2 篇文章带有标签 “计算机视觉”

构建YOLOv4容器应用在自定义数据集上

FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04
LABEL maintainer="wang-junjian@qq.com"

#auto install tzdata(opencv depend)
ENV DEBIAN_FRONTEND=noninteractive

RUN apt-get update && apt-get install -y \
    git wget nano \
    libopencv-dev python3-opencv \
    && rm -rf /var/lib/apt/lists/*

#set your localtime
RUN ln -fs /usr/share/zoneinfo/Asia/Shanghai /etc/localtime

WORKDIR /
// ...
  • 构建容器
docker build -t darknet:latest-gpu-yolov4 .
  • 训练的样本:train.txt
images/IMG_9255.JPG
images/IMG_9266.JPG
images/IMG_9280.JPG
  • 验证的样本:valid.txt
images/IMG_9263.JPG
  • 标注类型:voc.names
close
open

使用Darknet在自定义数据集上训练YOLOv3

  • 训练的样本:train.txt
yolos/IMG_9255.JPG
yolos/IMG_9266.JPG
yolos/IMG_9280.JPG
  • 验证的样本:valid.txt
yolos/IMG_9263.JPG
  • 标注类型:voc.names
close
open
  • 配置文件:voc.data
classes= 2
train  = cfg/train.txt
valid  = cfg/valid.txt
names = cfg/voc.names
backup = backup
  • 修改YOLO神经网络文件:yolov3.cfg
603行:filters=21    # (classes + 5)*3
610行:classes=2
689行:filters=21
696行:classes=2
776行:filters=21
783行:classes=2
  • 使用LabelImg标注图像样本集
# python3 labelImg.py [图像目录] [标注名字文件] [标注目录]
python3 labelImg.py open-close/yolos/ open-close/cfg/yolo.names
  • 下载基于imagenet的预训练模型 darknet53.conv.74
wget https://pjreddie.com/media/files/darknet53.conv.74