Update README.md

README.md

@@ -48,60 +48,24 @@ VisualSimpleQA is a multimodal fact-seeking benchmark with two key features. Fir
 Experiments on 15 LVLMs show that even state-of-the-art models such as GPT-4o achieve merely 60%+ correctness in multimodal fact-seeking QA on VisualSimpleQA and 30%+ on VisualSimpleQA-hard.
 Furthermore, the decoupled evaluation based on this benchmark across different models highlights substantial opportunities for improvement in both visual and linguistic modules.
 
-## Structure
-
-`original_image/`
-This directory contains all image files, where each filename follows the format `original_image_{ID}.png`, matching the unique ID of the corresponding sample in VisualSimpleQA.
-
-`cropped_image/`
-This directory contains all cropped rationales from the original images. Each filename follows the format `cropped_image_{ID}.painting`, matching the unique ID of the corresponding sample in VisualSimpleQA.
-
-`data.json`
-This JSON file provides detailed information about each sample.
-
-`hard_data.json`
-This JSON file provides detailed information about each hard sample in the following format:
-
-**Example:**
-```json
-  {
-    "id": 369,
-    "multimodal_question": "Which institution did the creator of this cartoon duck donate her natural science-related paintings to?",
-    "answer": "The Armitt Museum, Gallery, Library",
-    "rationale": "Jemima Puddle-Duck",
-    "text_only_question": "Which institution did the creator of Jemima Puddle-Duck donate her natural science-related paintings to?",
-    "image_source": "https://www.gutenberg.org/files/14814/14814-h/images/15-tb.jpg",
-    "evidence": "https://www.armitt.com/beatrix-potter-exhibition/\nhttps://en.wikipedia.org/wiki/Beatrix_Potter",
-    "resolution": "400x360",
-    "proportion_of_roi": 0.2232,
-    "category": "academic and education",
-    "text_in_image": "absence",
-    "rationale_granularity": "fine-grained"
-  }
+**Data Example:**
 ```
-
-
-
-## Usage
-1. Ensure the `data.json` file is in the same directory as the script.
-2. Run the script to randomly select and display a sample.
-
-```python
-import json
-import random
-
-with open('./data.json', 'r', encoding='utf-8') as file:
-    data = json.load(file)
-
-# Randomly select one sample
-random_sample = random.choice(data)
-image_id = random_sample.get('id')
-image_path = f'./original_image/original_image_{image_id}.png'
-multimodal_question = random_sample.get('multimodal_question')
-text_only_question = random_sample.get('text_only_question')
-answer = random_sample.get('answer')
+  {'id': 369,
+   'multimodal_question': 'Which institution did the creator of this cartoon duck donate her natural science-related paintings to?',
+   'answer': 'The Armitt Museum, Gallery, Library', 'rationale': 'Jemima Puddle-Duck',
+   'text_only_question': 'Which institution did the creator of Jemima Puddle-Duck donate her natural science-related paintings to?',
+   'image_source': 'https://www.gutenberg.org/files/14814/14814-h/images/15-tb.jpg',
+   'evidence': 'https://www.armitt.com/beatrix-potter-exhibition/\nhttps://en.wikipedia.org/wiki/Beatrix_Potter',
+   'resolution': '400x360',
+   'proportion_of_roi': '0.2232',
+   'category': 'research and education',
+   'text_in_image': 'absence',
+   'rationale_granularity': 'fine-grained',
+   'image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=400x360 at 0x7FE82C270D70>,
+   'cropped_image': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=164x196 at 0x7FE82C329550>}
 ```
 
+
 ## Disclaimer
 
 This dataset contains images collected from various sources. The authors do NOT claim ownership or copyright over the images. The images may be subject to third-party rights, and users are solely responsible for verifying the legal status of any content before use.