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Chess Piece Cnn

A from-scratch CNN that classifies 50x50 chess-board cells into 13 classes (empty + 6 white + 6 black pieces), trained on the synthetic koryakinp/chess-positions dataset with Kornia GPU augmentation and Optuna...

KindOtherVersionRevision ffdefe9

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122 KB
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vRevision ffdefe9
Updated
Sep 28, 2026
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Hugging Face

Source description

Chess Piece Classifier (Custom CNN)

A from-scratch CNN that classifies 50x50 chess-board cells into 13 classes (empty + 6 white + 6 black pieces), trained on the synthetic koryakinp/chess-positions dataset with Kornia GPU augmentation and Optuna hyperparameter tuning.

Classes

  • 0: empty
  • 1: wP
  • 2: wN
  • 3: wB
  • 4: wR
  • 5: wQ
  • 6: wK
  • 7: bP
  • 8: bN
  • 9: bB
  • 10: bR
  • 11: bQ
  • 12: bK

Usage

import torch
from huggingface_hub import hf_hub_download
weights = hf_hub_download(repo_id="honi05/chess-piece-cnn", filename="chess_cnn.pt")
state = torch.load(weights, map_location="cpu")

Sources

1 source
Hugging FacePrimaryVersion ffdefe9547211b3a0ed336f91af1138ec95763e6
huggingface.co/honi05/chess-piece-cnn/tree/ffdefe9547211b3a0ed336f91af1138ec95763e6

Verified Sep 28

Model artifacts

1 artifact

chess_cnn.pt

pt · 122 KB · SHA-256 9046824efb9f…40ab · Hugging Face

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Source excerpts

2 excerpts

--- license: cc0-1.0 tags: - image-classification - chess - pytorch --- # Chess Piece Classifier (Custom CNN) A from-scratch CNN that classifies 50x50 chess-board cells into 13 classes (empty + 6 white + 6 black pieces), trained on the synthetic `koryakinp/chess-positions` dataset with Kornia GPU augmentation and Optuna hyperparameter tuning. ## Classes - 0: empty - 1: wP - 2: wN - 3: wB - 4: wR - 5: wQ - 6: wK - 7: bP - 8: bN - 9: bB - 10: bR - 11: bQ - 12: bK ## Usage ```python import torch from huggingface_hub import hf_hub_download weights = hf_hub_download(repo_id="honi05/chess-piece-cnn", filename="chess_cnn.pt") state = torch.load(weights, map_location="cpu") ```

Source context: 0 downloads · 0 likes · Pipeline image-classification · Repo honi05/chess-piece-cnn