Datasets:
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README.md
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---
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license: apache-2.0
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dataset_info:
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features:
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- name: idx
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dtype: int64
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- name: id
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dtype: int64
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- name: type
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dtype: string
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- name: task
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dtype: string
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- name: filename
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dtype: string
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- name: image_url
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dtype: string
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- name: prompt
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dtype: string
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- name: question
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dtype: string
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- name: choices
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sequence: string
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- name: answer
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dtype: string
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- name: image
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dtype: image
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splits:
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- name: test
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num_bytes: 1808612125.49
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num_examples: 5814
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download_size: 580531082
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dataset_size: 1808612125.49
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configs:
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- config_name: default
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data_files:
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- split: test
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path: data/test-*
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---
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license: apache-2.0
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dataset_info:
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features:
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- name: idx
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dtype: int64
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- name: id
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dtype: int64
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- name: type
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dtype: string
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- name: task
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dtype: string
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- name: filename
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dtype: string
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- name: image_url
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dtype: string
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- name: prompt
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dtype: string
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- name: question
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dtype: string
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- name: choices
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sequence: string
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- name: answer
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dtype: string
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- name: image
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dtype: image
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splits:
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- name: test
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num_bytes: 1808612125.49
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num_examples: 5814
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download_size: 580531082
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dataset_size: 1808612125.49
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configs:
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- config_name: default
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data_files:
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- split: test
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path: data/test-*
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task_categories:
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- visual-question-answering
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language:
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- en
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pretty_name: ColorBench
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size_categories:
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- 1K<n<10K
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---
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# 🎨 ColorBench
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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".
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It provides:
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- **5,800 image-text questions** covering various image types and applications for VLMs evaluation.
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- **3 categories and 11 tasks** for multiple color-related capabilities evaluation including Perception (Color Recognition, Color Extraction and Object Recognition), Reasoning (Color Proportion, Color Comparison, Color Counting, and more.) and Robustness.
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## 📃 Instruction
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The data/test*.parquet files contain the dataset annotations and images pre-loaded for processing with HF Datasets.
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```bash
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from datasets import load_dataset
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colro_bench = load_dataset("umd-zhou-lab/ColorBench")
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```
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## 📂 Dataset Description
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The dataset contains the following fields:
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| Field Name | Description |
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|------------|-----------------------------------------------------------------------------|
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| idx | Global index of the sample in the dataset |
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| id | Index of the sample in each task |
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| type | Type of category: Perception, Reasoning, or Robustness |
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| task | Type of task: Colo Recognition, Color Extraction, Color Counting , and more |
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| filename | Path to the image |
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| image_url | Source of the image |
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| prompt | Prompt with question and choices pre-formatted |
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| question | Question asked about the image |
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| choices | Answer choices for the question |
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| answer | Correct answer to the question |
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| image | Image object (PIL.Image) |
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