Datasets:
Tasks:
Visual Question Answering
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
License:
SushantGautam
commited on
Commit
•
4821949
1
Parent(s):
785c41b
Update README.md
Browse files
README.md
CHANGED
@@ -48,14 +48,14 @@ ds = load_dataset("SimulaMet-HOST/Kvasir-VQA")
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```
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d_path ="./" #existing folder where you want to save images and metadata.csv
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-
df = ds['
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df.to_csv(f"{d_path}/metadata.csv", index=False)
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import os
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os.makedirs(f"{d_path}/images", exist_ok=True)
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for i, row in df.groupby('img_id').nth(0).iterrows(): # for images
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image = ds['
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```
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The total image size is around 1.5 GB. The CSV file will have 58,849 rows.
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```
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d_path ="./" #existing folder where you want to save images and metadata.csv
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df = ds['raw'].select_columns(['source', 'question', 'answer', 'img_id']).to_pandas()
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df.to_csv(f"{d_path}/metadata.csv", index=False)
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import os
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os.makedirs(f"{d_path}/images", exist_ok=True)
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for i, row in df.groupby('img_id').nth(0).iterrows(): # for images
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image = ds['raw'][i]['image'].save(f"{d_path}/images/{row['img_id']}.jpg")
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```
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The total image size is around 1.5 GB. The CSV file will have 58,849 rows.
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