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--- |
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dataset_info: |
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features: |
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- name: index |
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dtype: int64 |
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- name: video_index |
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dtype: string |
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- name: question |
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dtype: string |
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- name: answer |
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dtype: string |
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- name: eval_method |
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dtype: string |
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- name: option |
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sequence: string |
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- name: task_type |
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dtype: string |
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- name: task |
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dtype: string |
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- name: duration |
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dtype: float64 |
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- name: meta |
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struct: |
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- name: fps |
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dtype: float64 |
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- name: frame_count |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 500262 |
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num_examples: 2000 |
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download_size: 167816 |
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dataset_size: 500262 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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task_categories: |
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- video-text-to-text |
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--- |
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This dataset is from the paper [MME-VideoOCR: Evaluating OCR-Based Capabilities of Multimodal LLMs in |
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Video Scenarios](https://huggingface.co/papers/2505.21333). |
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See https://github.com/FrankYang-17/MME-VideoOCR for more information. |
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# License |
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Our MME-VideoOCR is released as [CC-BY-NC4.0](https://creativecommons.org/licenses/by-nc/4.0/). The video samples are collected from a publicly available resource. |
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## Note |
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MME-VideoOCR is only used for academic research. Commercial use in any form is prohibited. |
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The copyright of all videos belongs to the video owners. |
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If there is any infringement in MME-VideoOCR, please email [email protected] and we will remove it immediately. |
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Without prior approval, you cannot distribute, publish, copy, disseminate, or modify MME-VideoOCR in whole or in part. |
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You must strictly comply with the above restrictions. |
