check

app.py

@@ -11,7 +11,7 @@ from pl_bolts.transforms.dataset_normalizations import cifar10_normalization
 
 model = ResNet18(0.00333)
 
-state_model = torch.load("save_model.pkl", map_location=torch.device('cpu'))
+state_model = torch.load("final_model.pkl", map_location=torch.device('cpu'))
 state_dict = state_model.state_dict()
 
 model.load_state_dict(state_dict, strict=False)
@@ -43,11 +43,11 @@ def inference(input_img, transparency = 0.5, target_layer_number = -1):
     org_img = input_img
 
     input_img = input_img.reshape((32, 32, 3))
-    input_img = cifar10_normalization()(input_img)
     transform = transforms.ToTensor()
 
     input_img = transform(input_img)
     input_img = input_img.unsqueeze(0)
+    input_img = cifar10_normalization()(input_img)
     outputs = model(input_img)
     softmax = torch.nn.Softmax(dim=0)
     o = softmax(outputs.flatten())

save_model.pkl → final_model.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c9defecd2554c8ab9c20eb761089e10acce17a6a11e696c3632a97665877dfb5
-size 626468869
+oid sha256:0b232c13b46d9c87644f33fe59e6c691c490b567f9a819d5ca46b7de5aeb6e20
+size 532818376