metadata
tags:
- ultralyticsplus
- yolov8
- ultralytics
- yolo
- vision
- object-detection
- pytorch
library_name: ultralytics
library_version: 8.0.43
inference: false
model-index:
- name: eeshawn11/naruto_hand_seal_detection
results:
- task:
type: object-detection
metrics:
- type: precision
value: 0.995
name: mAP@0.5(box)
Supported Labels
['bird', 'boar', 'dog', 'dragon', 'hare', 'horse', 'monkey', 'ox', 'ram', 'rat', 'snake', 'tiger']
How to use
- Install ultralyticsplus:
pip install ultralyticsplus==0.0.28
- Load model and perform prediction:
from ultralyticsplus import YOLO, render_result
# load model
model = YOLO('eeshawn11/naruto_hand_seal_detection')
# set model parameters
model.overrides['conf'] = 0.50 # NMS confidence threshold
model.overrides['iou'] = 0.70 # NMS IoU threshold
model.overrides['agnostic_nms'] = False # NMS class-agnostic
model.overrides['max_det'] = 10 # maximum number of detections per image
# set image
image = 'https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg'
# perform inference
results = model.predict(image)
# observe results
print(results[0].boxes)
render = render_result(model=model, image=image, result=results[0])
render.show()