final submission yolo

script.py

@@ -313,41 +313,41 @@ def make_submission(metadata_df):
     OUTPUT_CSV_PATH = "./submission.csv"
     BASE_CKPT_PATH = "./checkpoints"
 
-    # model_names = [
-    #     "dino_2_optuna_05242231.ckpt",
-    #     "dino_optuna_05241449.ckpt",
-    #     "dino_optuna_05241257.ckpt",
-    #     "dino_optuna_05241222.ckpt",
-    #     "dino_2_optuna_05242055.ckpt",
-    #     "dino_2_optuna_05242156.ckpt",
-    #     "dino_2_optuna_05242344.ckpt",
-    # ]
-
-    # models = []
-
-    # for model_path in model_names:
-    #     print("loading ", model_path)
-    #     ckpt_path = os.path.join(BASE_CKPT_PATH, model_path)
-
-    #     ckpt = torch.load(ckpt_path)
-    #     model = FungiMEEModel()
-    #     model.load_state_dict(
-    #         {w: ckpt["model." + w] for w in model.state_dict().keys()}
-    #     )
-    #     model.eval()
-    #     model.cuda()
-
-    #     models.append(model)
-
-    # fungi_model = FungiEnsembleModel(models)
-
-    ckpt_path = os.path.join(BASE_CKPT_PATH, "dino_2_optuna_05242055.ckpt")
-
-    fungi_model = FungiMEEModel()
-    ckpt = torch.load(ckpt_path)
-    fungi_model.load_state_dict(
-        {w: ckpt["model." + w] for w in fungi_model.state_dict().keys()}
-    )
+    model_names = [
+        "dino_2_optuna_05242231.ckpt",
+        "dino_optuna_05241449.ckpt",
+        "dino_optuna_05241257.ckpt",
+        "dino_optuna_05241222.ckpt",
+        "dino_2_optuna_05242055.ckpt",
+        "dino_2_optuna_05242156.ckpt",
+        "dino_2_optuna_05242344.ckpt",
+    ]
+
+    models = []
+
+    for model_path in model_names:
+        print("loading ", model_path)
+        ckpt_path = os.path.join(BASE_CKPT_PATH, model_path)
+
+        ckpt = torch.load(ckpt_path)
+        model = FungiMEEModel()
+        model.load_state_dict(
+            {w: ckpt["model." + w] for w in model.state_dict().keys()}
+        )
+        model.eval()
+        model.cuda()
+
+        models.append(model)
+
+    fungi_model = FungiEnsembleModel(models)
+
+    # ckpt_path = os.path.join(BASE_CKPT_PATH, "dino_2_optuna_05242055.ckpt")
+
+    # fungi_model = FungiMEEModel()
+    # ckpt = torch.load(ckpt_path)
+    # fungi_model.load_state_dict(
+    #     {w: ckpt["model." + w] for w in fungi_model.state_dict().keys()}
+    # )
 
     embedding_dataset = EmbeddingMetadataDataset(metadata_df)
     loader = DataLoader(embedding_dataset, batch_size=128, shuffle=False)