Add dataset card for OpenSDI: Spotting Diffusion-Generated Images (#2)

- Add dataset card for OpenSDI: Spotting Diffusion-Generated Images (0de72759abcdbf7dbe7e60d9ee38440f798bc793)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,47 +1,40 @@
 ---
-dataset_info:
-  features:
-  - name: key
-    dtype: string
-  - name: image
-    dtype: image
-  - name: mask
-    dtype: image
-  - name: label
-    dtype:
-      class_label:
-        names:
-          '0': real
-          '1': fake
-  splits:
-  - name: sd15
-    num_bytes: 9360582700.0
-    num_examples: 20000
-  - name: sd3
-    num_bytes: 4644105100.0
-    num_examples: 20000
-  - name: sd2
-    num_bytes: 3270806600.0
-    num_examples: 20000
-  - name: sdxl
-    num_bytes: 4185546140.0
-    num_examples: 20000
-  - name: flux
-    num_bytes: 3353782220.0
-    num_examples: 20000
-  download_size: 18266080332
-  dataset_size: 24814822760.0
-configs:
-- config_name: default
-  data_files:
-  - split: sd15
-    path: data/sd15-*
-  - split: sd3
-    path: data/sd3-*
-  - split: sd2
-    path: data/sd2-*
-  - split: sdxl
-    path: data/sdxl-*
-  - split: flux
-    path: data/flux-*
+license: cc-by-sa-4.0
+task_categories:
+- image-classification
+tags:
+- diffusion
+- image-generation
+- ai-generated-content
 ---
+
+# OpenSDI: Spotting Diffusion-Generated Images in the Open World
+
+This dataset is designed to address the **OpenSDI challenge**: spotting diffusion-generated images in realistic, open-world scenarios. It is described in the paper: [](https://huggingface.co/papers/2503.19653)
+
+**Project Page:** [https://iamwangyabin.github.io/OpenSDI/](https://iamwangyabin.github.io/OpenSDI/)
+
+**OpenSDID Dataset Highlights:**
+
+*   **User Diversity:** Simulates a wide range of user intentions and creative styles using diverse text prompts generated by VLMs.
+*   **Model Innovation:** Includes images from multiple state-of-the-art diffusion models (SD1.5, SD2.1, SDXL, SD3, Flux.1) released after 2023.
+*   **Manipulation Scope:** Covers the full spectrum of diffusion-based manipulation, from global image synthesis to precise local edits, object insertions, and background changes.
+
+**Dataset Overview:**
+
+| Model   | Training Set |          | Test Set |          | Total  |
+| :------ | :----------- | :------- | :------- | :------- | :----- |
+|         | Real         | Fake     | Real     | Fake     | Images |
+| SD1.5   | 100K         | 100K     | 10K      | 10K      | 220K   |
+| SD2.1   | -            | -        | 10K      | 10K      | 20K    |
+| SDXL    | -            | -        | 10K      | 10K      | 20K    |
+| SD3     | -            | -        | 10K      | 10K      | 20K    |
+| Flux.1  | -            | -        | 10K      | 10K      | 20K    |
+| **Total** | **100K**   | **100K** | **50K**  | **50K**  | **300K** |
+
+**Download:**
+
+*   **OpenSDI Training Dataset:** [https://huggingface.co/datasets/nebula/OpenSDI_train](https://huggingface.co/datasets/nebula/OpenSDI_train)
+*   **OpenSDI Testing Dataset:** This repository
+
+This dataset is for academic use and is distributed under the [CC BY-SA 4.0 license](https://creativecommons.org/licenses/by-sa/4.0/). Real images come from [megalith-10m](https://huggingface.co/datasets/madebyollin/megalith-10m).