test dinov2

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.csv filter=lfs diff=lfs merge=lfs -text

_test_preprocessed.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8615ab5f08f97624cfc5d3200a0a573dac6e99958196ff297000ce8c6b572fcf
+size 12274373

script.py

@@ -23,15 +23,15 @@ 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)
-            weights = torch.load(model_path, map_location=self.device)
-            model.load_state_dict({w.replace("model.", ""): v for w, v in weights.items()})
+            model = timm.create_model(model_name, num_classes=0, pretrained=False)
+            # weights = torch.load(model_path, map_location=self.device)
+            # model.load_state_dict({w.replace("model.", ""): v for w, v in weights.items()})
 
             return model.to(self.device).eval()
 
         self.model = _load_model(model_name, model_path)
 
-        self.transforms = T.Compose([T.Resize((224, 224)),
+        self.transforms = T.Compose([T.Resize((518, 518)),
                                      T.ToTensor(),
                                      T.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])])
 
@@ -43,9 +43,9 @@ class PytorchWorker:
         :return: A list with logits and confidences.
         """
 
-        logits = self.model(self.transforms(image).unsqueeze(0).to(self.device))
+        self.model(self.transforms(image).unsqueeze(0).to(self.device))
 
-        return logits.tolist()
+        return [-1]
 
 
 def make_submission(test_metadata, model_path, model_name, output_csv_path="./submission.csv", images_root_path="/tmp/data/private_testset"):
@@ -77,33 +77,34 @@ def make_submission(test_metadata, model_path, model_name, output_csv_path="./su
 if __name__ == "__main__":
 
     MODEL_PATH = "metaformer-s-224.pth"
-    MODEL_NAME = "caformer_s18.sail_in22k"
+    MODEL_NAME = "timm/vit_base_patch14_reg4_dinov2.lvd142m"
 
     # Real submission
-    import zipfile
+    # import zipfile
 
-    with zipfile.ZipFile("/tmp/data/private_testset.zip", 'r') as zip_ref:
-        zip_ref.extractall("/tmp/data")
-
-    metadata_file_path = "./FungiCLEF2024_TestMetadata.csv"
-    test_metadata = pd.read_csv(metadata_file_path)
-
-    make_submission(
-        test_metadata=test_metadata,
-        model_path=MODEL_PATH,
-        model_name=MODEL_NAME
-    )
-
-    # Test submission
-    # metadata_file_path = "../trial_test.csv"
+    # with zipfile.ZipFile("/tmp/data/private_testset.zip", 'r') as zip_ref:
+    #     zip_ref.extractall("/tmp/data")
 
+    # metadata_file_path = "./test_preprocessed.csv"
     # test_metadata = pd.read_csv(metadata_file_path)
 
     # make_submission(
     #     test_metadata=test_metadata,
     #     model_path=MODEL_PATH,
-    #     model_name=MODEL_NAME,
-    #     images_root_path="../data/DF"
+    #     model_name=MODEL_NAME
     # )
 
+    # Test submission
+
+    metadata_file_path = "../trial_submission.csv"
+
+    test_metadata = pd.read_csv(metadata_file_path)
+
+    make_submission(
+        test_metadata=test_metadata,
+        model_path=MODEL_PATH,
+        model_name=MODEL_NAME,
+        images_root_path="../data/DF_FULL"
+    )
+