AdithyaSK/cursor-detection-yolov8n

Cursor Detection YOLOv8n

A YOLOv8n model trained to detect mouse cursors in screenshots and video frames.

Training Details

• Base Model: YOLOv8n (3.2M parameters)
• Training Data: Synthetic dataset generated by compositing 366 different cursor types onto 1688 website screenshots
• Dataset Size: 500 train / 100 val / 50 test
• Image Size: 640x640
• Epochs: 30
• Hardware: NVIDIA T4 GPU

Performance

Metric	Value
mAP50	92.1%
mAP50-95	58.2%
Precision	84.8%
Recall	89.5%

Dataset Generation

The synthetic dataset was created by:

1. Loading cursor images from Fraser/cursors (366 cursor types with hotspot info)
2. Loading background screenshots from naorm/website-screenshots
3. Compositing cursors at random positions with alpha blending
4. Generating YOLO format bounding box labels

Usage

from ultralytics import YOLO

# Load model
model = YOLO("AdithyaSK/cursor-detection-yolov8n/best.pt")

# Detect cursor in an image
results = model("screenshot.jpg")
results[0].show()

License

AGPL-3.0 (same as Ultralytics YOLOv8)