pls

script.py

@@ -12,12 +12,6 @@ def is_gpu_available():
     """Check if the python package `onnxruntime-gpu` is installed."""
     return torch.cuda.is_available()
 
-WIDTH = 224
-HEIGHT = 224
-
-MODEL_PATH = "metaformer-s-224.pth"
-MODEL_NAME = "caformer_s18.sail_in22k"
-
 class PytorchWorker:
     """Run inference using ONNX runtime."""
 
@@ -37,12 +31,12 @@ class PytorchWorker:
 
         self.model = _load_model(model_name, model_path)
 
-        self.transforms = T.Compose([T.Resize((HEIGHT, WIDTH)),
+        self.transforms = T.Compose([T.Resize((224, 224)),
                                      T.ToTensor(),
                                      T.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])])
 
 
-    def predict_image(self, image: np.ndarray) -> List:
+    def predict_image(self, image: np.ndarray):
         """Run inference using ONNX runtime.
 
         :param image: Input image as numpy array.
@@ -62,7 +56,7 @@ def make_submission(test_metadata, model_path, model_name, output_csv_path="./su
     predictions = []
 
     for _, row in tqdm(test_metadata.iterrows(), total=len(test_metadata)):
-        image_path = os.path.join(images_root_path, row.image_path.replace("jpg", "JPG"))
+        image_path = os.path.join(images_root_path, row.image_path) #.replace("jpg", "JPG"))
 
         test_image = Image.open(image_path).convert("RGB")
 
@@ -80,23 +74,12 @@ def make_submission(test_metadata, model_path, model_name, output_csv_path="./su
 
     user_pred_df[["observation_id", "class_id"]].to_csv(output_csv_path, index=None)
 
-def test_submission():
-
-    metadata_file_path = "../trial_test.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/"
-    )
-
-
 if __name__ == "__main__":
 
-    # test_submission()
+    MODEL_PATH = "metaformer-s-224.pth"
+    MODEL_NAME = "caformer_s18.sail_in22k"
 
+    # Real submission
     import zipfile
 
     with zipfile.ZipFile("/tmp/data/private_testset.zip", 'r') as zip_ref:
@@ -110,3 +93,17 @@ if __name__ == "__main__":
         model_path=MODEL_PATH,
         model_name=MODEL_NAME
     )
+
+    # Test submission
+    # metadata_file_path = "../trial_test.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"
+    # )
+
+