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End of preview.
VietSpeedYOLO — Residential zone traffic signs (R420/R421)
YOLO-format object detection dataset for Vietnam residential-zone traffic signs: R420 (Bắt đầu khu dân cư) and R421 (Hết khu dân cư). Use for speed-zone detection, ADAS, or traffic sign recognition in Vietnam.
Classes
| ID | Class name | Sign | Description |
|---|---|---|---|
| 0 | khu_dan_cu | R420 | Start of residential area |
| 1 | ngoai_dan_cu | R421 | End of residential area |
Dataset structure
Standard YOLO layout:
- images/train/ — training images
- images/val/ — validation images
- labels/train/ — one
.txtper image:class_id x_center y_center width height(normalized 0–1) - labels/val/ — validation labels
- data.yaml — dataset config (paths + class names)
Usage
With Ultralytics YOLO
# Clone or download this repo, then:
yolo detect train data=data.yaml model=yolov8n.pt epochs=80 batch=16 imgsz=640
With Python
from ultralytics import YOLO
model = YOLO("yolov8n.pt")
model.train(data="data.yaml", epochs=80, batch=16, imgsz=640)
Loading from Hugging Face
After cloning or downloading the dataset from the Hub, point your training script to the local data.yaml. Paths in data.yaml are relative to the dataset root (this repo).
Statistics (example)
- Train: 94 original images (+ optional augmentation for training)
- Val: 23 images
- Labels: one text file per image, YOLO format
License
MIT.
Citation
If you use this dataset, please cite:
- Dataset: NghiMe/vietspeedyolo on Hugging Face
- Code: nghimestudio/vietspeedyolo on GitHub
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