Update dataset card w/ data struct info

README.md

@@ -5,13 +5,63 @@ size_categories:
 - 10K<n<100K
 ---
 
-This is the evaluation sample of Semi-Truths dataset. Semi-Truths contains AI-augmented images featuring varying degrees of targeted and localized edits, created using diverse augmentation methods, diffusion models, and data distributions.
-This resource was created for the targeted evaluation of AI-genertaed image detectors.
+# Semi-Truths: The Evaluation Sample #
 
-The structure of the uploaded data is as follows:
- - The original image data is in the folder `original`
- - Inpainting augmented images are in the folder `inpainting`
+<!-- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/666454f1f99defe86aca3882/AaKKr-VDqcsml4sDcYLrh.png) -->
+<centering><img src="https://cdn-uploads.huggingface.co/production/uploads/666454f1f99defe86aca3882/AaKKr-VDqcsml4sDcYLrh.png" alt="head_figure" width="800"/></centering>
+
+
+**Recent efforts have developed AI-generated image detectors claiming robustness against various augmentations, but their effectiveness remains unclear. Can these systems detect varying degrees of augmentation?**
+To address these questions, we introduce **Semi-Truths**, featuring 27,600 real images, 245,300 masks, and 850,200 AI-augmented images featuring varying degrees of targeted and localized edits, created using diverse augmentation methods, diffusion models, and data distributions. 
+Each augmented image includes detailed metadata for standardized, targeted evaluation of detector robustness. 
+
+🚀 Leverage the Semi-Truths dataset to understand the sensitivities of the latest AI-augmented image detectors, to various sizes of edits and semantic changes!
+
+<!-- ## Loading Dataset ##
+
+```
+from datasets import load_dataset
+dataset = load_dataset('hoffman-lab/SkyScenes',name="H_35_P_45 images")
+``` -->
+
+## Dataset Structure ##
+
+The general structure of the Semi-Truths Dataset is as follows:
+ - The original, real image and mask data can be found in the folder `original`
+ - Augmented images created with Diffusion Inpainting are in `inpainting`
  - Prompt-edited images are in the folder `p2p`
  - Prompt-edited image masks, computed post-augmentation, are in the folder `p2p_masks`
  - All metadata can be found in `metadata.csv`, including labels, datasets, entities, augmentation methods, diffusion models, change metrics, and so on.
- - Data has been uploaded in 3 tar files.
+
+```
+├── metadata.csv (Image, Mask, and Change Information)
+├── original (Real Images/Mask Pairs)
+│   ├── images
+│   │   ├── ADE20K
+│   │   ├── CelebAHQ
+│   │   ├── CityScapes
+│   │   ├── HumanParsing
+│   │   ├── OpenImages
+│   │   └── SUN_RGBD
+│   └── masks
+│       ├── ADE20K
+│       ├── CelebAHQ
+│       ├── CityScapes
+│       ├── HumanParsing
+│       ├── OpenImages
+│       └── SUN_RGBD
+├── inpainting (Augmented Images)
+│   ├── ADE20K
+│   ├── CelebAHQ
+│   ├── CityScapes
+│   ├── HumanParsing
+│   ├── OpenImages
+│   └── SUN_RGBD
+└── p2p (Augmented Images)
+    ├── ADE20K
+    ├── CelebAHQ
+    ├── CityScapes
+    ├── HumanParsing
+    ├── OpenImages
+    └── SUN_RGBD
+```