Update README.md

README.md

@@ -1,17 +1,17 @@
----
-license: other
-license_name: server-side-public-license
-license_link: https://www.mongodb.com/licensing/server-side-public-license
-task_categories:
-- object-detection
-- image-segmentation
-tags:
-- fashion
-- e-commerce
-- apparel
-size_categories:
-- 1K<n<10K
----
+---
+license: other
+license_name: server-side-public-license
+license_link: https://www.mongodb.com/licensing/server-side-public-license
+task_categories:
+- object-detection
+- image-segmentation
+tags:
+- fashion
+- e-commerce
+- apparel
+size_categories:
+- 1K<n<10K
+---
 
 # FashionFail Dataset
 
@@ -20,6 +20,9 @@ The FashionFail dataset, proposed in the paper ["FashionFail: Addressing Failure
 comprises 2,495 high-resolution images (2400x2400 pixels) of products found on e-commerce websites. The dataset is divided into training, validation, and test sets, consisting of 1,344, 150, and 1,001 images, respectively.
 
 
+> Note: The annotations are **automatically** generated by foundation models. However, a human annotator reviewed each sample to ensure the accuracy of the annotations.
+
+
 ### Download Dataset
 To address concerns regarding data regulations, we share only the URLs of the images, rather than sharing the image files directly.
 However, we provide a simple script to facilitate dataset construction. 
@@ -37,8 +40,7 @@ Then, execute the following script:
 python fashionfail/data/make_dataset.py
 ```
 which constructs the dataset inside `"~/.cache/fashionfail/"`. 
-An optional argument `--save_dir` can be set to construct the dataset in the preferred directory, but 
-it is not recommended to alter the default location.
+An optional argument `--save_dir` can be set to construct the dataset in the preferred directory.
 
 ### Annotation format