The GPU is not used when running detection with YOLOv5 When I run the YOLOv5 detection code, it still uses CPU And it causes the detection process to be slow, I get fps = 0 4 For installation, CUDA has been activated but the CUDA on the Jetson nano is still not used Please give me an explanation why it happened and what is the solution?
python - yolov5 not training on custom dataset - Stack Overflow The code in yolov5 will turn the word "images" in the absolute path mentioned above "D:\yolov5\datasets\mydata\images\IMG_000001 jpg" into "labels" automatically to find your labels file So you dont need to mention your labelfile's path in this file And that is exactly why you need to organize your directory like that
yolov5训练得到best. pt文件，如何在其他项目中打开并使用？ - 知乎 以下内容由 AI 生成，仅供参考 要在一个新的项目中打开并使用YOLov5训练得到的 best pt 文件，您可以按照以下步骤操作： 使用PyTorch加载模型 如果您希望直接在Python脚本或其他应用程序中使用该模型，可以通过PyTorch库来实现。
Jetson Orin NX + JetPack 6. 2: Best PyTorch Version YOLOv5 Deployment . . . Hello, I’m currently using a Jetson Orin NX 16GB module running JetPack 6 2, and I would like to deploy YOLOv5 on it with maximum inference speed and minimal latency I’ve noticed that some users reported compatibility issues between the latest Ultralytics library and JetPack 6 2 Therefore, I’m planning to use the original YOLOv5 GitHub implementation (v6 2 or earlier) and optimize it