kennymckormick commited on
Commit
e401827
1 Parent(s): ef4756a
Files changed (2) hide show
  1. gen_table.py +5 -6
  2. meta_data.py +8 -2
gen_table.py CHANGED
@@ -7,7 +7,7 @@ import gradio as gr
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  import numpy as np
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  import pandas as pd
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- from meta_data import META_FIELDS, URL
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  def listinstr(lst, s):
@@ -62,16 +62,15 @@ def model_type_flag(line, FIELDS):
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  def BUILD_L1_DF(results, fields):
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  check_box = {}
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  check_box['essential'] = ['Method', 'Parameters (B)', 'Language Model', 'Vision Model']
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- # revise there to set defualt dataset
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- defualt_dataset = ['MMBench_TEST_EN', 'MMBench_TEST_CN', 'MMStar', 'MME', 'MMMU_VAL', 'MathVista', 'OCRBench', 'MMVet', 'AI2D', 'HallusionBench', 'LLaVABench', 'SEEDBench_IMG']
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- check_box['required'] = ['Avg Score', 'Avg Rank'] + defualt_dataset
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  check_box['avg'] = ['Avg Score', 'Avg Rank']
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  check_box['all'] = check_box['avg'] + fields
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  type_map = defaultdict(lambda: 'number')
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  type_map['Method'] = 'html'
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  type_map['Language Model'] = type_map['Vision Model'] = type_map['OpenSource'] = type_map['Verified'] = 'str'
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  check_box['type_map'] = type_map
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-
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  res = generate_table(results, fields)
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  df = pd.DataFrame(res)
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  df = df.sort_values('Avg Score')
@@ -169,4 +168,4 @@ def generate_table(results, fields, df=None):
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  df.update(res)
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  df = df.sort_values('Avg Score')
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  df = df.iloc[::-1]
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- return df
 
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  import numpy as np
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  import pandas as pd
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+ from meta_data import DEFAULT_BENCH, META_FIELDS, URL
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  def listinstr(lst, s):
 
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  def BUILD_L1_DF(results, fields):
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  check_box = {}
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  check_box['essential'] = ['Method', 'Parameters (B)', 'Language Model', 'Vision Model']
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+ # revise there to set default dataset
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+ check_box['required'] = ['Avg Score', 'Avg Rank'] + DEFAULT_BENCH
 
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  check_box['avg'] = ['Avg Score', 'Avg Rank']
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  check_box['all'] = check_box['avg'] + fields
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  type_map = defaultdict(lambda: 'number')
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  type_map['Method'] = 'html'
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  type_map['Language Model'] = type_map['Vision Model'] = type_map['OpenSource'] = type_map['Verified'] = 'str'
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  check_box['type_map'] = type_map
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+
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  res = generate_table(results, fields)
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  df = pd.DataFrame(res)
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  df = df.sort_values('Avg Score')
 
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  df.update(res)
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  df = df.sort_values('Avg Score')
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  df = df.iloc[::-1]
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+ return df
meta_data.py CHANGED
@@ -24,6 +24,11 @@ MAIN_FIELDS = [
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  'MMMU_VAL', 'MathVista', 'OCRBench', 'AI2D',
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  'HallusionBench', 'SEEDBench_IMG', 'MMVet', 'LLaVABench', 'CCBench', 'RealWorldQA'
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  ]
 
 
 
 
 
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  MMBENCH_FIELDS = ['MMBench_TEST_EN', 'MMBench_DEV_EN', 'MMBench_TEST_CN', 'MMBench_DEV_CN', 'CCBench']
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  MODEL_SIZE = ['<10B', '10B-20B', '20B-40B', '>40B', 'Unknown']
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  MODEL_TYPE = ['API', 'OpenSource', 'Proprietary']
@@ -37,8 +42,9 @@ LEADERBOARD_MD['MAIN'] = f"""
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  - Metrics:
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  - Avg Score: The average score on all VLM Benchmarks (normalized to 0 - 100, the higher the better).
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  - Avg Rank: The average rank on all VLM Benchmarks (the lower the better).
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- - The overall evaluation results on {len(MAIN_FIELDS)} VLM benchmarks, sorted by the descending order of Avg Score.
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- - The following datasets are included in the main results: {', '.join(MAIN_FIELDS)}.
 
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  - Detailed evaluation results for each dataset (included or not included in main) are provided in the consequent tabs.
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  """
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  'MMMU_VAL', 'MathVista', 'OCRBench', 'AI2D',
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  'HallusionBench', 'SEEDBench_IMG', 'MMVet', 'LLaVABench', 'CCBench', 'RealWorldQA'
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  ]
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+ DEFAULT_BENCH = [
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+ 'MMBench_TEST_EN', 'MMBench_TEST_CN', 'MMStar', 'MME',
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+ 'MMMU_VAL', 'MathVista', 'OCRBench', 'AI2D',
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+ 'HallusionBench', 'SEEDBench_IMG', 'MMVet', 'LLaVABench'
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+ ]
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  MMBENCH_FIELDS = ['MMBench_TEST_EN', 'MMBench_DEV_EN', 'MMBench_TEST_CN', 'MMBench_DEV_CN', 'CCBench']
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  MODEL_SIZE = ['<10B', '10B-20B', '20B-40B', '>40B', 'Unknown']
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  MODEL_TYPE = ['API', 'OpenSource', 'Proprietary']
 
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  - Metrics:
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  - Avg Score: The average score on all VLM Benchmarks (normalized to 0 - 100, the higher the better).
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  - Avg Rank: The average rank on all VLM Benchmarks (the lower the better).
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+ - Avg Score & Rank are calculated based on selected benchmark.
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+ - By default, we present the overall evaluation results based on {len(DEFAULT_BENCH)} VLM benchmarks, sorted by the descending order of Avg Score.
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+ - The following datasets are included in the main results: {', '.join(DEFAULT_BENCH)}.
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  - Detailed evaluation results for each dataset (included or not included in main) are provided in the consequent tabs.
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  """
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