update

app.py

@@ -57,7 +57,7 @@ with gr.Blocks() as demo:
                 new_fields = [field for field in fields if field not in filter_list]
                 df = generate_table(results, new_fields)
 
-                df['flag'] = [model_size_flag(x, model_size) for x in df['Parameters (B)']]
+                df['flag'] = [model_size_flag(x, model_size) for x in df['Param (B)']]
                 df = df[df['flag']]
                 df.pop('flag')
                 if len(df):
@@ -119,7 +119,7 @@ with gr.Blocks() as demo:
                     s = structs[DATASETS.index(dataset_name)]
                     headers = s.check_box['essential'] + fields
                     df = cp.deepcopy(s.table)
-                    df['flag'] = [model_size_flag(x, model_size) for x in df['Parameters (B)']]
+                    df['flag'] = [model_size_flag(x, model_size) for x in df['Param (B)']]
                     df = df[df['flag']]
                     df.pop('flag')
                     if len(df):

gen_table.py

@@ -63,7 +63,7 @@ def model_type_flag(line, FIELDS):
 
 def BUILD_L1_DF(results, fields):
     check_box = {}
-    check_box['essential'] = ['Method', 'Parameters (B)', 'Language Model', 'Vision Model']
+    check_box['essential'] = ['Method', 'Param (B)', 'Language Model', 'Vision Model']
     # revise there to set default dataset
     check_box['required'] = ['Avg Score', 'Avg Rank'] + DEFAULT_BENCH
     check_box['avg'] = ['Avg Score', 'Avg Rank']
@@ -95,7 +95,7 @@ def BUILD_L2_DF(results, dataset):
             continue
         meta = item['META']
         for k in META_FIELDS:
-            if k == 'Parameters (B)':
+            if k == 'Param (B)':
                 param = meta['Parameters']
                 res[k].append(float(param.replace('B', '')) if param != '' else None)
             elif k == 'Method':
@@ -120,7 +120,7 @@ def BUILD_L2_DF(results, dataset):
         df = df.iloc[::-1]
 
     check_box = {}
-    check_box['essential'] = ['Method', 'Parameters (B)', 'Language Model', 'Vision Model']
+    check_box['essential'] = ['Method', 'Param (B)', 'Language Model', 'Vision Model']
     check_box['required'] = required_fields
     check_box['all'] = all_fields
     type_map = defaultdict(lambda: 'number')
@@ -143,7 +143,7 @@ def generate_table(results, fields):
         item = results[m]
         meta = item['META']
         for k in META_FIELDS:
-            if k == 'Parameters (B)':
+            if k == 'Param (B)':
                 param = meta['Parameters']
                 res[k].append(float(param.replace('B', '')) if param != '' else None)
             elif k == 'Method':

meta_data.py

@@ -20,7 +20,7 @@ This leaderboard was last updated: {}.
 OpenVLM Leaderboard only includes open-source VLMs or API models that are publicly available. To add your own model to the leaderboard, please create a PR in [VLMEvalKit](https://github.com/open-compass/VLMEvalKit) to support your VLM and then we will help with the evaluation and updating the leaderboard. For any questions or concerns, please feel free to contact us at [opencompass,duanhaodong]@pjlab.org.cn.
 """
 # CONSTANTS-FIELDS
-META_FIELDS = ['Method', 'Parameters (B)', 'Language Model', 'Vision Model', 'OpenSource', 'Verified']
+META_FIELDS = ['Method', 'Param (B)', 'Language Model', 'Vision Model', 'OpenSource', 'Verified']
 MAIN_FIELDS = [
     'MMBench_V11', 'MMStar', 'MME',
     'MMMU_VAL', 'MathVista', 'OCRBench', 'AI2D',