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480
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chess_044_jpeg.rf.87e53a1f002cb177e31a4698f0aa71af
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chess_028_jpeg.rf.e3bef21b689460e915e0df1c6c60e04c
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chess_031_jpeg.rf.4242331512b20fcbe978bacd41c2a41a
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chess_00023_jpeg.rf.4116b902365ccc50a46cf22d94ce5f95
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chess_00040_jpeg.rf.d8f1336f541bad3cfff94b8a3aa80bcc
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chess_006_jpeg.rf.ced2b0ccf38cc6f919b3676aad47afea
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chess_001_jpeg.rf.43260d30059792e12d240cfbfa7b0384
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chess_039_jpeg.rf.df485a9dc749c5e2224f9b7058bdbf9f
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chess_00022_jpeg.rf.84fd39e5d0d69190c61973466324b8aa
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chess_00046_jpeg.rf.31071c54555ab3c64009976fb8d606e1
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chess_00022_jpeg.rf.0f61e7af0048bd09d65d8699bcb2b54e
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chess_00040_jpeg.rf.0320279b1cc516780827a5a5896033e9
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chess_027_jpeg.rf.6c82ca008ef442e7f87fbb53a075b8ba
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chess_069_jpeg.rf.f3acbf02031733f0c878a5f059ab06e0
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chess_00008_jpeg.rf.8babb3822ccdbbe4454b02d43cca1ad9
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chess_00003_jpeg.rf.30e72204255ffc18b399a49f8c5a90b3
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chess_029_jpeg.rf.7299ac9d81f127f11e05cf14704853c7
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chess_00048_jpeg.rf.95aab22fbd86537ceec0146e4e907a9a
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chess_00027_jpeg.rf.7073d1857c097e63ec22d9729642973d
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chess_057_jpeg.rf.e419324b2bfc6257a70a52cfd23ce40f
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Chess Piece Detection Dataset: chess_pieces_dominique

Dataset Description

This dataset contains chess piece detection annotations in YOLOv8 format.

Chess piece detection dataset from Dominique with 12 classes of chess pieces, optimized for YOLOv8 training.

Dataset Structure

The dataset follows the YOLOv8 format with the following structure:

  • train/: Training images and labels
  • valid/: Validation images and labels
  • test/: Test images and labels

Classes

The dataset contains 12 classes of chess pieces:

  1. black-bishop
  2. black-king
  3. black-knight
  4. black-pawn
  5. black-queen
  6. black-rook
  7. white-bishop
  8. white-king
  9. white-knight
  10. white-pawn
  11. white-queen
  12. white-rook

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("dopaul/chess_pieces_dominique")

# Access different splits
train_data = dataset["train"]
valid_data = dataset["valid"]
test_data = dataset["test"]

# Example: Access first training image and annotations
example = train_data[0]
image = example["image"]
annotations = example["annotations"]

Citation

If you use this dataset, please consider citing the original sources and this repository.

License

This dataset is released under the CC BY 4.0 license.

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