star092304/traffic-sign-detection-vietnam-yolo

🚦 Traffic Sign Detection — Vietnam (YOLO11s)

YOLO11s model trained on the Vietnam Traffic Sign Detection dataset.

Property	Value
Model	YOLO11s
Classes	82 Vietnamese traffic signs
Image size	640×640
Framework	Ultralytics
Dataset Source	Hugging Face

Evaluation Results

Below is the summary of the evaluation results from evalution/summary.json:

Metric	Value
Model	yolo11s.pt
Epochs Trained	50
Number of Classes	82
Device	GPU
Precision	96.42% (0.9642)
Recall	96.15% (0.9615)
mAP50	98.06% (0.9806)
mAP75	93.37% (0.9337)
mAP50-95	83.57% (0.8357)
FPS	61.5
Mean Latency	16.25 ms
p50 Latency	15.03 ms
p95 Latency	22.59 ms
Min Latency	13.44 ms
Max Latency	23.24 ms

Visualizations

Training Curves

Results

Random Predictions (Inference)

Files

File	Description
best.pt	PyTorch weights (main model)
best.onnx	ONNX export (CPU/edge deploy)
data.yaml	Dataset config with class names
config.json	Training hyperparameters
metrics.json	Test-set evaluation results
benchmark.json	FPS / latency results
summary.json	All metrics combined

Quick Start

from ultralytics import YOLO

# PyTorch
model = YOLO("best.pt")
results = model("image.jpg", conf=0.25)
results[0].show()

# ONNX (faster on CPU)
model_onnx = YOLO("best.onnx")
results = model_onnx("image.jpg")

CLI Inference

python infer.py --source image.jpg
python infer.py --source video.mp4 --save
python infer.py --source 0 --show          # webcam

Training Details

• Base model: yolo11s.pt (pretrained COCO)
• Early stopping: patience=20
• Dataset cache: enabled (faster I/O)
• Seed: 42 (reproducible)
• Optimizer: auto (AdamW)