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generate_seperate_html_from_csv_backup.py
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import pandas as pd
def generate_leaderboard_html_mimiccxr(test_csv_path, valid_csv_path, output_path):
# 读取CSV文件
df_test = pd.read_csv(test_csv_path)
df_valid = pd.read_csv(valid_csv_path)
# HTML开头部分
html_string = '''
<div class="col-md-12">
<div class="infoCard">
<div class="infoBody">
<div class="infoHeadline">
<h2>Leaderboard on MIMIC-CXR Dataset</h2>
</div>
<div><p> <a class="link" href="https://physionet.org/content/mimic-cxr/2.0.0/">MIMIC-CXR </a> contains 377,110 images corresponding to 227,835 radiographic studies performed at the Beth Israel Deaconess Medical Center in Boston, MA. We follow the official split of MIMIC-CXR in the following experiments. * denotes the model was trained on this dataset.</p>
</div>
<div>
<button id="testBtnMIMIC" class="btn btn-black">Findings</button>
<button id="validBtnMIMIC" class="btn btn-gray">Findings + Impression</button>
</div>
<table class="table performanceTable tablesorter" id="modelTableTest">
<thead>
<tr>
<th>Rank</th>
<th>Model</th>
<th>RadCliQ-v1 <b>↓</b></th>
<th>RadCliQ-v0 <b>↓</b></th>
<th>BLEU <b>↑</b></th>
<th>BertScore <b>↑</b></th>
<th>SembScore <b>↑</b></th>
<th>RadGraph <b>↑</b></th>
<th>RaTEScore <b>↑</b></th>
<th>GREEN <b>↑</b></th>
</tr>
</thead>
<tbody id="testResultsMIMIC">
'''
# 生成测试集表格内容
for _, row in df_test.iterrows():
html_string += f'''
<tr>
<td>
<p>{row['Rank']}</p>
<span class="date label label-default">{row['Date']}</span>
</td>
<td style="word-break:break-word;">
<a class="link" href="{row['Model URL']}">{row['Model Name']}</a>
<p class="institution">{row['Institution']}</p>
</td>
<td><b>{row['RadCliQ-v1']}</b></td>
<td><b>{row['RadCliQ-v0']}</b></td>
<td><b>{row['BLEU']}</b></td>
<td><b>{row['BertScore']}</b></td>
<td><b>{row['SembScore']}</b></td>
<td><b>{row['RadGraph']}</b></td>
<td><b>{row['RaTEScore']}</b></td>
<td><b>{row['GREEN']}</b></td>
</tr>
'''
html_string += '''
</tbody>
<tbody id="validResultsMIMIC" style="display: none;">
'''
# 生成验证集表格内容
for _, row in df_valid.iterrows():
html_string += f'''
<tr>
<td>
<p>{row['Rank']}</p>
<span class="date label label-default">{row['Date']}</span>
</td>
<td style="word-break:break-word;">
<a class="link" href="{row['Model URL']}">{row['Model Name']}</a>
<p class="institution">{row['Institution']}</p>
</td>
<td><b>{row['RadCliQ-v1']}</b></td>
<td><b>{row['RadCliQ-v0']}</b></td>
<td><b>{row['BLEU']}</b></td>
<td><b>{row['BertScore']}</b></td>
<td><b>{row['SembScore']}</b></td>
<td><b>{row['RadGraph']}</b></td>
<td><b>{row['RaTEScore']}</b></td>
<td><b>{row['GREEN']}</b></td>
</tr>
'''
# HTML结尾部分
html_string += '''
</tbody>
</table>
</div>
</div>
</div>
'''
# 写入HTML文件
with open(output_path, 'w') as file:
file.write(html_string)
def generate_leaderboard_html_gradienthealth(test_csv_path, valid_csv_path, output_path):
# 读取CSV文件
df_test = pd.read_csv(test_csv_path)
df_valid = pd.read_csv(valid_csv_path)
# HTML开头部分
html_string = '''
<div class="col-md-12">
<div class="infoCard">
<div class="infoBody">
<div class="infoHeadline">
<h2>Leaderboard on Private Dataset</h2>
</div>
<div>
<p> ReXGradient is a large-scale private test dataset contains 10,000 studies collected from different medical centers in the US. </p>
</div>
<div style="margin-top: 5px;">
<button id="testBtnPrivate" class="btn btn-black">Findings</button>
<button id="validBtnPrivate" class="btn btn-gray">Findings + Impression</button>
</div>
<table class="table performanceTable tablesorter" id="modelTablePrivate">
<thead>
<tr>
<th>Rank</th>
<th>Model</th>
<th>RadCliQ-v1 <b>↓</b></th>
<th>RadCliQ-v0 <b>↓</b></th>
<th>BLEU <b>↑</b></th>
<th>BertScore <b>↑</b></th>
<th>SembScore <b>↑</b></th>
<th>RadGraph <b>↑</b></th>
<th>RaTEScore <b>↑</b></th>
<th>GREEN <b>↑</b></th>
</tr>
</thead>
<tbody id="testResultsPrivate">
'''
# 生成表格内容
for _, row in df_test.iterrows():
html_string += f'''
<tr>
<td>
<p>{row['Rank']}</p>
<span class="date label label-default">{row['Date']}</span>
</td>
<td style="word-break:break-word;">
<a class="link" href="{row['Model URL']}">{row['Model Name']}</a>
<p class="institution">{row['Institution']}</p>
</td>
<td><b>{row['RadCliQ-v1']}</b></td>
<td><b>{row['RadCliQ-v0']}</b></td>
<td><b>{row['BLEU']}</b></td>
<td><b>{row['BertScore']}</b></td>
<td><b>{row['SembScore']}</b></td>
<td><b>{row['RadGraph']}</b></td>
<td><b>{row['RaTEScore']}</b></td>
<td><b>{row['GREEN']}</b></td>
</tr>
'''
html_string += '''
</tbody>
<tbody id="validResultsPrivate" style="display: none;">
'''
for _, row in df_valid.iterrows():
html_string += f'''
<tr>
<td>
<p>{row['Rank']}</p>
<span class="date label label-default">{row['Date']}</span>
</td>
<td style="word-break:break-word;">
<a class="link" href="{row['Model URL']}">{row['Model Name']}</a>
<p class="institution">{row['Institution']}</p>
</td>
<td><b>{row['RadCliQ-v1']}</b></td>
<td><b>{row['RadCliQ-v0']}</b></td>
<td><b>{row['BLEU']}</b></td>
<td><b>{row['BertScore']}</b></td>
<td><b>{row['SembScore']}</b></td>
<td><b>{row['RadGraph']}</b></td>
<td><b>{row['RaTEScore']}</b></td>
<td><b>{row['GREEN']}</b></td>
</tr>
'''
# HTML结尾部分
html_string += '''
</tbody>
</table>
</div>
</div>
</div>
'''
# 写入HTML文件
with open(output_path, 'w') as file:
file.write(html_string)
def generate_leaderboard_html_chexpertplus(test_csv_path, valid_csv_path, output_path):
# 读取CSV文件
df_test = pd.read_csv(test_csv_path)
df_valid = pd.read_csv(valid_csv_path)
# HTML开头部分
html_string = '''
<div class="col-md-12">
<div class="infoCard">
<div class="infoBody">
<div class="infoHeadline">
<h2>Leaderboard on CheXpert Plus Dataset</h2>
</div>
<div>
<p> <a class="link" href="https://stanfordaimi.azurewebsites.net/datasets/5158c524-d3ab-4e02-96e9-6ee9efc110a1">CheXpert Plus </a> contains 223,228 unique pairs of radiology reports and chest X-rays from 187,711 studies and 64,725 patients. We follow the official split of CheXpert Plus in the following experiments and use the valid set for evaluation. * denotes the model was trained on CheXpert Plus.</p>
</div>
<div style="margin-top: 5px;">
<button id="testBtnCheXpert" class="btn btn-black">Findings</button>
<button id="validBtnCheXpert" class="btn btn-gray">Findings + Impression</button>
</div>
<table class="table performanceTable tablesorter" id="modelTableCheXpert">
<thead>
<tr>
<th>Rank</th>
<th>Model</th>
<th>RadCliQ-v1 <b>↓</b></th>
<th>RadCliQ-v0 <b>↓</b></th>
<th>BLEU <b>↑</b></th>
<th>BertScore <b>↑</b></th>
<th>SembScore <b>↑</b></th>
<th>RadGraph <b>↑</b></th>
<th>RaTEScore <b>↑</b></th>
<th>GREEN <b>↑</b></th>
</tr>
</thead>
<tbody id="testResultsCheXpert">
'''
# 生成表格内容
for _, row in df_test.iterrows():
html_string += f'''
<tr>
<td>
<p>{row['Rank']}</p>
<span class="date label label-default">{row['Date']}</span>
</td>
<td style="word-break:break-word;">
<a class="link" href="{row['Model URL']}">{row['Model Name']}</a>
<p class="institution">{row['Institution']}</p>
</td>
<td><b>{row['RadCliQ-v1']}</b></td>
<td><b>{row['RadCliQ-v0']}</b></td>
<td><b>{row['BLEU']}</b></td>
<td><b>{row['BertScore']}</b></td>
<td><b>{row['SembScore']}</b></td>
<td><b>{row['RadGraph']}</b></td>
<td><b>{row['RaTEScore']}</b></td>
<td><b>{row['GREEN']}</b></td>
</tr>
'''
html_string += '''
</tbody>
<tbody id="validResultsCheXpert" style="display: none;">
'''
# 生成验证集表格内容
for _, row in df_valid.iterrows():
html_string += f'''
<tr>
<td>
<p>{row['Rank']}</p>
<span class="date label label-default">{row['Date']}</span>
</td>
<td style="word-break:break-word;">
<a class="link" href="{row['Model URL']}">{row['Model Name']}</a>
<p class="institution">{row['Institution']}</p>
</td>
<td><b>{row['RadCliQ-v1']}</b></td>
<td><b>{row['RadCliQ-v0']}</b></td>
<td><b>{row['BLEU']}</b></td>
<td><b>{row['BertScore']}</b></td>
<td><b>{row['SembScore']}</b></td>
<td><b>{row['RadGraph']}</b></td>
<td><b>{row['RaTEScore']}</b></td>
<td><b>{row['GREEN']}</b></td>
</tr>
'''
# HTML结尾部分
html_string += '''
</tbody>
</table>
</div>
</div>
</div>
'''
# 写入HTML文件
with open(output_path, 'w') as file:
file.write(html_string)
def generate_leaderboard_html_iu_xray(test_csv_path, valid_csv_path, output_path):
# 读取CSV文件
df_test = pd.read_csv(test_csv_path)
df_valid = pd.read_csv(valid_csv_path)
# HTML开头部分
html_string = '''
<div class="col-md-12">
<div class="infoCard">
<div class="infoBody">
<div class="infoHeadline">
<h2>Leaderboard on IU Xray Dataset</h2>
</div>
<div>
<p> <a class="link" href="https://paperswithcode.com/dataset/iu-x-ray">IU Xray</a> contains 7,470 pairs of radiology reports and chest X-rays from Indiana University. We follow the split given by <a class="link" href="https://github.com/cuhksz-nlp/R2Gen">R2Gen</a>. * denotes the model was trained on IU X-ray.</p>
</div>
<div style="margin-top: 5px;">
<button id="testBtnIU" class="btn btn-black">Findings</button>
<button id="validBtnIU" class="btn btn-gray">Findings + Impression</button>
</div>
<table class="table performanceTable tablesorter" id="modelTableIU">
<thead>
<tr>
<th>Rank</th>
<th>Model</th>
<th>RadCliQ-v1 <b>↓</b></th>
<th>RadCliQ-v0 <b>↓</b></th>
<th>BLEU <b>↑</b></th>
<th>BertScore <b>↑</b></th>
<th>SembScore <b>↑</b></th>
<th>RadGraph <b>↑</b></th>
<th>RaTEScore <b>↑</b></th>
<th>GREEN <b>↑</b></th>
</tr>
</thead>
<tbody id="testResultsIU">
'''
# 生成测试集表格内容
for _, row in df_test.iterrows():
html_string += f'''
<tr>
<td>
<p>{row['Rank']}</p>
<span class="date label label-default">{row['Date']}</span>
</td>
<td style="word-break:break-word;">
<a class="link" href="{row['Model URL']}">{row['Model Name']}</a>
<p class="institution">{row['Institution']}</p>
</td>
<td><b>{row['RadCliQ-v1']}</b></td>
<td><b>{row['RadCliQ-v0']}</b></td>
<td><b>{row['BLEU']}</b></td>
<td><b>{row['BertScore']}</b></td>
<td><b>{row['SembScore']}</b></td>
<td><b>{row['RadGraph']}</b></td>
<td><b>{row['RaTEScore']}</b></td>
<td><b>{row['GREEN']}</b></td>
</tr>
'''
html_string += '''
</tbody>
<tbody id="validResultsIU" style="display: none;">
'''
# 生成验证集表格内容
for _, row in df_valid.iterrows():
html_string += f'''
<tr>
<td>
<p>{row['Rank']}</p>
<span class="date label label-default">{row['Date']}</span>
</td>
<td style="word-break:break-word;">
<a class="link" href="{row['Model URL']}">{row['Model Name']}</a>
<p class="institution">{row['Institution']}</p>
</td>
<td><b>{row['RadCliQ-v1']}</b></td>
<td><b>{row['RadCliQ-v0']}</b></td>
<td><b>{row['BLEU']}</b></td>
<td><b>{row['BertScore']}</b></td>
<td><b>{row['SembScore']}</b></td>
<td><b>{row['RadGraph']}</b></td>
<td><b>{row['RaTEScore']}</b></td>
<td><b>{row['GREEN']}</b></td>
</tr>
'''
# HTML结尾部分
html_string += '''
</tbody>
</table>
</div>
</div>
</div>
'''
# 写入HTML文件
with open(output_path, 'w') as file:
file.write(html_string)
generate_leaderboard_html_iu_xray('./results/findings_result_iu_xray.csv','./results/result_iu_xray.csv','./results/table_iuxray.html')
generate_leaderboard_html_chexpertplus('./results/findings_result_chexpertplus.csv','./results/result_chexpertplus.csv','./results/table_chexpertplus.html')
generate_leaderboard_html_gradienthealth('./results/findings_result_gradienthealth.csv','./results/result_gradienthealth.csv','./results/table_gradienthealth.html')
generate_leaderboard_html_mimiccxr('./results/findings_result_mimiccxr.csv','./results/result_mimiccxr.csv','./results/table_mimiccxr.html')