CapArena_Auto / src /about.py
ycy
1
66d7de3
from dataclasses import dataclass
from enum import Enum
@dataclass
class Task:
benchmark: str
metric: str
col_name: str
# Select your tasks here
# ---------------------------------------------------
#TODO ζŒ‡ζ ‡
class Tasks(Enum):
# task_key in the json file, metric_key in the json file, name to display in the leaderboard
task0 = Task("Score_avg", "score", "Score_Avg ⬆️")
task1 = Task("Score_gpt", "score", "Score_GPT")
task2 = Task("Score_cog", "score", "Score_COG")
task3 = Task("Score_cpm", "score", "Score_CPM")
task4 = Task("Length_Avg", "scoreL", "Length_Avg")
NUM_FEWSHOT = 0 # Change with your few shot
# ---------------------------------------------------
#TODO title
TITLE = """
<h1 align="center" id="space-title" style="font-family: 'Arial', sans-serif;
font-size: 42px; font-weight: bold;
display: flex; justify-content: center; align-items: center; gap: 12px;">
<span style="font-size: 35px;">πŸ“ˆ</span>
<span style="background: linear-gradient(90deg, #A45EE5, #C085F6, #D8B9FF);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;">
CapArena-Auto Leaderboard
</span>
<span style="font-size: 35px;">πŸ“Š</span>
</h1>
"""
# introduction text
def get_INTRODUCTION_TEXT(model_num: int, LAST_UPDATED: str, paper_link="TODO"):
return f"""
<div style="display: flex; flex-wrap: wrap; gap: 10px; align-items: center;">
<!-- Paper icon with custom link -->
<a href="{paper_link}" target="_blank">
πŸ“‘ Paper
</a>
<span style="margin: 0 10px;">|</span>
<span style="font-weight: bold;">MODELS:</span> {model_num}
<span style="margin: 0 10px;">|</span>
<span style="font-weight: bold;">UPDATED:</span> {"3-15"}
</div>
"""
#TODO
INTRODUCE_BENCHMARK = f"""
<details style="margin: 10px 0; padding: 10px;">
<summary style="cursor: pointer; font-size: 18px; color: #2c3e50; font-weight: bold; transition: color 0.3s;">
πŸ’¬ Metric Explanations
</summary>
<div style="color: #2c3e50; border-left: 4px solid #2980b9; padding-left: 12px; margin-top: 8px;">
<p>
<strong>CapArena-Auto</strong> is an arena-style automated evaluation benchmark for detailed captioning.
It includes <strong>600 evaluation images</strong> and assesses model performance through
<em>pairwise battles</em> with three baseline models. The final score is calculated by <strong>GPT4o-as-a-Judge</strong>.
</p>
</div>
</details>
"""
#TODO About
LLM_BENCHMARKS_TEXT = f"""
<div style="text-align: center; margin: 20px;">
<h2 style="color: #2c3e50; font-family: Arial, sans-serif;"> See details in
<a href="https://github.com/njucckevin/CapArena" target="_blank"
style="color: #2980b9; text-decoration: none; font-weight: bold;">
CapArena
</a>
</h2>
</div>
"""
EVALUATION_QUEUE_TEXT = """
"""
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
CITATION_BUTTON_TEXT = r"""
"""