Update

app.py

@@ -174,12 +174,10 @@ def evaluate_submission(file, submission_name, model_description):
         return f"❌ Error during merge for MAE: {e}"
     
     # Convert weight columns to numeric.
-    df["weight_gt"] = pd.to_numeric(df["weight"], errors="coerce")
-    df["weight_pred"] = pd.to_numeric(df["weight_pred"], errors="coerce")  # Note: prediction file column might be named "weight" as well.
-    # If prediction CSV uses the same column name 'weight', adjust accordingly:
-    if "weight_pred" not in df.columns:
-        df.rename(columns={"weight": "weight_pred"}, inplace=True)
-        df["weight_gt"] = pd.to_numeric(gt_df["weight"], errors="coerce")
+    # After merging, the ground truth weight is in "weight_gt" and prediction weight in "weight_pred"
+    df["weight_gt"] = pd.to_numeric(df["weight_gt"], errors="coerce")
+    df["weight_pred"] = pd.to_numeric(df["weight_pred"], errors="coerce")
+
     
     # Filter out rows where either weight is -1.
     before_filter = df.shape[0]

requirements.txt

@@ -5,4 +5,4 @@ APScheduler==3.9.1
 huggingface-hub>=0.10.0
 pydantic==2.10.6
 scikit-learn==1.3.2
-pycocotools
+pycocotools==2.0.8