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README.md

@@ -1,26 +1,24 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: mask
-    dtype: image
-  - name: image_id
-    dtype: string
-  splits:
-  - name: test
-    num_bytes: 427394822
-    num_examples: 200
-  - name: train
-    num_bytes: 1321626247
-    num_examples: 600
-  download_size: 1749104370
-  dataset_size: 1749021069
-configs:
-- config_name: default
-  data_files:
-  - split: test
-    path: data/test-*
-  - split: train
-    path: data/train-*
+license: cc-by-4.0
 ---
+
+# FIVES
+
+800 high-resolution 2048 × 2048 images with pixel-wise manual annotations from 573 Asian patients aged 4–83, collected 2016–2021 at the Ophthalmology Centre of the Second Affiliated Hospital of Zhejiang University and balanced at 200 images each across normal controls, diabetic retinopathy, age-related macular degeneration and glaucoma. Annotation ran December 2020–June 2021 by 3 senior practitioners and 24 medical staff, each image labeled by two juniors then verified by a senior. Released on figshare 2022-05-01 (CC BY 4.0).
+
+## Classes
+
+| id | name |
+|---|---|
+| 0 | Background (black, non-vessel) |
+| 255 | Vessel (white) |
+
+## License
+
+CC BY 4.0 (https://api.figshare.com/v2/articles/19688169)
+
+## Citation
+
+```
+Jin K, Huang X, Zhou J, Li Y, Yan Y, Sun Y, Zhang Q, Wang Y, Ye J. "FIVES: A Fundus Image Dataset for Artificial Intelligence based Vessel Segmentation." Scientific Data 9, 475 (2022). doi:10.1038/s41597-022-01564-3
+```