++

src/display/utils.py

@@ -20,17 +20,17 @@ class ColumnContent:
 # Init
 auto_eval_column_dict = [
     ["eval_name", ColumnContent, ColumnContent("Eval Name", "str", True)],
-    ["result_name", ColumnContent, ColumnContent("Result Name", "str", True)],
+    ["result_name", ColumnContent, ColumnContent("Result Name", "str", False)],
     ["date", ColumnContent, ColumnContent("Submission Date", "str", True)],
     ["miou", ColumnContent, ColumnContent("mIoU ⬆️", "number", True)],
     ["accuracy", ColumnContent, ColumnContent("Accuracy ⬆️", "number", False)],
-    ["precision_score", ColumnContent, ColumnContent("Precision ⬆️", "number", False)],
-    ["recall", ColumnContent, ColumnContent("Recall ⬆️", "number", False)],
-    ["f1", ColumnContent, ColumnContent("F1 ⬆️", "number", False)],
-    ["producer_accuracy", ColumnContent, ColumnContent("Producer Accuracy", "list", False)],
-    ["user_accuracy", ColumnContent, ColumnContent("User Accuracy", "list", False)],
-    ["confusion_matrix", ColumnContent, ColumnContent("Confusion Matrix", "matrix", False)],
-    ["num_classes", ColumnContent, ColumnContent("Number of classes", "number", False)],
+    # ["precision_score", ColumnContent, ColumnContent("Precision ⬆️", "number", False)],
+    # ["recall", ColumnContent, ColumnContent("Recall ⬆️", "number", False)],
+    # ["f1", ColumnContent, ColumnContent("F1 ⬆️", "number", False)],
+    # ["producer_accuracy", ColumnContent, ColumnContent("Producer Accuracy", "list", False)],
+    # ["user_accuracy", ColumnContent, ColumnContent("User Accuracy", "list", False)],
+    # ["confusion_matrix", ColumnContent, ColumnContent("Confusion Matrix", "matrix", False)],
+    # ["num_classes", ColumnContent, ColumnContent("Number of classes", "number", False)],
 ]
 
 # We use make dataclass to dynamically fill the scores from Tasks

src/leaderboard/read_evals.py

@@ -10,13 +10,13 @@ class EvalResult:
     result_name: str
     date: str
     accuracy: float
-    precision_score: float
-    recall: float
-    f1: float
+    # precision_score: float
+    # recall: float
+    # f1: float
     miou: float
-    producer_accuracy: List[float]
-    user_accuracy: List[float]
-    confusion_matrix: List[List[float]]
+    # producer_accuracy: List[float]
+    # user_accuracy: List[float]
+    # confusion_matrix: List[List[float]]
 
     @classmethod
     def init_from_json_file(cls, json_filepath):
@@ -39,14 +39,14 @@ class EvalResult:
             eval_name=result_key,
             result_name=result_name,
             date=data.get("submitted_time", ""),
-            accuracy=data.get("accuracy"),
-            precision_score=data.get("precision"),
-            recall=data.get("recall"),
-            f1=data.get("f1"),
-            miou=data.get("miou"),
-            producer_accuracy=data.get("producer_accuracy", []),
-            user_accuracy=data.get("user_accuracy", []),
-            confusion_matrix=data.get("confusion_matrix", []),
+            accuracy=data.get("accuracy", 0)*100,
+            # precision_score=data.get("precision")*100,
+            # recall=data.get("recall")*100,
+            # f1=data.get("f1")*100,
+            miou=data.get("miou", 0)*100,
+            # producer_accuracy=data.get("producer_accuracy", []),
+            # user_accuracy=data.get("user_accuracy", []),
+            # confusion_matrix=data.get("confusion_matrix", []),
         )
 
 
@@ -58,14 +58,14 @@ class EvalResult:
             AutoEvalColumn.result_name.name: self.result_name,
             AutoEvalColumn.date.name: self.date,
             AutoEvalColumn.accuracy.name: self.accuracy,
-            AutoEvalColumn.precision_score.name: self.precision_score,
-            AutoEvalColumn.recall.name: self.recall,
-            AutoEvalColumn.f1.name: self.f1,
-            AutoEvalColumn.producer_accuracy.name: self.producer_accuracy,
-            AutoEvalColumn.user_accuracy.name: self.user_accuracy,
-            AutoEvalColumn.confusion_matrix.name: self.confusion_matrix,
+            # AutoEvalColumn.precision_score.name: self.precision_score,
+            # AutoEvalColumn.recall.name: self.recall,
+            # AutoEvalColumn.f1.name: self.f1,
+            # AutoEvalColumn.producer_accuracy.name: self.producer_accuracy,
+            # AutoEvalColumn.user_accuracy.name: self.user_accuracy,
+            # AutoEvalColumn.confusion_matrix.name: self.confusion_matrix,
             AutoEvalColumn.miou.name: self.miou,
-            AutoEvalColumn.num_classes.name: len(self.producer_accuracy) if self.producer_accuracy else 0,
+            # AutoEvalColumn.num_classes.name: len(self.num_classes) if self.num_classes else 0,
         }
 
         return data_dict