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README.dataset.txt

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+# Chess Pieces > 416x416_aug
+https://universe.roboflow.com/joseph-nelson/chess-pieces-new
+
+Provided by [Roboflow](https://roboflow.ai)
+License: Public Domain
+
+# Overview
+
+This is a dataset of Chess board photos and various pieces. All photos were captured from a constant angle, a tripod to the left of the board. The bounding boxes of all pieces are annotated as follows: `white-king`, `white-queen`, `white-bishop`, `white-knight`, `white-rook`, `white-pawn`, `black-king`, `black-queen`, `black-bishop`, `black-knight`, `black-rook`, `black-pawn`. There are 2894 labels across 292 images.
+
+![Chess Example](https://i.imgur.com/nkjobw1.png)
+
+**Follow [this tutorial](https://blog.roboflow.ai/training-a-yolov3-object-detection-model-with-a-custom-dataset/) to see an example of training an object detection model using this dataset or jump straight to the [Colab notebook](https://colab.research.google.com/drive/1ByRi9d6_Yzu0nrEKArmLMLuMaZjYfygO#scrollTo=WgHANbxqWJPa).**
+
+# Use Cases
+
+At Roboflow, we built a chess piece object detection model using this dataset.
+
+![ChessBoss](https://blog.roboflow.ai/content/images/2020/01/chess-detection-longer.gif)
+
+You can see a video demo of that [here](https://www.youtube.com/watch?v=XLispu-Yb_0). (We did struggle with pieces that were occluded, i.e. the state of the board at the very beginning of a game has many pieces obscured - let us know how your results fare!)
+
+# Using this Dataset
+
+We're releasing the data free on a public license.
+
+# About Roboflow
+
+[Roboflow](https://roboflow.ai) makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless.
+
+Developers reduce 50% of their boilerplate code when using Roboflow's workflow, save training time, and increase model reproducibility.
+
+#### [![Roboflow Workmark](https://i.imgur.com/WHFqYSJ.png =350x)](https://roboflow.ai)
+

README.md

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 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: image_id
-    dtype: string
-  - name: annotations
-    sequence:
-    - name: class_id
-      dtype: int32
-    - name: x_center
-      dtype: float32
-    - name: y_center
-      dtype: float32
-    - name: width
-      dtype: float32
-    - name: height
-      dtype: float32
-  - name: image_width
-    dtype: int32
-  - name: image_height
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 14796314.0
-    num_examples: 606
-  - name: valid
-    num_bytes: 1390937.0
-    num_examples: 58
-  - name: test
-    num_bytes: 742690.0
-    num_examples: 29
-  download_size: 16901375
-  dataset_size: 16929941.0
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: valid
-    path: data/valid-*
-  - split: test
-    path: data/test-*
+license: cc-by-4.0
+task_categories:
+- object-detection
+tags:
+- chess
+- computer-vision
+- yolo
+- object-detection
+size_categories:
+- 1K<n<10K
 ---
+
+# Chess Piece Detection Dataset: chess_pieces_roboflow
+
+## Dataset Description
+
+This dataset contains chess piece detection annotations in YOLOv8 format.
+
+Chess piece detection dataset from Roboflow with processed labels, cleaned and standardized for YOLOv8 format.
+
+## 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:
+
+0. black-bishop
+1. black-king
+2. black-knight
+3. black-pawn
+4. black-queen
+5. black-rook
+6. white-bishop
+7. white-king
+8. white-knight
+9. white-pawn
+10. white-queen
+11. white-rook
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("dopaul/chess_pieces_roboflow")
+
+# 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.

README.roboflow.txt

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+
+Chess Pieces - v24 416x416_aug
+==============================
+
+This dataset was exported via roboflow.com on January 27, 2024 at 10:40 AM GMT
+
+Roboflow is an end-to-end computer vision platform that helps you
+* collaborate with your team on computer vision projects
+* collect & organize images
+* understand and search unstructured image data
+* annotate, and create datasets
+* export, train, and deploy computer vision models
+* use active learning to improve your dataset over time
+
+For state of the art Computer Vision training notebooks you can use with this dataset,
+visit https://github.com/roboflow/notebooks
+
+To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
+
+The dataset includes 693 images.
+Pieces are annotated in YOLOv8 Oriented Object Detection format.
+
+The following pre-processing was applied to each image:
+* Auto-orientation of pixel data (with EXIF-orientation stripping)
+* Resize to 416x416 (Stretch)
+
+The following augmentation was applied to create 3 versions of each source image:
+* 50% probability of horizontal flip
+* Randomly crop between 0 and 15 percent of the image
+* Random shear of between -6° to +6° horizontally and -6° to +6° vertically
+* Random brigthness adjustment of between -10 and +10 percent
+* Random exposure adjustment of between -10 and +10 percent
+
+

data.yaml

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+train: ../train/images
+val: ../valid/images
+test: ../test/images
+names:
+  0: black-bishop
+  1: black-king
+  2: black-knight
+  3: black-pawn
+  4: black-queen
+  5: black-rook
+  6: white-bishop
+  7: white-king
+  8: white-knight
+  9: white-pawn
+  10: white-queen
+  11: white-rook