1. 克隆仓库

从官网下载Yolov11到本地。

git clone git@github.com:ultralytics/ultralytics.git

2. 安装环境依赖

pip install -e . -i https://pypi.mirrors.ustc.edu.cn/simple/

3. 训练、验证、推理以及onnx模型导出

from ultralytics import YOLO

# Load a model
model = YOLO("/home/mjy/ultralytics/ultralytics/cfg/models/11/yolo11.yaml")

# Train the model
train_results = model.train(
    data="/home/mjy/ultralytics/ultralytics/cfg/datasets/coco128.yaml",  # path to dataset YAML
    epochs=100,  # number of training epochs
    imgsz=640,  # training image size
    device="0",  # device to run on, i.e. device=0 or device=0,1,2,3 or device=cpu
)

# Evaluate model performance on the validation set
metrics = model.val()

# Perform object detection on an image
results = model("/home/mjy/ultralytics/ultralytics/assets/bus.jpg")
results[0].show()

# Export the model to ONNX format
path = model.export(format="onnx")  # return path to exported model