movensys/cube-detection-monoply-background-obb
Cube Detection on Monopoly Board Background (OBB) A small oriented-bounding-box (OBB) detection dataset of colored cubes placed on a Movensys "Monopoly" board background. Intended for fine-tuning YOLO-style OBB detectors used in pick-and-place / robotic manipulation pipelines. Classes ID Name 0 green_cube 1 yellow_cube 2 blue_cube 3 red_cube Splits Split Images Labels train 104 104 val 29 29 test 16 16 total… See the full description on the dataset page: https://huggingface.co/datasets/movensys/cube-detection-monoply-background-obb.
Cube Detection on Monopoly Board Background (OBB)
A small oriented-bounding-box (OBB) detection dataset of colored cubes placed on a Movensys "Monopoly" board background. Intended for fine-tuning YOLO-style OBB detectors used in pick-and-place / robotic manipulation pipelines.
Classes
Splits
Image format
- Resolution: 1280 × 720, RGB JPEG
- Captured from a top-down camera over a printed Movensys Monopoly board, with colored cubes placed at varying positions and orientations
Label format
YOLO OBB — one row per object, 9 values:
class_id x1 y1 x2 y2 x3 y3 x4 y4All polygon coordinates are normalized to [0, 1] relative to image width/height. Vertices are given in order around the box.
Example (train/labels/00001.txt):
0 0.0522 0.1119 0.1013 0.0214 0.1529 0.1101 0.1038 0.2005
3 0.2423 0.0615 0.3122 0.0615 0.3122 0.1869 0.2423 0.1869Directory layout
.
├── dataset.yaml
├── train/
│ ├── images/ # *.jpg
│ └── labels/ # *.txt
├── val/
│ ├── images/
│ └── labels/
└── test/
├── images/
└── labels/Usage
Download
hf download movensys/cube-detection-monoply-background-obb \
--repo-type dataset \
--local-dir ./cube-detection-monoply-background-obbTrain with Ultralytics YOLO (OBB)
After download, update the path: field in dataset.yaml to point at the local copy:
path: /absolute/path/to/cube-detection-monoply-background-obb
train: train/images
val: val/images
test: test/images
names:
0: green_cube
1: yellow_cube
2: blue_cube
3: red_cubeThen:
from ultralytics import YOLO
model = YOLO("yolo11n-obb.pt")
model.train(data="dataset.yaml", epochs=100, imgsz=1280)License
Released under the MIT License.
