yolov5_ros

Environments

We have tested this repository on both x86 Ubuntu 20.04 and Nvidia Xavier NX.

You can set these model_name, nms_threshold, conf_thresh and batch_size in the following launch file

roslaunch yolov5_ros yolov5_ros.launch

- Subscriber: /usb_cam/image_raw    [sensor_msgs/Image]
- Publisher: /yolov5_video          [sensor_msgs/Image]

Engines are specific to the exact hardware and software they were built on. Below are the steps to build the engine file with your CPU/GPU.

Remember to checkout the v5.0 branch in ultralytics/yolov5
Train your custom model with pretrained weight python train.py --img 640 --batch 32 --epochs 500 --data custom_model.yaml --weights yolov5l.pt
Generate .wts from pytorch with .pt usging the gen_wts.py script
Remember to update the Number of classes defined in yololayer.h
Build the repo and generate the engine file with the following command: rosrun yolov5_ros yolov5_engine -s (path-to- .wts file) custom_model.engine l