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---
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license: openrail
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---
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---
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license: openrail
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---
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# OVDEval:How to Evaluate the Generalization of Detection? A Benchmark for Comprehensive Open-Vocabulary Detection
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## Dataset Description
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OVDEval is a new benchmark for OVD model, which includes 9 sub-tasks and introduces evaluations on commonsense knowledge, attribute understanding, position understanding, object relation comprehension, and more.
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## Languages
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The dataset contains questions in English and code solutions in Python.
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## Dataset Structure
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```python
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{
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"categories": [
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{
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"supercategory": "object",
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"id": 0,
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"name": "computer without screen on"
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}]
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"annotations": [
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{
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"id": 0,
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"bbox": [
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111,
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117,
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99,
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75
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],
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"category_id": 0,
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"image_id": 0,
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"iscrowd": 0,
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"area": 7523
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}]
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"images": [
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{
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"file_name": "64d22c6fe4b011b0db94b993.jpg",
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"id": 0,
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"height": 254,
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"width": 340,
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"text": [
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"computer without screen on"
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],
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"neg_text": [
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"computer with screen on"
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]
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}]
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}
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```
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### How to use it
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Reference https://github.com/om-ai-lab/OVDEval
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### Data Fields
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
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## Citation Information
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If you find our data, or code helpful, please cite the original paper:
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```
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@article{yao2023evaluate,
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title={How to Evaluate the Generalization of Detection? A Benchmark for Comprehensive Open-Vocabulary Detection},
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author={Yao, Yiyang and Liu, Peng and Zhao, Tiancheng and Zhang, Qianqian and Liao, Jiajia and Fang, Chunxin and Lee, Kyusong and Wang, Qing},
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journal={arXiv preprint arXiv:2308.13177},
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year={2023}
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}
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```
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