支持导入预训练模型辅助标注，
https://github.com/SkalskiP/make-sense
但是需要先将yolov5模型(不支持v8)转换为tensorflowjs模型
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| conda activate yolov5
pip install tensorflowjs==2.8.5
python export --weight your_best.pt --include tfjs
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npm安装方式报错了，只好使用docker。windows安装docker，下载make scense源码
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| git clone https://github.com/SkalskiP/make-sense.git
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官方给出的下一步骤是直接构建镜像，但是在windows上面，Dockerfile不使用EXPOSE会无法暴露容器的镜像，于是需要先在Dockerfile中添加一行EXPOSE 3000
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| FROM node:16.16.0
RUN apt-get update && apt-get -y install git && rm -rf /var/lib/apt/lists/*
COPY ./ /make-sense
RUN cd /make-sense && \
npm install
WORKDIR /make-sense
EXPOSE 3000
ENTRYPOINT ["npm", "run", "dev"]
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执行构建命令，先进入源码目录再构建
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| cd make-sense
# Build Docker Image
docker build -t make-sense -f docker/Dockerfile .
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运行容器
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| # Run Docker Image as Service
docker run -dit -p 3000:3000 --restart=always --name=make-sense make-sense
# Get Docker Container Logs
docker logs make-sense
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然后打开浏览器就能打开数据标注网站了。
https://public.roboflow.com
参考视频:
https://www.bilibili.com/video/BV1GM4y1m7nm?spm_id_from=333.788.videopod.sections&vd_source=cdd8cee3d9edbcdd99486a833d261c72
