| |
|
| | --- |
| | license: mit |
| | tags: |
| | - yolov8 |
| | - object-detection |
| | - computer-vision |
| | - mobile-phone |
| | - suitcase |
| | --- |
| | |
| | # YOLOv8n Multi-Object Detector (Phone & Suitcase) |
| |
|
| | A fine-tuned **YOLOv8 Nano (YOLOv8n)** model capable of detecting **mobile phones**, **suit cases** and **handbags** in images. |
| | The model has been trained and validated on custom datasets with diverse backgrounds, lighting conditions, |
| | and object orientations. |
| |
|
| | ## Model Details |
| |
|
| | - **Base Model**: YOLOv8n (Nano) |
| | - **Task**: Object Detection |
| | - **Supported Classes**: |
| | - `mobile_phone` |
| | - `suitcase` |
| | - **Number of Classes**: 2 |
| | - **Input Resolution**: 640 × 640 |
| | - **Framework**: Ultralytics YOLO |
| | - **Training Date**: 2026-02-06 |
| |
|
| | ## Capabilities |
| |
|
| | This model can: |
| | - Detect **mobile phones** in real-world scenes |
| | - Detect **suitcases / luggage** in travel and indoor environments |
| | - Handle multiple objects per image |
| | - Perform robustly under varied lighting and viewpoints |
| |
|
| | ## Training Details |
| |
|
| | - **Image Size**: 640 |
| | - **Optimizer**: Default YOLOv8 optimizer |
| | - **Augmentations**: YOLOv8 default augmentations |
| | - **Device**: NVIDIA GPU |
| | - **Training Strategy**: Transfer learning from YOLOv8n |
| |
|
| | ## Dataset Information |
| |
|
| | The model was trained using curated datasets containing: |
| | - Mobile phone images with bounding-box annotations |
| | - Suitcase / luggage images with bounding-box annotations |
| | - Real-world indoor and outdoor scenes |
| | - Multiple object instances per image |
| |
|
| | Dataset annotations follow object-detection standards compatible with YOLO training pipelines. |
| |
|
| | ## Evaluation & Metrics |
| |
|
| | - Quantitative evaluation metrics are available in `results.csv` |
| | - Qualitative predictions can be seen in validation images from the training run |
| |
|
| | ## Files in This Repository |
| |
|
| | - `Yolov8_SE_2.pt` – Trained YOLOv8 model weights |
| | - `args.yaml` – Training configuration |
| | - `results.csv` – Training and validation metrics |
| |
|
| | ## License |
| |
|
| | This model is released under the **MIT License**. |
| |
|
| | ## Acknowledgements |
| |
|
| | - Ultralytics YOLOv8: https://github.com/ultralytics/ultralytics |
| | - Training datasets sourced and curated for object detection research |
| |
|
