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README.md
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#
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### Dataset Description
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<!-- Provide a longer summary of what this dataset is. -->
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- **Curated by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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<!-- Motivation for the creation of this dataset. -->
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[More Information Needed]
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### Source Data
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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#### Data Collection and Processing
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<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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[More Information Needed]
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#### Who are the source data producers?
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<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
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[More Information Needed]
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### Annotations [optional]
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<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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#### Annotation process
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<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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[More Information Needed]
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#### Who are the annotators?
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<!-- This section describes the people or systems who created the annotations. -->
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[More Information Needed]
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#### Personal and Sensitive Information
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<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Dataset Card Authors [optional]
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[More Information Needed]
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## Dataset Card Contact
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[More Information Needed]
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size_categories:
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- 100M<n<1B
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---
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# SQLITE-DB for Danbooru 2023 (until 7110548)
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This is an cleaned-up version (almost totally recreated) of https://huggingface.co/datasets/KBlueLeaf/danbooru2023-sqlite
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The previous sqlite database had major defects, especially with tag ids being mismatched, which was causing data to be actually different from server.
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Note that minor information, such as uploader id, are not fixed.
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Most of the discrepancy has been detected from id 5139963-6859952.
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The additional scripts and example files that can be used for modify/ adding post are provided for maintenance.
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# view-dataset.py offers you to get the information of post:
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The example post which contained wrong information can be viewed like this:
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post : https://danbooru.donmai.us/posts/6719955
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```
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Post 6719955
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tag_list_general: 1girl(0), long_hair(24), ribbon(36), simple_background(42), smile(43), solo(44), ahoge(71), open_mouth(90), blonde_hair(116), :d(147), red_eyes(193), blush_stickers(274), upper_body(285), neck_ribbon(376), red_ribbon(380), chibi(437), transparent_background(513), cardigan(2754), looking_afar(3998), white_cardigan(52258), sad_keanu_(meme)(136930)
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tag_list_copyright: tokino_sora_(old_design)(364562), juufuutei_raden(649634)
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tag_list_character: regloss_(hololive)(650035)
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tag_list_meta: (175)
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tag_list_artist: xt0y4x(525184)
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```
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However, the actual data will show you the difference:
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```
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{"id": 6719955, "difference": [{"tag_list_general": ["virtual_youtuber"], "tag_list_character": ["otonose_kanade"], "tag_list_artist": ["jb_jagbung"], "tag_list_copyright": ["hololive", "hololive_dev_is"]}, {"tag_list_general": ["sad_keanu_(meme)"], "tag_list_character": ["regloss_(hololive)"], "tag_list_artist": ["xt0y4x"], "tag_list_copyright": ["tokino_sora_(old_design)", "juufuutei_raden"]}]}
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```
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The actual tags ids are followed:
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```
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virtual_youtuber(136931)
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otonose_kanade(650036)
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jb_jagbung(525185)
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hololive(364563)
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hololive_dev_is(649635)
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```
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There were tags added / removed from post, but other than that, there is actual shift on tags - which is not consistent over database.
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```
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tag_list_character: regloss_(hololive)(650035) <-> otonose_kanade(650036)
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tag_list_artist: xt0y4x(525184) <-> jb_jagbung(525185)
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tag_list_copyright: tokino_sora_(old_design)(364562), juufuutei_raden(649634) <-> hololive(364563), hololive_dev_is(649635)
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```
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The tag virtual_youtuber is the good difference that we can add to database too.
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# crawling code is not included.
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# commit_difference.py offers you to change the database's information based on **difference jsonl** files.
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You can prepare bunch of jsonl files, which contains the line of json which contains id-difference.
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The data **must** contain string form of data, not tag id. **The actual danbooru tag id won't match with the database, it is intended to skip bunch of tags which does not have actual post usages.**
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# fix-tags.py just contains the code which will reflect the actual tag usage count, to tag popularity.
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# add_post.py includes code to add more recent post data directly into dataset.
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It contains simple skip schema, if post already exists and it has non-empty tag list, it won't add the post.
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