Update README.md

README.md

@@ -23,16 +23,16 @@ configs:
 ---
 
 # WAON-Bench: Japanese Cultural Image Classification Dataset
-WAON-Bench is a small-scale, manually curated image classification dataset designed to benchmark Vision-Language models on the visual understanding of Japanese culture.
-It consists of 385 images, each corresponding to a distinct class, capturing a wide range of cultural, natural, and everyday elements of Japanese life.
+WAON-Bench is a manually curated image classification dataset designed to benchmark Vision-Language models on visual understanding of Japanese culture.
+It comprises 374 classes, each containing 5 images, covering a diverse range of cultural, natural, and everyday aspects of Japanese life.
 
 
 ## Data Collection Pipeline
 We followed the pipeline below to construct the dataset:
 
-1. **Class Definition**: A total of 385 class names were manually defined and grouped into eight top-level categories:
+1. **Class Definition**: A total of 374 class names were manually defined and grouped into eight top-level categories:
 animal, building, event, everyday, food, nature, scenery, and tradition.
-2. **Image Selection**: For each class, a representative image was manually retrieved using Google Image Search. \
+2. **Image Selection**: For each class, 5 images were manually retrieved using Google Image Search. \
 Images were selected based on the following criteria:
     - The image should clearly represent the intended class.
     - It should not contain elements that could be easily confused with other classes.
@@ -47,7 +47,7 @@ Each sample includes:
 
 Example:
 ```
-{'class': '柴犬', 'url': 'https://www.woodtec.co.jp/products/lineup/flooring/fordog/wp/wp-content/uploads/2024/12/67-1-1024x683.jpg', 'category': 'animal', 'jpg': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=1024x683 at 0x7FC03F469700>}
+{'class': '柴犬', 'url': 'https://img.wanqol.com/2020/11/6e489894-main.jpg?auto=format', 'category': 'animal', 'jpg': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=1440x1000 at 0x7F8FA9E10170>}
 ```
 
 ## Statistics
@@ -55,21 +55,21 @@ Example:
 - **Class num per category**
 | **class** | animal | building | event | everyday | food | nature | scenery | tradition | total |
 |----------:|-------:|---------:|------:|---------:|-----:|-------:|--------:|----------:|------:|
-| **count** |     41 |       39 |    30 |       34 |   55 |     26 |      85 |        75 |   385 |
+| **count** |     41 |       40 |    29 |       45 |   55 |     27 |      75 |        62 |   374 |
 
 
 
 - **Example Class Names per Category**
 |category | class names|   
 |:-----------|--------:|
-| animal   | '柴犬', 'エゾシカ', 'ニホンカモシカ', 'イノシシ', 'タヌキ', ...|
-| building | '鳥居', '茶室', '合掌造り', '町家', '和室', '縁側', ...|
+| animal   | '柴犬', 'エゾシカ', 'ニホンカモシカ', 'イノシシ', ...|
+| building | '鳥居', '茶室', '合掌造り', '町家', '縁側', ...|
 | event    | '花見', '花火大会', '盆踊り', '運動会', '卒業式', '成人式', ...|
-| everyday | 'カラオケ', '温泉', '屋台', '洗濯物', 'ランドセル', ...|
-| food     | '茄子', 'しらす', 'ラーメン', '焼き鳥', '焼肉', '白米', '弁当', 'カレーライス', ...|
-| nature   | '桜', '梅', '藤', '牡丹', 'つばき', 'アサガオ', 'アジサイ', '噴火', ...|
-| scenery  | '茶畑', '雪国の街並み', '漁港', '砂防ダム', '石垣', '自動販売機', ...|
-| tradition| '華道', '書道', '剣道', '柔道', '弓道', ...|
+| everyday | 'カラオケ', '温泉', '屋台', '洗濯物', '敷布団', ...|
+| food     | '茄子', 'しらす', 'ラーメン', '焼き鳥', '焼肉', ...|
+| nature   | '桜', '梅', '藤', '松, '噴火', ...|
+| scenery  | '茶畑', '雪国の街並み', '漁港', '砂防ダム', '石垣', ...|
+| tradition| '華道', 剣道', '柔道', '弓道', ...|