You can deploy this model and start earning money today!

IndUSV/
yolov8n-mobile-phone

Views

No views yet

YOLOv8n Mobile Phone Detector

A fine-tuned YOLOv8 Nano model trained on the Datacluster Labs Mobile Phone Image Dataset for object detection of mobile phones in images.

Model Details

Base Model: YOLOv8n (Nano)
Task: Object Detection
Dataset: Datacluster Labs Mobile Phone Image Dataset
Classes: mobile_phone (1 class)
Training Date: 2026-02-04

Usage

python

from ultralytics import YOLO

# Load model from Hugging Face
model = YOLO('huggingface://IndUSV/yolov8n-mobile-phone-detector/pytorch_model.bin')

# Run inference
results = model.predict(source='image.jpg', conf=0.5)

Training Details

Input Size: 640x640
Batch Size: 16
Optimizer: SGD
Learning Rate: Auto
Epochs: 50 (with early stopping)
Device: NVIDIA GPU

Dataset Information

The model was trained on the Datacluster Labs Mobile Phone Image Dataset which contains:

High-resolution mobile phone images
Pascal VOC format annotations
Diverse backgrounds and lighting conditions
Various phone models and orientations

Dataset splits:

Training: 80%
Validation: 10%
Testing: 10%

Performance

Check results.csv for detailed training metrics and evaluation results.

Citation

If you use this model, please cite:

License

This model is released under the MIT License.