CSI相机 将MIPI-CSI（2）相机（例如Raspberry Pi版本2相机）与NVIDIA Jetson Nano Developer Kit一起使用的简单示例。 这是JetsonHacks上文章的支持代码： ://wp.me/p7ZgI9-19v 摄像机应安装在载板上的MIPI-CSI摄像机连接器中。 相机色带上的插针应面向Jetson Nano模块，条纹朝外。 新的Jetson Nano B01开发人员套件具有两个CSI摄像机插槽。 您可以将sensor_mode属性与nvarguscamerasrc一起使用以指定摄像机。 有效值为0或1（如果未指定，则默认为0），即 nvarguscamerasrc sensor_id=0 要测试相机： # Simple Test # Ctrl^C to exit # sensor_id selects the camera: 0

樱桃自动赛车（CAR） NCAT ECE高级设计项目 试运行 拆除

Jetson_Xavier_NX_Thermal_Design_Guide_TDG-09774-001_v1.1

jetson-nano的ROS镜像

jetson tx2 手动安装cuda9.0,此包为arm架构,为方便以后使用,特意上传保存.安装:里面有三个包,解压后,分别运行sudo dpkg -i cuda-xxxx.deb 命令来安装这3个包

This repo implements SSD (Single Shot MultiBox Detector). The implementation is heavily influenced by the projects ssd.pytorch and Detectron. The design goal is modularity and extensibility. Currently, it has MobileNetV1, MobileNetV2, and VGG based SSD/SSD-Lite implementations. It also has out-of-box support for retraining on Google Open Images dataset.

This repo implements SSD (Single Shot MultiBox Detector). The implementation is heavily influenced by the projects ssd.pytorch and Detectron. The design goal is modularity and extensibility. Currently, it has MobileNetV1, MobileNetV2, and VGG based SSD/SSD-Lite implementations. It also has out-of-box support for retraining on Google Open Images dataset.

This repo implements SSD (Single Shot MultiBox Detector). The implementation is heavily influenced by the projects ssd.pytorch and Detectron. The design goal is modularity and extensibility. Currently, it has MobileNetV1, MobileNetV2, and VGG based SSD/SSD-Lite implementations. It also has out-of-box support for retraining on Google Open Images dataset.

2021年愿景 2021年第一个FRC银河搜寻任务视觉代码。该代码将能够使用Nvidia Jetson Nano和YOLOv5在运动场上运行实时目标检测。 YOLOv5对象检测信息/文档 YOLOv5是用于实时对象检测的AI对象检测库。 资源 用法 注意：所有软件包和模块都使用virtualenv坐在虚拟环境中。要为此仓库运行任何命令，您必须输入venv。 FROM YOLOv5_trained_model目录键入source venv/bin/activate以启动环境变量 powercell_model / YOLOv5_Trained_Model目录中的文件都是经过训练的ML模型。它由data.yaml，custom_yolov5s.yaml和best.pt（即经过训练的模型文件）组成。 注意：Roboflow用于创建yolov5格式。 要获取（或更新）训练后的模型，请执行以下操作

deepstream_sdk_v4.0.2_jetson.tbz2