Tensorflow Object Detection API クイックスタート ref: http://qiita.com/watanabe0621/items/08cc6c873066258435d6

file0.txt

git clone https://github.com/Jwata/tensorflow-pet-detector-quickstart
cd tensorflow-pet-detector-quickstart

file1.sh

pushd data
  wget http://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz
  wget http://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gz
  tar -xvf images.tar.gz
  tar -xvf annotations.tar.gz
popd

docker run -it -v `pwd`/data:/data jwata/tensorflow-object-detection \
  python object_detection/create_pet_tf_record.py \
  --label_map_path=/data/pet_label_map.pbtxt \
  --data_dir=/data \
  --output_dir=/data

file2.txt

ls data/pet_*.record
data/pet_train.record  data/pet_val.record

file3.sh

pushd data
  wget http://storage.googleapis.com/download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_coco_11_06_2017.tar.gz
  tar -xvf faster_rcnn_resnet101_coco_11_06_2017.tar.gz
  cp faster_rcnn_resnet101_coco_11_06_2017/* .
popd

file4.sh

docker run -d -v `pwd`/data:/data --name pet_detector_train jwata/tensorflow-object-detection \
  python object_detection/train.py \
  --logtostderr \
  --pipeline_config_path=/data/faster_rcnn_resnet101_pets.config \
  --train_dir=/data/train

file5.sh

docker run -d -v `pwd`/data:/data --name pet_detector_eval jwata/tensorflow-object-detection \
  python object_detection/eval.py \
  --logtostderr \
  --pipeline_config_path=/data/faster_rcnn_resnet101_pets.config \
  --checkpoint_dir=/data/train \
  --eval_dir=/data/eval

file6.txt

docker run -d -v `pwd`/data:/data -p 6006:6006 --name tensorboard \
  jwata/tensorflow-object-detection \
  tensorboard --logdir=/data

open http://localhost:6006