构建RetinaNet容器应用在自定义数据集上

训练自己的数据集

标注数据 LabelImg

#标注后的目录结构
project
└── labelimg
    ├── 20190128155421222575013.jpg
    ├── 20190128155421222575013.xml
    ├── 20190128155703035712899.jpg
    ├── 20190128155703035712899.xml
    ├── 20190129091126392737624.jpg
    └── 20190129091126392737624.xml

拉取容器镜像

$ sudo docker pull gouchicao/keras-retinanet:latest

运行容器

$ sudo docker run -it --runtime=nvidia --name=keras-retinanet -p 8888:8888 -p 6006:6006 \
              -v /home/wjunjian/ailab/datasets/helmet:/keras-retinanet/project \
              gouchicao/keras-retinanet bash

voc转csv格式，分隔数据集

$ python voc2csv.py --data_dir=project/labelimg/ --output_dir=project/dataset

#生成的目录结构
project
├── dataset
│   ├── class.csv
│   ├── train
│   │   ├── 20190128155421222575013.jpg
│   │   ├── 20190128155421222575013.xml
│   │   ├── 20190129091126392737624.jpg
│   │   └── 20190129091126392737624.xml
│   ├── train.csv
│   ├── val
│   │   ├── 20190128155703035712899.jpg
│   │   └── 20190128155703035712899.xml
│   └── val.csv
└── labelimg
    ├── 20190128155421222575013.jpg
    ├── 20190128155421222575013.xml
    ├── 20190128155703035712899.jpg
    ├── 20190128155703035712899.xml
    ├── 20190129091126392737624.jpg
    └── 20190129091126392737624.xml

模型训练

$ python keras-retinanet/keras_retinanet/bin/train.py --tensorboard-dir=project/logs --snapshot-path project/snapshots \
  csv project/dataset/train.csv project/dataset/class.csv --val-annotations project/dataset/val.csv
$ ll -h project/models/resnet50_csv_01.h5
-rw-r--r-- 1 root     root     417M 7月  27 22:58 resnet50_csv_01.h5

训练过程可视化 TensorBoard
```
$ tensorboard --logdir=project/logs --bind_all
```
在本机浏览器中访问网址:http://localhost:6006

模型评估

$ python keras-retinanet/keras_retinanet/bin/evaluate.py csv project/dataset/val.csv project/dataset/class.csv \
  project/snapshots/resnet50_csv_01.h5 --convert-model

模型转换

$ mkdir project/inference
$ python keras-retinanet/keras_retinanet/bin/convert_model.py --no-class-specific-filter \
  project/snapshots/resnet50_csv_01.h5 project/inference/model.h5
$ ll -h project/inference/model.h5
-rw-r--r-- 1 root     root     140M 7月  27 23:14 model.h5

模型预测

$ python predict.py --model project/inference/model.h5 \
  --class_csv project/dataset/class.csv \
  --data_dir project/test \
  --predict_dir project/predict

训练自己的数据集

参考资料