Turbot-DL入门教程篇-Yolo v3(jetpack3.3)验证例子

Turbot-DL入门教程篇--验证Yolo v3(jetpack3.3)验证例子

说明：

• 介绍在tx2下验证Yolo v3
• 环境：jetpack3.3 + CUDA9.0 + opencv 3.3.1

步骤：

测试yolov3

• 进入Yolo目录

$ cd ~/dl/Yolo/darknet

• 测试运行

$ ./darknet detect cfg/yolov3.cfg yolov3.weights data/dog.jpg


Loading weights from yolov3.weights...Done!
data/dog.jpg: Predicted in 0.669016 seconds.
dog: 100%
truck: 92%
bicycle: 99%

• 测试运行

$ ./darknet detect cfg/yolov3-tiny.cfg yolov3-tiny.weights data/dog.jpg


Loading weights from yolov3-tiny.weights...Done!
data/dog.jpg: Predicted in 0.035101 seconds.
dog: 57%
car: 51%
truck: 56%
car: 62%
bicycle: 59%

• 使用摄像头进行实时检测

$ ./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights

• 或使用视频文件

$ ./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights <video file>

• 或使用板载摄像头

$ ./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights "nvcamerasrc ! video/x-raw(memory:NVMM), width=(int)1280, height(int)720, format=(string)I420, framerate=(fraction)30/1 ! nvvidconv flip-method=0 ! video/x-raw, format=(string)BGRx ! videoconvert ! video/x-raw, format=(string)BGR ! appsink"

参考：

• https://pjreddie.com/darknet/yolo/
• https://pjreddie.com/darknet/install/