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--- |
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annotations_creators: |
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- no-annotation |
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language_creators: |
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- crowdsourced |
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language: |
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- ko |
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license: |
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- cc-by-4.0 |
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multilinguality: |
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- monolingual |
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pretty_name: laion2B-multi-korean-subset |
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size_categories: |
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- 10M<n<100M |
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task_categories: |
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- feature-extraction |
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--- |
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# laion2B-multi-korean-subset |
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## Dataset Description |
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- **Homepage:** [laion-5b](https://laion.ai/blog/laion-5b/) |
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- **Huggingface:** [laion/laion2B-multi](https://huggingface.co/datasets/laion/laion2B-multi) |
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## About dataset |
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a subset data of [laion/laion2B-multi](https://huggingface.co/datasets/laion/laion2B-multi), including only korean |
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### Lisence |
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CC-BY-4.0 |
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## Data Structure |
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### Data Instance |
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```pycon |
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>>> from datasets import load_dataset |
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>>> dataset = load_dataset("Bingsu/laion2B-multi-korean-subset") |
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>>> dataset |
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DatasetDict({ |
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train: Dataset({ |
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features: ['SAMPLE_ID', 'URL', 'TEXT', 'HEIGHT', 'WIDTH', 'LICENSE', 'LANGUAGE', 'NSFW', 'similarity'], |
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num_rows: 11376263 |
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}) |
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}) |
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``` |
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```pycon |
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>>> dataset["train"].features |
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{'SAMPLE_ID': Value(dtype='int64', id=None), |
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'URL': Value(dtype='string', id=None), |
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'TEXT': Value(dtype='string', id=None), |
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'HEIGHT': Value(dtype='int32', id=None), |
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'WIDTH': Value(dtype='int32', id=None), |
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'LICENSE': Value(dtype='string', id=None), |
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'LANGUAGE': Value(dtype='string', id=None), |
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'NSFW': Value(dtype='string', id=None), |
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'similarity': Value(dtype='float32', id=None)} |
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``` |
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### Data Size |
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download: 1.56 GiB<br> |
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generated: 2.37 GiB<br> |
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total: 3.93 GiB |
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### Data Field |
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- 'SAMPLE_ID': `int` |
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- 'URL': `string` |
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- 'TEXT': `string` |
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- 'HEIGHT': `int` |
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- 'WIDTH': `int` |
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- 'LICENSE': `string` |
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- 'LANGUAGE': `string` |
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- 'NSFW': `string` |
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- 'similarity': `float` |
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### Data Splits |
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| | train | |
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| --------- | -------- | |
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| # of data | 11376263 | |
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## Note |
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### Height, Width |
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μ΄λ―Έμ§μ κ°λ‘κ° `HEIGHT`λ‘, μΈλ‘κ° `WIDTH`λ‘ λμ΄μλ κ² κ°μ΅λλ€. |
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```pycon |
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>>> dataset["train"][98] |
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{'SAMPLE_ID': 2937471001780, |
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'URL': 'https://image.ajunews.com/content/image/2019/04/12/20190412175643597949.png', |
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'TEXT': 'μΈμ²μκ΅μ‘μ², μΈμ² μꡰꡬλ°μ νμν μμμ§κ³Όμ κ°λ΄ν κ°μ΅', |
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'HEIGHT': 640, |
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'WIDTH': 321, |
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'LICENSE': '?', |
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'LANGUAGE': 'ko', |
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'NSFW': 'UNLIKELY', |
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'similarity': 0.33347243070602417} |
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``` |
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![image](https://image.ajunews.com/content/image/2019/04/12/20190412175643597949.png) |
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### Code used to generate |
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```py |
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import csv |
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import re |
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from datasets import load_dataset |
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from tqdm import tqdm |
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pattern = re.compile(r"[κ°-ν£]") |
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def quote(s: str) -> str: |
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s = s.replace('"""', "") |
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return s |
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def filter_func(example) -> bool: |
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lang = example.get("LANGUAGE") |
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text = example.get("TEXT") |
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if not isinstance(lang, str) or not isinstance(text, str): |
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return False |
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return lang == "ko" or pattern.search(text) is not None |
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file = open("./laion2B-mulit_korean_subset.csv", "w", encoding="utf-8", newline="") |
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ds = load_dataset("laion/laion2B-multi", split="train", streaming=True) |
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dsf = ds.filter(filter_func) |
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header = [ |
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"SAMPLE_ID", |
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"URL", |
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"TEXT", |
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"HEIGHT", |
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"WIDTH", |
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"LICENSE", |
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"LANGUAGE", |
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"NSFW", |
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"similarity", |
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] |
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writer = csv.DictWriter(file, fieldnames=header) |
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writer.writeheader() |
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try: |
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for data in tqdm(dsf): |
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data["TEXT"] = quote(data.get("TEXT", "")) |
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if data["TEXT"]: |
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writer.writerow(data) |
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finally: |
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file.close() |
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print("Done!") |
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``` |
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μ΄νμ `HEIGHT`λ `WIDTH`κ° NoneμΈ λ°μ΄ν°λ₯Ό μ κ±°νκ³ μ
λ‘λνμμ΅λλ€. |
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|
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### img2dataset |
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|
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[img2dataset](https://github.com/rom1504/img2dataset)μ μ¬μ©νμ¬ URLλ‘λ μ΄λ―Έμ§λ€μ λ°μ΄ν°μ
ννλ‘ λ§λ€ μ μμ΅λλ€. |
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