Change data paths

.gitignore

@@ -3,3 +3,6 @@
 
 data/*
 !data/.gitkeep
+
+states/*
+!states/.gitkeep

wsddn-pytorch.py

@@ -123,12 +123,12 @@ def __init__(self, split):
         self.split = split
 
         #loaded_mat = loadmat(f"/kaggle/input/selective-search-windows/selective_search_data/voc_2007_{self.split}.mat")
-        loaded_mat = loadmat(f"~/.datasets/selective_search_data/voc_2007_{self.split}.mat")
+        loaded_mat = loadmat(f"data/selective_search_data/voc_2007_{self.split}.mat")
         self.ssw_boxes = loaded_mat["boxes"][0]
         self.ssw_scores = loaded_mat["boxScores"][0]
 
         #voc_dir = f"/kaggle/input/pascal-voc/voc{self.split}_06-nov-2007/VOCdevkit/VOC2007"
-        voc_dir = f"~/.datasets/VOC{self.split}_06-Nov-2007/VOCdevkit/VOC2007"
+        voc_dir = f"data/VOC{self.split}_06-Nov-2007/VOCdevkit/VOC2007"
         self.ids = [id_.strip() for id_ in open(f"{voc_dir}/ImageSets/Main/{self.split}.txt")]
         self.img_paths = [f"{voc_dir}/JPEGImages/{id_}.jpg" for id_ in self.ids]
         self.annotation_paths = [f"{voc_dir}/Annotations/{id_}.xml" for id_ in self.ids]
@@ -230,10 +230,11 @@ def __len__(self):
 ### Create the network
 
 class WSDDN(nn.Module):
-    base = alexnet(pretrained=True)
+    base = alexnet(pretrained=False)
 
     def __init__(self):
         super().__init__()
+        self.base.load_state_dict(torch.load("states/alexnet-owt-4df8aa71.pth"))
         self.features = self.base.features[:-1]
         self.fcs = self.base.classifier[1:-1]
         self.fc_c = nn.Linear(4096, 20)
@@ -299,7 +300,7 @@ def loss_func(combined_scores, target):
 
         optimizer.step()
 
-    torch.save(net, f"epoch_{epoch}.pt")
+    torch.save(net, f"states/epoch_{epoch}.pt")
 
     print("Avg loss is", epoch_loss / len(train_ds))