YOLO钢轨缺口识别

yolov8在钢轨故障识别的应用

##训练
from ultralytics import YOLO
if __name__ =="__main__":
    model = YOLO("yolov8n.pt")
    model.train(
        data="/gap.yaml",
        epochs=100,
        imgsz=640,
        device="0"##设备可使用cpu，值改为"cpu"
        )

from ultralytics import YOLO


##预测
from ultralytics import YOLO

# Load a model
model = YOLO("/best.pt")  # pretrained YOLOv8n model

# Run batched inference on a list of images
results = model(["/aug_prefix_0_1352.jpg"])  # return a list of Results objects

# Process results list
for result in results:
    boxes = result.boxes  # Boxes object for bounding box outputs
    masks = result.masks  # Masks object for segmentation masks outputs
    keypoints = result.keypoints  # Keypoints object for pose outputs
    probs = result.probs  # Probs object for classification outputs
    obb = result.obb  # Oriented boxes object for OBB outputs
    result.show()  # display to screen
    result.save(filename="C:/Users/yusialone/Desktop/3d/its_rail/jieguo/result.jpg")  # save to disk