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README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+---
+
+# Omni-I2C: Image2Code_Full
+
+## Dataset Description
+
+`Image2Code_Full.tsv` is the inference split of the **Omni-I2C** benchmark. It is designed to evaluate whether multimodal models can generate high-fidelity code or structured outputs from input images.
+
+Each sample contains an image, an instruction, and metadata describing the target task. The goal is to generate code or a structured string that can reproduce the original figure as accurately as possible.
+
+- **Number of samples:** 1,080
+- **Number of subjects:** 8
+- **Number of figure types:** 45
+- **Number of code types:** 5
+
+Project repository: [Omni-I2C on GitHub](https://github.com/MiliLab/Omni-I2C)
+
+## Data Fields
+
+The dataset is stored as a 7-column TSV file with the following header:
+
+```tsv
+index	image	question	answer	subject	figure_type	code_type
+````
+
+| Field         | Description                                                                     |
+| ------------- | ------------------------------------------------------------------------------- |
+| `index`       | Unique sample identifier.                                                       |
+| `image`       | Input image stored as a base64-encoded string.                                  |
+| `question`    | Instruction text for the generation task.                                       |
+| `answer`      | Filename of the ground-truth reference file. This is not the full code content. |
+| `subject`     | Subject or application domain.                                                  |
+| `figure_type` | Fine-grained figure category.                                                   |
+| `code_type`   | Target output format or code type.                                              |
+
+## Task Description
+
+This is an **image-to-code** inference dataset. Given an input image and an instruction, the model is expected to generate an executable, renderable, or otherwise structured output that reconstructs the original figure.
+
+The `answer` field links each sample to its corresponding ground-truth file used in evaluation.
+
+## Supported Code Types
+
+```text
+python
+html-css
+latex-tikz
+svg
+smiles
+```
+
+### Sample Counts by Code Type
+
+| code_type    | Count | Extension |
+| ------------ | ----: | --------- |
+| `python`     |   357 | `.py`     |
+| `latex-tikz` |   265 | `.tex`    |
+| `svg`        |   192 | `.svg`    |
+| `html-css`   |   166 | `.html`   |
+| `smiles`     |   100 | `.smi`    |
+
+## Subjects
+
+```text
+Biology&Medicine
+Chemistry
+Computer Science
+Economics
+Geography
+Math
+Other
+Physics
+```
+
+## Figure Types
+
+This split includes 45 figure types, including but not limited to:
+
+```text
+3d-plot, Area, Contour, Density, Graph, Histogram, Phase-Diagram,
+Quiver, Treemap, UML-class-diagram, Violin, analytical-geometry,
+anatomy-diagram, atom-model, bar-chart, block-diagram, box-chart,
+cell-structure, circuit, equations-texts, error-bar, error-point,
+flow-chart, free-body-diagram, function-related, gauge-chart, graph,
+heatmap, line-graph, magnetic-field-line, map, molecular-formula,
+multi-graph, optics-ray-diagram, other-figures, physiological-process,
+pie-chart, plane-geometry, radar-chart, relationship-diagram,
+scatter-plot, schematic, solid-geometry, tables, venn-diagram
+```
+
+## Usage
+
+Within the Omni-I2C project, this file is used as the inference input to the evaluation pipeline:
+
+1. `VLMEvalKit_infer` loads `Image2Code_Full.tsv`
+2. The model takes `image` and `question` as input
+3. Predictions are saved after inference
+4. `eval_pipeline` matches predictions with GT files for code-level and image-level evaluation
+
+For implementation details, please refer to the project repository: [https://github.com/MiliLab/Omni-I2C](https://github.com/MiliLab/Omni-I2C)
+
+