使用RetinaNet算法训练自定义数据集
训练自己的数据集
标注数据
#标注后的目录结构
project
└── labelimg
├── 20190128155421222575013.jpg
├── 20190128155421222575013.xml
├── 20190128155703035712899.jpg
├── 20190128155703035712899.xml
├── 20190129091126392737624.jpg
└── 20190129091126392737624.xml
构建镜像
- 拉取
$ sudo docker pull gouchicao/keras-retinanet:latest
- 手动构建
FROM gouchicao/tensorflow:2.2.0-gpu-jupyter-opencv4-pillow-wget-curl-git-nano
LABEL maintainer="wang-junjian@qq.com"
WORKDIR /
RUN mkdir -p /root/.keras/models/ && \
wget -O /root/.keras/models/ResNet-50-model.keras.h5 https://github.com/fizyr/keras-models/releases/download/v0.0.1/ResNet-50-model.keras.h5
RUN git clone --depth 1 --recurse-submodules https://github.com/gouchicao/keras-retinanet.git
WORKDIR /keras-retinanet/keras-retinanet
# 提前安装指定版本 keras==2.3.1 解决错误 TypeError: type object got multiple values for keyword argument 'training'
RUN pip install keras==2.3.1 && \
pip install . && \
python setup.py build_ext --inplace
WORKDIR /keras-retinanet