Edit model card
keremberke/yolov8s-pcb-defect-segmentation

Supported Labels

['Dry_joint', 'Incorrect_installation', 'PCB_damage', 'Short_circuit']

How to use

pip install ultralyticsplus==0.0.23 ultralytics==8.0.21
  • Load model and perform prediction:
from ultralyticsplus import YOLO, render_result

# load model
model = YOLO('keremberke/yolov8s-pcb-defect-segmentation')

# set model parameters
model.overrides['conf'] = 0.25  # NMS confidence threshold
model.overrides['iou'] = 0.45  # NMS IoU threshold
model.overrides['agnostic_nms'] = False  # NMS class-agnostic
model.overrides['max_det'] = 1000  # 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)
print(results[0].masks)
render = render_result(model=model, image=image, result=results[0])
render.show()

More models available at: awesome-yolov8-models

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Inference API
Inference API (serverless) has been turned off for this model.

Dataset used to train keremberke/yolov8s-pcb-defect-segmentation

Evaluation results