Deploy YOLO-Seg ONNX model with ONNX Runtime
Project description
yolo-seg-ort
yolo-seg-ort
采用纯ONNX Runtime实现YOLOv11-seg的onnx模型。
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1. 模型转换
from ultralytics import YOLO
# Load the YOLO11 model
model = YOLO("best.pt")
# Export the model to ONNX format
model.export(format="onnx") # creates 'yolo11n.onnx'
2. 安装依赖
pip install -r requirements.txt
3. 用法
from yolo_seg_ort import YOLOSeg
import cv2
onnx_path = "best.onnx"
image_path = "test.jpg"
image = cv2.imread(image_path)
model = YOLOSeg(
onnx_model=onnx_path,
classes=["Grass", "Ground", "Ramp", "Road", "Stairs"],
conf=0.25,
iou=0.7,
imgsz=640,
)
result = model(image)
if result:
result[0].save("./results.jpg")
# result[0].show()
else:
print("未检测到任何对象或结果为空。")
4. 结果
5. 贡献者
6. 许可证
本项目采用 MIT 许可证。有关详细信息,请查看 LICENSE 文件。
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