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pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5431a638f8d44f1ea1d67cd65f9d46e05c28eb34b35d697b9739df9beb7fc4d2
-size 118714633
+oid sha256:8e753b4464161be4b061c59e1b3e2dbfb7b0fba36ea913feea467d45391a0149
+size 113472190

script.py

@@ -24,7 +24,7 @@ class PytorchWorker:
             self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
             print(f"Using devide: {self.device}")
 
-            model = timm.create_model(model_name, num_classes=number_of_categories, pretrained=False)
+            model = timm.create_model(model_name, pretrained=False)
 
             # if not torch.cuda.is_available():
             #     model_ckpt = torch.load(model_path, map_location=torch.device("cpu"))
@@ -38,7 +38,7 @@ class PytorchWorker:
 
         self.model = _load_model(model_name, model_path)
 
-        self.transforms = T.Compose([T.Resize((299, 299)),
+        self.transforms = T.Compose([T.Resize((256, 256)),
                                      T.ToTensor(),
                                      T.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])])