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README.md

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+---
+license: apache-2.0
+task_categories:
+  - image-to-image
+tags:
+  - image-generation
+  - benchmark
+  - evaluation
+---
+
+# ConceptEdit: Unlocking the Potential of Image Editing via Concept Scaling and Dense Supervision
+
+[![arXiv](https://img.shields.io/badge/ArXiv-2608.16812-b31b1b?logo=arxiv)](https://arxiv.org/abs/2608.16812)  [![GitHub](https://img.shields.io/badge/GitHub-ConceptEdit-181717?logo=github)](https://github.com/inclusionAI/ConceptEdit)  [![Training Dataset](https://img.shields.io/badge/%F0%9F%A4%97%20Dataset-ConceptEdit--12M-yellow)](https://huggingface.co/datasets/inclusionAI/ConceptEdit-12M)  [![Benchmark Dataset](https://img.shields.io/badge/%F0%9F%A4%97%20Benchmark-ConceptEdit--Bench-yellow)](https://huggingface.co/datasets/inclusionAI/ConceptEdit-Bench)
+
+ConceptEdit-Bench is the evaluation benchmark for ConceptEdit. It contains 1,000 curated image editing test cases across 6 major editing categories. Each test case includes a source image and a JSON metadata file with the edit instruction, taxonomy information, and a relative path to the source image.
+
+The benchmark evaluation code is provided in the ConceptEdit GitHub repository:
+
+```text
+https://github.com/inclusionAI/ConceptEdit
+```
+
+## Files
+
+This Hugging Face dataset repository provides the benchmark data package:
+
+```text
+conceptbench_data.tar
+```
+
+The tar file contains one top-level directory:
+
+```text
+data/
+```
+
+## How to extract
+
+Extract the benchmark package with:
+
+```bash
+mkdir -p ConceptEdit-Bench
+
+tar -xf conceptbench_data.tar -C ConceptEdit-Bench
+```
+
+After extraction, the expected layout is:
+
+```text
+ConceptEdit-Bench/
+└── data/
+    ├── taxonomy.json
+    ├── images/
+    │   ├── <image_id>.jpg
+    │   └── ...
+    ├── advanced_domain_application/
+    ├── general_object_editing/
+    ├── generation_composition/
+    ├── global_enhancement_atmosphere/
+    ├── portrait_human_specialized/
+    └── text_graphic_design/
+```
+
+Each benchmark case JSON is stored under the taxonomy hierarchy:
+
+```text
+data/<category>/<sub_category>/<task>/<detail>.json
+```
+
+The source images are stored under:
+
+```text
+data/images/
+```
+
+You can inspect the tar file without extracting it:
+
+```bash
+tar -tf conceptbench_data.tar | head
+```
+
+## Expected data size
+
+| Item | Count |
+|---|---:|
+| Case JSON files | 1,000 |
+| Source images | 979 |
+| Top-level categories | 6 |
+
+Some source images are shared by multiple benchmark cases, so the number of source images is smaller than the number of case JSON files.
+
+## JSON format
+
+Each case JSON keeps only the fields needed for benchmark inference and evaluation:
+
+```json
+{
+  "caption": "source image caption",
+  "edit_concept": {
+    "category": "...",
+    "sub_category": "...",
+    "task": "...",
+    "detail": "..."
+  },
+  "instruction_en": "short English edit instruction",
+  "instruction_zh": "short Chinese edit instruction",
+  "detailed_instruction_en": "detailed English edit instruction",
+  "detailed_instruction_zh": "detailed Chinese edit instruction",
+  "local_image_path": "images/example.jpg"
+}
+```
+
+Field descriptions:
+
+- `caption`: short English caption for the source image.
+- `edit_concept`: taxonomy information for the editing case.
+- `instruction_en` / `instruction_zh`: short English and Chinese edit instructions.
+- `detailed_instruction_en` / `detailed_instruction_zh`: detailed English and Chinese edit instructions.
+- `local_image_path`: relative path to the source image under the extracted `data/` directory.
+
+For example, if a JSON file contains:
+
+```json
+{
+  "local_image_path": "images/example.jpg"
+}
+```
+
+then the corresponding source image should be located at:
+
+```text
+ConceptEdit-Bench/data/images/example.jpg
+```
+
+All paths inside the released JSON files are relative paths. No local absolute paths are included.
+
+## Using with the evaluation code
+
+Clone the ConceptEdit code repository and place the extracted `data/` directory under the benchmark code directory expected by the scripts:
+
+```bash
+git clone https://github.com/inclusionAI/ConceptEdit.git
+cd ConceptEdit/benchmark
+
+# place or symlink the extracted data directory here
+# expected path: ConceptEdit/benchmark/data/
+```
+
+The benchmark scripts read cases from `./data` and use `local_image_path` to find source images.
+
+## Source Image Acknowledgement
+
+The source images in ConceptEdit-12M are based on images from [Fine-T2I](https://huggingface.co/datasets/ma-xu/fine-t2i).
+
+
+## Citation
+
+If you find this benchmark useful, please cite the ConceptEdit paper and refer to the project repository:
+
+```bibtex
+@article{cui2026unlocking,
+  title={Unlocking the Potential of Image Editing via Concept Scaling and Dense Supervision},
+  author={Cui, Long and Liu, Xiaoqian and Qin, Qi and Xin, Yi and Lin, Tao and Li, Jianguo and Zhang, Linfeng},
+  journal={arXiv preprint arXiv:2608.16812},
+  year={2026}
+}
+```
+