khhuiyh commited on
Commit
3a09e7a
·
1 Parent(s): 21a0003

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +2 -2
app.py CHANGED
@@ -1,6 +1,6 @@
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  MODEL_INFO = ["Model"]
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  AVGACC = "Overall Acc."
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- TASK_INFO = [AVGACC, "Dynamic Perception","State Transitions Perception","Camera Movement Perception","Explanatory Reasoning","Counterfactual Reasoning","Predictive Reasoning","Comparison Reasoning","Reasoning with External Knowledge","Description"]
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  DATA_TITILE_TYPE = ["markdown", "number", "number", "number", "number", "number", "number", "number", "number", "number", "number"]
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  CSV_DIR = "./file/result.csv"
@@ -124,7 +124,7 @@ def add_new_eval(
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  if model_name_textbox in model_name_list:
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  return "In the leaderboard, there already exists a model with the same name, and duplicate submissions of it are not allowed.", get_result_df()
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- questiontype = ["Dynamic Perception","State Transitions Perception","Camera Movement Perception","Explanatory Reasoning","Counterfactual Reasoning","Predictive Reasoning","Comparison Reasoning","Reasoning with External Knowledge","Description"]
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  id2questiontype = dict(zip(range(1, 10),questiontype))
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  content = input_file.decode("utf-8").strip()
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  userdata = content.split('\n')
 
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  MODEL_INFO = ["Model"]
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  AVGACC = "Overall Acc."
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+ TASK_INFO = [AVGACC, "Dynamic Perception","State Transitions Perception","Comparison Reasoning","Reasoning with External Knowledge","Explanatory Reasoning","Predictive Reasoning","Description","Counterfactual Reasoning","Camera Movement Perception"]
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  DATA_TITILE_TYPE = ["markdown", "number", "number", "number", "number", "number", "number", "number", "number", "number", "number"]
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  CSV_DIR = "./file/result.csv"
 
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  if model_name_textbox in model_name_list:
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  return "In the leaderboard, there already exists a model with the same name, and duplicate submissions of it are not allowed.", get_result_df()
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+ questiontype = COLUMN_NAMES[-9:]
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  id2questiontype = dict(zip(range(1, 10),questiontype))
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  content = input_file.decode("utf-8").strip()
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  userdata = content.split('\n')