Mac YOLO V9推理测试（基于ultralytics）

环境：

Mac M1 (MacOS Sonoma 14.3.1)

Python 3.11+PyTorch 2.1.2

一、准备工作

使用YOLO一般都会接触ultralytics这个框架，今天来试试用该框架进行YOLO V9模型的推理。

YOLOv9目前提供了四种模型下载：yolov9-c.pt、yolov9-e.pt、gelan-c.pt、gelan-e.pt

wget -P /Users/zhujiahui/Local/model/yolov9 -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-c.pt
wget -P /Users/zhujiahui/Local/model/yolov9 -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-e.pt
wget -P /Users/zhujiahui/Local/model/yolov9 -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/gelan-c.pt
wget -P /Users/zhujiahui/Local/model/yolov9 -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/gelan-e.pt

将下载好的模型放到指定的位置（实际发现这一步不用做，白费了）。

下载示例图片（也可手动下载放置），放到指定位置下：

wget -P /Users/zhujiahui/Local/dataset -q https://media.roboflow.com/notebooks/examples/dog.jpeg

安装Python依赖

pip install opencv-python
pip install ultralytics

二、推理

编写以下代码：

from ultralytics import YOLOdef yolov9_inference():yolo_model = YOLO("/Users/zhujiahui/Local/model/yolov9/yolov9-e.pt")yolo_model.info()if __name__ == '__main__':yolov9_inference()

直接运行，发现报错：

TypeError: ERROR ❌️ /Users/zhujiahui/Local/model/yolov9/yolov9-e.pt appears to be an Ultralytics YOLOv5 model originally trained with https://github.com/ultralytics/yolov5.
This model is NOT forwards compatible with YOLOv8 at https://github.com/ultralytics/ultralytics.
Recommend fixes are to train a new model using the latest 'ultralytics' package or to run a command with an official YOLOv8 model, i.e. 'yolo predict model=yolov8n.pt'

意思是说从https://github.com/WongKinYiu/yolov9下载的模型yolov9-e.pt与本训练推理框架（ultralytics）不match，必须使用经过ultralytics训练的模型。

于是改动如下，选用ultralytics提供的YOLO V9模型：

from ultralytics import YOLOdef yolov9_inference():yolo_model = YOLO("yolov9e.pt")yolo_model.info()if __name__ == '__main__':yolov9_inference()

首次运行会下载模型到当前代码所在的文件夹下

对示例图片进行检测：

from ultralytics import YOLOdef yolov9_inference():yolo_model = YOLO("yolov9e.pt")yolo_model.info()results = yolo_model.predict(source='/Users/zhujiahui/Local/dataset/dog.jpeg', save=True, save_txt=True)print(results)if __name__ == '__main__':yolov9_inference()

结果如下：

具体检测后的结果图片在runs/detect/predict/dog.jpeg下，效果：

原图	检测结果

输入的图片也可以通过OpenCV读入：

def yolov9_inference2():yolo_model = YOLO("yolov9e.pt")yolo_model.info()input_image = cv2.imread("/Users/zhujiahui/Local/dataset/dog.jpeg")results = yolo_model.predict(source=input_image, save=True, save_txt=True)print(results)