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@@ -272,17 +272,6 @@ PhysInOne is divided into <strong>Train, Val, and Test</strong> splits, containi
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  <h2 id="how-to-download" style="margin-left: 0; font-size: 1.9em; line-height: 1.22; margin-top: 1.2em; margin-bottom: 0.5em;">📥 How to Download</h2>
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- <div style="margin-left: 24px;">
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- <p style="text-align: justify;">
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- PhysInOne is distributed across multiple Hugging Face dataset repositories because of its large scale. We provide two scripts for selecting and downloading cases:
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- - `filter_cases.py`: parses the case-to-repository assignment file and exports selected cases to JSON.
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- - `download.py`: downloads the selected case zip files from the corresponding Hugging Face shard repositories.
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- </p>
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- </div>
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  <h3 id="download-scripts" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;">1. Download Scripts</h3>
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  <div style="margin-left: 40px;">
@@ -300,6 +289,17 @@ scripts/
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  </div>
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  <h3 id="install-dependencies" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;">2. Install Dependencies</h3>
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  Export a JSON file containing case information matching your filter criteria, for use in subsequent download scripts. The `filter_cases.py` script supports selection by:
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  - Split: `train`, `val`, `test`
@@ -322,6 +323,7 @@ Export a JSON file containing case information matching your filter criteria, fo
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  - Number of cases: globally sample `num` cases after filtering
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  The following examples show common filtering workflows.
 
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  </div>
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  <h2 id="how-to-download" style="margin-left: 0; font-size: 1.9em; line-height: 1.22; margin-top: 1.2em; margin-bottom: 0.5em;">📥 How to Download</h2>
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  <h3 id="download-scripts" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;">1. Download Scripts</h3>
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  <div style="margin-left: 40px;">
 
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  </div>
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+ <div style="margin-left: 24px;">
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+
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+ <p style="text-align: justify;">
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+ PhysInOne is distributed across multiple Hugging Face dataset repositories because of its large scale. We provide two scripts for selecting and downloading cases:
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+
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+ - `filter_cases.py`: parses the case-to-repository assignment file and exports selected cases to JSON.
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+ - `download.py`: downloads the selected case zip files from the corresponding Hugging Face shard repositories.
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+ </p>
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+
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+ </div>
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+
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  <h3 id="install-dependencies" style="font-size: 1.35em; margin-top: 0.75em; margin-bottom: 0.22em; line-height: 1.2; margin-left: 24px;">2. Install Dependencies</h3>
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  <div style="margin-left: 40px;">
 
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  <div style="margin-left: 40px;">
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+ <p style="text-align: justify;">
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  Export a JSON file containing case information matching your filter criteria, for use in subsequent download scripts. The `filter_cases.py` script supports selection by:
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  - Split: `train`, `val`, `test`
 
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  - Number of cases: globally sample `num` cases after filtering
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  The following examples show common filtering workflows.
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+ </p>
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  </div>
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