Add model card

README.md

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+---
+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')
+```