tensorrt yolov8

在使用TensorRT加速Yolov8时，你可以按照以下步骤进行操作：
1. 首先，创建一个新的Python环境并安装依赖项，可以使用以下命令：

conda create -n yolov8 python==3.8 -y
conda activate yolov8
pip install ultralytics==8.0.5
pip install onnx==1.12.0

2. 下载Yolov8的官方权重文件(".pt"文件)，可以从以下链接下载所需的权重文件：

https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n.pt
https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s.pt
https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m.pt
https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l.pt
https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x.pt
https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x6.pt

3. 使用以下命令将权重文件转换为ONNX格式的模型：

python -c "from yolov5 import YOLOV5; YOLOV5(task='segment', mode='export', model='yolov8[n s m l x]-seg.pt', format='onnx', opset=12)"

请注意，你需要将``替换为所需的Yolov8版本，例如`yolov8s`或`yolov8x`等。这将在models/目录下生成相应的ONNX模型文件。
引用<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
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