| --- |
| license: mit |
| tags: |
| - pytorch |
| - object-detection |
| - yolo |
| - computer-vision |
| - aircraft-detection |
| --- |
| |
| # WingID |
|
|
| ## Model Description |
| A YOLO11l model fine-tuned for aircraft and bird detection. WingID is a real-time visual identification system capable of detecting and classifying flying objects — including various aircraft types and bird species — from camera feeds or static images. |
|
|
| ## Model Architecture |
| - **Base Model**: YOLO11l (Large variant) |
| - **Framework**: PyTorch / Ultralytics |
| - **Task**: Object Detection |
| - **Input**: RGB images / video frames |
|
|
| ## Training Details |
| - **Approach**: Fine-tuned YOLO11l on a curated dataset of aircraft and bird images |
| - **Augmentations**: Mosaic, random flip, scale jitter, HSV augmentation |
| - **Optimizer**: SGD / AdamW with cosine LR scheduling |
|
|
| ## Performance |
| Achieves high mAP on the validation set for aircraft and bird detection across multiple classes. |
|
|
| ## Files |
| | File | Description | |
| |------|-------------| |
| | `yolo11l.pt` | Fine-tuned YOLO11l model weights | |
|
|
| ## Usage |
|
|
| ```python |
| from ultralytics import YOLO |
| from huggingface_hub import hf_hub_download |
| |
| # Download model |
| model_path = hf_hub_download(repo_id='devanshty/WingID', filename='yolo11l.pt') |
| |
| # Load model |
| model = YOLO(model_path) |
| |
| # Run inference |
| results = model('aircraft_image.jpg') |
| results[0].show() |
| ``` |
|
|
| ## Download & Use |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| model_path = hf_hub_download(repo_id='devanshty/WingID', filename='yolo11l.pt') |
| ``` |
|
|
