LanluZ/vascular-bundle-yolov10

Vascular Bundle Detection (YOLOv10m)

A YOLOv10m object-detection model for vascular bundles / bamboo cells in microscopy video frames. Trained on the data.yaml dataset from the companion GitHub repo LanluZ/vascular-bundle-track (formerly yolov8_test).

Model

• —Architecture: YOLOv10m via Ultralytics 8.3.87
• —Input size: 640
• —Single class: Vascular

Metrics

Independent validation on data.yaml (2 images / 224 instances):

Getting started

from ultralytics import YOLO

model = YOLO("https://huggingface.co/LanluZ/vascular-bundle-yolov10/resolve/main/weights/best.pt")
results = model.predict("videos/56-fire.mp4", conf=0.58)

Or download the weight to a local folder and point Ultralytics at it:

hf download LanluZ/vascular-bundle-yolov10 weights/best.pt --local-dir .

Training config

• —model: yolov10m.pt, epochs: 50, batch: 8, imgsz: 640, patience: 30
• —optimizer: auto, seed: 0, deterministic: true
• —Data: data.yaml (1 class: Vascular)

Files

Related

• —Source repo: LanluZ/vascular-bundle-track
• —Source/demo videos: LanluZ/vascular-bundle-media