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  ## 📂 Dataset Structure
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  ```
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-
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- visual-equation-solving/
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-
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- ├── train/
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- ├── images/ # equation images
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- ├── annotations.json # ground-truth equations & solutions
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-
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- ├── test/
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- ├── images/
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- ├── annotations.json
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-
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- └── metadata.json # dataset metadata & icon mapping
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-
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ````
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  **Annotations** include:
 
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  ## 📂 Dataset Structure
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  ```
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+ There are 2 variants of the dataset based on number of variables used -
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+ 2 variables and 3 variables which can be found in the respective zip files.
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+ Once you extract any of them you will see the following tree -
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+
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+ ├── char_only
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+ └── metadata.csv
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+ └── *.png
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+ ├── counting
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+ └── metadata.csv
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+ └── *.png
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+ ├── icon_only
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+ └── metadata.csv
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+ │ └── *.png
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+ ├── icon_partial
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+ │ └── metadata.csv
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+ │ └── *.png
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+ └── [two/three]-vars.txt
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+
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+ The char_only, icon_only, icon_partial, counting points to the
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+ symbolic, visual, visual-symbolic and counting datasets mentioned in the paper
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+ respectively. Each of them consist of the following metadata -
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+ 1. file_path to corresponding image
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+ 2. solution to variable
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+ 3. mapping to symbolic variable (in case of visual, visual-symbolic, counting dataset)
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+
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+ The base equations which are used to create the same are attached in the respective .txt file in the root level directory.
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  ````
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  **Annotations** include: