Duplicate from umd-zhou-lab/ColorBench

Co-authored-by: Tianyi Zhou <zhoutianyi@users.noreply.huggingface.co>

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README.md

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+---
+language:
+- en
+license: apache-2.0
+size_categories:
+- 1K<n<10K
+task_categories:
+- visual-question-answering
+pretty_name: ColorBench
+dataset_info:
+  features:
+  - name: idx
+    dtype: int64
+  - name: id
+    dtype: int64
+  - name: type
+    dtype: string
+  - name: task
+    dtype: string
+  - name: filename
+    dtype: string
+  - name: image
+    dtype: image
+  - name: prompt
+    dtype: string
+  - name: question
+    dtype: string
+  - name: choices
+    sequence: string
+  - name: answer
+    dtype: string
+  - name: image_url
+    dtype: string
+  - name: image_type
+    dtype: string
+  splits:
+  - name: test
+    num_bytes: 3639277127.95
+    num_examples: 5885
+  download_size: 3535506580
+  dataset_size: 3639277127.95
+configs:
+- config_name: default
+  data_files:
+  - split: test
+    path: data/test-*
+---
+
+# 🎨 ColorBench
+[**📖 Paper**](https://arxiv.org/abs/2504.10514) | [**💻 GitHub**](https://github.com/tianyi-lab/ColorBench)
+
+ColorBench is a **multimodal dataset** to comprehensively assess capabilities of VLMs in color understanding, including color perception, reasoning, and robustness, introduced in ["ColorBench: Can VLMs See and Understand the Colorful World? A Comprehensive Benchmark for Color Perception, Reasoning, and Robustness"](https://arxiv.org/abs/2504.10514).
+
+It provides:
+- **More than 5,800 image-text questions** covering diverse application scenarios and practical challenges for VLMs evaluation.
+- **3 categories and 11 tasks** for various color-centric capabilities evaluation including Perception (Color Recognition, Color Extraction and Object Recognition), Reasoning (Color Proportion, Color Comparison, Color Counting, and more) and Robustness. 
+
+## 📃 Instruction
+The data/test*.parquet files contain the dataset annotations and images pre-loaded for processing with HF Datasets.
+```bash
+from datasets import load_dataset
+
+color_bench = load_dataset("umd-zhou-lab/ColorBench")
+```
+
+## 📂 Dataset Description
+
+The dataset contains the following fields:
+
+| Field Name | Description                                                                 |
+|------------|-----------------------------------------------------------------------------|
+| idx        | Global index of the sample in the dataset                                   |
+| id         | Index of the sample in each task                                            |
+| type       | Type of category: Perception, Reasoning, or Robustness                      |
+| task       | Type of task: Color Recognition, Color Extraction, Color Counting, and more |
+| filename   | Path to the image                                                           |
+| image_url  | Source of the image                                                         |
+| prompt     | Prompt with question and choices pre-formatted                              |
+| question   | Question about the image                                                    |
+| choices    | Answer choices for the question                                             |
+| answer     | Correct answer to the question                                              |
+| image      | Image object (PIL.Image)                                                    |

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