surawut/chess-move-tracking-yolo11
Object Detection
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Chessboard Corner Pose Dataset ♟️📐
1. Dataset Description
This dataset is designed for Keypoint Detection (Pose Estimation) tasks, specifically to detect the 4 semantic corners of a chessboard from various camera angles.
It is intended to be used as Phase 1 of a Chess Move Tracking pipeline. The detected keypoints are used to calculate the Homography matrix for Perspective Warping (straightening the board).
- Task: Keypoint Detection (YOLO-Pose)
- Format: YOLOv8 / YOLO11 Pose Format
- Input: Raw video frames (rotated, tilted, occluded)
- Output: 4 Keypoints (
a1,h1,a8,h8)
2. Dataset Structure
Keypoints Definition
The model is trained to detect 1 Class (Chessboard) with 4 Keypoints:
- Index 0:
a1(Bottom-Left in White perspective) - Index 1:
h1(Bottom-Right in White perspective) - Index 2:
a8(Top-Left in White perspective) - Index 3:
h8(Top-Right in White perspective)
Data Splits
| Split | Images | Description |
|---|---|---|
| Train | 3390 | Extracted from Various Chess Play Videos with augmentations |
| Valid | 290 | Extracted from Various Chess Play Videos (Unseen angles) |
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Models trained or fine-tuned on surawut/chessboard-dataset-yolo