
-list_c1 = torch.load('/content/gdrive/MyDrive/da_demo/cv/models/26_06/list_mnist_m_non_dann_misclassified_dann_classified.pt')
+list_c1 = torch.load('list_mnist_m_non_dann_misclassified_dann_classified.pt')
 
 class CustomDataset(torch.utils.data.Dataset):
     def __init__(self, data):
@@ -54,7 +54,7 @@ def get_images():
     pil_images = [transform_to_pil(image) for image in images]
     return pil_images, labels.tolist()
 
-list_c2 = torch.load('/content/gdrive/MyDrive/da_demo/cv/models/26_06/list_mnist_m_non_dann_misclassified_dann_misclassified.pt')
+list_c2 = torch.load('list_mnist_m_non_dann_misclassified_dann_misclassified.pt')
 dataset_c2 = CustomDataset(list_c2)
 dataloader_c2 = torch.utils.data.DataLoader(dataset_c2, batch_size=10, shuffle=True)
 def get_images_2():
@@ -173,7 +173,7 @@ class Network(nn.Module):
 loaded_model_non_dann = Network()
 loaded_model_non_dann = loaded_model_non_dann.to(device)
 # Load the saved state dictionary
-loaded_model_non_dann.load_state_dict(torch.load('/content/gdrive/MyDrive/da_demo/cv/models/26_06/non_dann_26_06.pt', map_location=device), strict=False)
+loaded_model_non_dann.load_state_dict(torch.load('non_dann_26_06.pt', map_location=device), strict=False)
 loaded_model_non_dann.eval()
 
 ##  DANN
@@ -181,7 +181,7 @@ loaded_model_non_dann.eval()
 loaded_model_dann = Network()
 loaded_model_dann = loaded_model_dann.to(device)
 # Load the saved state dictionary
-loaded_model_dann.load_state_dict(torch.load('/content/gdrive/MyDrive/da_demo/cv/models/26_06/dann_26_06.pt', map_location=device), strict=False)
+loaded_model_dann.load_state_dict(torch.load('dann_26_06.pt', map_location=device), strict=False)
 loaded_model_dann.eval()
 
 img_size = 28 # for mnist
@@ -329,7 +329,7 @@ def classify_image_inference(image):
 
 def display_image():
     # Load the image from a local file
-    image = Image.open("/content/gdrive/MyDrive/da_demo/mnist-m.JPG")
+    image = Image.open("mnist-m.JPG")
     return image
 
 with gr.Blocks() as demo: