Rename model to Image2SceneGraph
Browse files- ANNOTATION_GUIDE.md +1 -1
- README.md +3 -3
- SHA256SUMS +4 -4
- assets/sources.json +1 -1
- scene_graph.schema.json +1 -1
ANNOTATION_GUIDE.md
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@@ -40,4 +40,4 @@ The [included training example](examples/README.md) contains the exact image, gr
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Annotations are model-produced and `human_gold` is false. Schema and identity checks establish structural consistency; they do not establish the correctness of every recognized value, box, group, or visual claim in the source image.
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Annotations are model-produced and `human_gold` is false. Schema and identity checks establish structural consistency; they do not establish the correctness of every recognized value, box, group, or visual claim in the source image.
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Image2SceneGraph's native predictions use a different layout field and box order. Consult the model's output-format guide before comparing a prediction to this dataset.
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README.md
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<p align="center"><strong>A Richly Annotated Dataset for Chart Understanding and Generation</strong></p>
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<p align="center"><a href="https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus">Project</a> · <a href="https://huggingface.co/ChartGalaxyPP/ChartGalaxyPlusPlus-
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**ChartGalaxy++ connects what is in an infographic chart with how it is organized.** Each chart is paired with a scene graph: visual elements and semantic groups form the nodes, while hierarchical and spatial relationships connect them. These annotations support chart structure prediction, visual question answering, and evaluation of image generation.
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| Application | What the scene graph enables | Released resource |
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| --- | --- | --- |
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| **Image-to-scene-graph prediction** | Recover elements, semantic groups, and chart hierarchy | [
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| **Infographic question answering** | Associate text and marks through explicit groups and relationships | [1,266 questions, reference answers, and original images](https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus/tree/main/applications/qa) |
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| **Scene graph preservation** | Evaluate structural fidelity in generated infographic charts | [11-model benchmark and generated outputs](https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus/tree/main/applications/scene_graph_preservation) |
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See the [project page](https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus#three-applications) for qualitative results and links to all three application packages. Under the paper's evaluation protocol, the released
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## Annotation and release notes
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<p align="center"><strong>A Richly Annotated Dataset for Chart Understanding and Generation</strong></p>
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<p align="center"><a href="https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus">Project</a> · <a href="https://huggingface.co/ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph">Image2SceneGraph model</a> · <a href="https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus/releases/tag/v1.0">Application data</a> · <a href="https://huggingface.co/datasets/ChartGalaxyPP/ChartGalaxyPlusPlus/blob/main/USAGE.md">Loading guide</a></p>
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**ChartGalaxy++ connects what is in an infographic chart with how it is organized.** Each chart is paired with a scene graph: visual elements and semantic groups form the nodes, while hierarchical and spatial relationships connect them. These annotations support chart structure prediction, visual question answering, and evaluation of image generation.
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| Application | What the scene graph enables | Released resource |
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| --- | --- | --- |
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| **Image-to-scene-graph prediction** | Recover elements, semantic groups, and chart hierarchy | [Image2SceneGraph model](https://huggingface.co/ChartGalaxyPP/ChartGalaxyPlusPlus-Image2SceneGraph); [1,000-chart benchmark](https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus/tree/main/applications/image_to_scene_graph) |
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| **Infographic question answering** | Associate text and marks through explicit groups and relationships | [1,266 questions, reference answers, and original images](https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus/tree/main/applications/qa) |
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| **Scene graph preservation** | Evaluate structural fidelity in generated infographic charts | [11-model benchmark and generated outputs](https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus/tree/main/applications/scene_graph_preservation) |
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See the [project page](https://github.com/ChartGalaxyPP/ChartGalaxyPlusPlus#three-applications) for qualitative results and links to all three application packages. Under the paper's evaluation protocol, the released Image2SceneGraph model achieves **89.4% node F1, 85.1% hierarchy F1, and 88.0% spatial F1**.
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## Annotation and release notes
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577accb542221312b19cc79ecace9f5004ee51eb59acd1da2ab9699089463624 .gitattributes
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81c88405668ceb8b2aba512be68db631e75a509cdfcd0267fa6e143680a97e50 LICENSE_AND_SOURCES.md
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assets/sources.json
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"node_ids": "Illustrative IDs from the paper figure; not a claim of released sample identifiers."
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},
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"paper_figures": {
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"generation-results.png": "Qualitative scene graph preservation comparison (paper figure)."
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"node_ids": "Illustrative IDs from the paper figure; not a claim of released sample identifiers."
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"paper_figures": {
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"image2scenegraph-results.png": "Qualitative comparison of image-to-scene-graph predictions (paper figure).",
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"generation-results.png": "Qualitative scene graph preservation comparison (paper figure)."
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}
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}
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scene_graph.schema.json
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