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README.md

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+---
+language:
+  - en
+tags:
+  - remote-sensing
+  - image-quality-assessment
+  - benchmark
+  - visual-question-answering
+task_categories:
+  - visual-question-answering
+  - image-classification
+pretty_name: SenseBench
+license: cc-by-4.0
+---
+
+# SenseBench
+
+> A benchmark for remote sensing low-level visual perception and description in large vision-language models.
+
+🏠 [github](https://github.com/Zhong-Chenchen/SenseBench) | 🤗 [Hugging Face Subset](https://huggingface.co/datasets/Zhongchenchen/SenseBench_subset)
+
+## Overview
+
+SenseBench is a remote sensing benchmark for evaluating low-level visual perception and description in large vision-language models.
+
+## Supported Tasks
+
+- Visual question answering
+- Text generation
+
+## Language
+
+- English
+
+## Data format
+
+Each example contains image paths, a question, an answer, and metadata describing the distortion type.
+
+```json
+{
+  "id": "4fda312e-70d2-4df7-b1f7-2f06955bf338",
+  "images": [
+    "images/4fda312e-70d2-4df7-b1f7-2f06955bf338_0.png",
+    "images/4fda312e-70d2-4df7-b1f7-2f06955bf338_1.png"
+  ],
+  "question": "Using the options provided, rate the overall quality of Image 2 compared to Image 1.\nA.No/Slight distortion\nB.Moderate distortion\nC.Severe distortion",
+  "answer": "A",
+  "meta": {
+    "image_count": "multi",
+    "modality": "RGB",
+    "task": "how",
+    "domain": "general",
+    "distortion_family": "blur",
+    "distortion_type": "blur_gaussian",
+    "distortion_complexity": "single",
+    "comparison": "intra-image"
+  }
+}
+```