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TX2入门教程软件篇-安装Yolo v3(jetpack3.3)

TX2入门教程软件篇-安装Yolo v3(jetpack3.3)

说明:

  • 介绍在tx2下安装安装Yolo v3
  • 环境:jetpack3.3 + CUDA9.0 + opencv 3.3.1

步骤:

  • 先增加swap分区,要不后面运行测试容易出现内存不足导致失败,参考增加swap教程
  • 下载darknet
mkdir -p ~/dl/darknet
cd ~/dl/darknet
git clone https://github.com/pjreddie/darknet.git
cd darknet
  • 修改Makefile文件,启用GPU和opencv
GPU=1
CUDNN=1
OPENCV=1
OPENMP=0
DEBUG=0
 
ARCH= -gencode arch=compute_53,code=[sm_53,compute_53] \
      -gencode arch=compute_62,code=[sm_62,compute_62]
#      -gencode arch=compute_20,code=[sm_20,sm_21] \ This one is deprecated?
# This is what I use, uncomment if you know your arch and want to specify
# ARCH= -gencode arch=compute_52,code=compute_52
  • 编译
make -j4
  • 判断成功
./darknet 
usage: ./darknet <function>

测试yolov3

  • 下载训练好的yolov3模型
wget https://pjreddie.com/media/files/yolov3.weights
  • 测试运行
./darknet detect cfg/yolov3.cfg yolov3.weights data/dog.jpg
  • 下载训练好的tiny yolov3模型
wget https://pjreddie.com/media/files/yolov3-tiny.weights
  • 测试运行
./darknet detect cfg/yolov3-tiny.cfg yolov3-tiny.weights data/dog.jpg
  • 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/

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