Remove 1166 invalid images from UniMER-1M
Browse files- README.md +3 -3
- UniMER-1M.zip +2 -2
README.md
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The UniMER dataset is a specialized collection curated to advance the field of Mathematical Expression Recognition (MER). It encompasses the comprehensive UniMER-1M training set, featuring over one million instances that represent a diverse and intricate range of mathematical expressions, coupled with the UniMER Test Set, meticulously designed to benchmark MER models against real-world scenarios. The dataset details are as follows:
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- **UniMER-1M Training Set:**
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- Total Samples: 1,
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- Composition: A balanced mix of concise and complex, extended formula expressions
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- Aim: To train robust, high-accuracy MER models, enhancing recognition precision and generalization
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UniMER数据集是专门为通用数学表达式识别（MER）发布的数据集。它包含了真实全面的UniMER-1M训练集，拥有超过一百万个代表广泛和复杂数学表达式的实例，以及精心设计的UniMER测试集，用于在真实世界场景中评估MER模型。数据集详情如下：
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- **UniMER-1M 训练集：**
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- 总样本数：1,
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- 组成：简洁与复杂、扩展公式表达式的平衡融合
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- 目标：帮助训练鲁棒性强、高精度的MER模型，增强识别准确性和模型泛化能力
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howpublished = {\url{https://opendatalab.com}},
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year={2022}
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}
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```
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The UniMER dataset is a specialized collection curated to advance the field of Mathematical Expression Recognition (MER). It encompasses the comprehensive UniMER-1M training set, featuring over one million instances that represent a diverse and intricate range of mathematical expressions, coupled with the UniMER Test Set, meticulously designed to benchmark MER models against real-world scenarios. The dataset details are as follows:
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- **UniMER-1M Training Set:**
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- Total Samples: 1,060,625 Latex-Image pairs
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- Composition: A balanced mix of concise and complex, extended formula expressions
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- Aim: To train robust, high-accuracy MER models, enhancing recognition precision and generalization
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UniMER数据集是专门为通用数学表达式识别（MER）发布的数据集。它包含了真实全面的UniMER-1M训练集，拥有超过一百万个代表广泛和复杂数学表达式的实例，以及精心设计的UniMER测试集，用于在真实世界场景中评估MER模型。数据集详情如下：
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- **UniMER-1M 训练集：**
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- 总样本数：1,060,625
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- 组成：简洁与复杂、扩展公式表达式的平衡融合
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- 目标：帮助训练鲁棒性强、高精度的MER模型，增强识别准确性和模型泛化能力
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howpublished = {\url{https://opendatalab.com}},
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year={2022}
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}
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```
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UniMER-1M.zip
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 1985324814
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