Madhavan Iyengar commited on
Commit
b5bca51
1 Parent(s): a6073db

fix issues with decimals

Browse files
Files changed (2) hide show
  1. src/about.py +17 -16
  2. src/envs.py +1 -1
src/about.py CHANGED
@@ -12,25 +12,26 @@ class Task:
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  # ---------------------------------------------------
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  class Tasks(Enum):
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  # task_key in the json file, metric_key in the json file, name to display in the leaderboard
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- task0 = Task("random", "accuracy", "Accuracy (Random)")
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- task2 = Task("popular", "accuracy", "Accuracy (Popular)")
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- task1 = Task("adversarial", "accuracy", "Accuracy (Adversarial)")
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- task7 = Task("random", "precision_score", "Precision (Random)")
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- task11 = Task("adversarial", "precision_score", "Precision (Adversarial)")
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- task3 = Task("popular", "precision_score", "Precision (Popular)")
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- task8 = Task("random", "recall", "Recall (Random)")
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- task12 = Task("adversarial", "recall", "Recall (Adversarial)")
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- task4 = Task("popular", "recall", "Recall (Popular)")
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- task9 = Task("random", "f1_score", "F1 Score (Random)")
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- task5 = Task("popular", "f1_score", "F1 Score (Popular)")
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- task13 = Task("adversarial", "f1_score", "F1 Score (Adversarial)")
 
 
 
 
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- task10 = Task("random", "yes_percent", "Yes Percent (Random)")
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- task6 = Task("popular", "yes_percent", "Yes Percent (Popular)")
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- task14 = Task("adversarial", "yes_percent", "Yes Percent (Adversarial)")
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  NUM_FEWSHOT = 0 # Change with your few shot
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  # ---------------------------------------------------
@@ -91,7 +92,7 @@ CITATION_BUTTON_TEXT = r"""
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  @misc{yang20243dgrand,
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  title={3D-GRAND: Towards Better Grounding and Less Hallucination for 3D-LLMs},
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  author={Jianing Yang and Xuweiyi Chen and Nikhil Madaan and Madhavan Iyengar and Shengyi Qian and David F. Fouhey and Joyce Chai},
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- year=\{2024\},
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  eprint={2406.05132},
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  archivePrefix={arXiv},
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  primaryClass={cs.CV}
 
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  # ---------------------------------------------------
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  class Tasks(Enum):
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  # task_key in the json file, metric_key in the json file, name to display in the leaderboard
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+ task0 = Task("random_accuracy", "random_accuracy", "Accuracy (Random)")
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+ task2 = Task("popular_accuracy", "popular_accuracy", "Accuracy (Popular)")
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+ task1 = Task("adversarial_accuracy", "adversarial_accuracy", "Accuracy (Adversarial)")
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+ task7 = Task("random_precision", "random_precision", "Precision (Random)")
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+ task3 = Task("popular_precision", "popular_precision", "Precision (Popular)")
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+ task11 = Task("adversarial_precision", "adversarial_precision", "Precision (Adversarial)")
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+ task8 = Task("random_recall", "random_recall", "Recall (Random)")
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+ task4 = Task("popular_recall", "popular_recall", "Recall (Popular)")
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+ task12 = Task("adversarial_recall", "adversarial_recall", "Recall (Adversarial)")
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+ task9 = Task("random_f1_score", "random_f1_score", "F1 Score (Random)")
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+ task5 = Task("popular_f1_score", "popular_f1_score", "F1 Score (Popular)")
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+ task13 = Task("adversarial_f1_score", "adversarial_f1_score", "F1 Score (Adversarial)")
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+
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+ task10 = Task("random_yes_percentage", "random_yes_percentage", "Yes Percent (Random)")
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+ task6 = Task("popular_yes_percentage", "popular_yes_percentage", "Yes Percent (Popular)")
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+ task14 = Task("adversarial_yes_percentage", "adversarial_yes_percentage", "Yes Percent (Adversarial)")
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  NUM_FEWSHOT = 0 # Change with your few shot
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  # ---------------------------------------------------
 
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  @misc{yang20243dgrand,
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  title={3D-GRAND: Towards Better Grounding and Less Hallucination for 3D-LLMs},
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  author={Jianing Yang and Xuweiyi Chen and Nikhil Madaan and Madhavan Iyengar and Shengyi Qian and David F. Fouhey and Joyce Chai},
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+ year={2024},
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  eprint={2406.05132},
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  archivePrefix={arXiv},
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  primaryClass={cs.CV}
src/envs.py CHANGED
@@ -7,7 +7,7 @@ from huggingface_hub import HfApi
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  TOKEN = os.environ.get("TOKEN") # A read/write token for your org
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  OWNER = "sled-umich" # Change to your org - don't forget to create a results and request dataset, with the correct format!
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- # ----------------------------------
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  REPO_ID = f"{OWNER}/3D-POPE-leaderboard"
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  QUEUE_REPO = f"{OWNER}/3D-POPE-requests"
 
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  TOKEN = os.environ.get("TOKEN") # A read/write token for your org
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  OWNER = "sled-umich" # Change to your org - don't forget to create a results and request dataset, with the correct format!
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+ # ----------------------------------``
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  REPO_ID = f"{OWNER}/3D-POPE-leaderboard"
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  QUEUE_REPO = f"{OWNER}/3D-POPE-requests"