docker build -f ./dockerfiles/gpu/Dockerfile -t logost.tensorflow .
nvidia-docker run -it -v $PWD:/code --net=host --ipc=host logost.tensorflow:latest /bin/bash

mkdir dataset
./scripts/load_data.sh
python ./logos/data_preprocessing.py
python ./logos/create_tf_records.py

export PATH_TO_YOUR_PIPELINE_CONFIG=...
export PATH_TO_TRAIN_DIR=...
export PATH_TO_EVAL_DIR=...
export TRAIN_PATH=...
export EXPORT_DIR=...

python object_detection/train.py \
    --logtostderr \
    --pipeline_config_path=${PATH_TO_YOUR_PIPELINE_CONFIG} \
    --train_dir={PATH_TO_TRAIN_DIR}

python object_detection/eval.py \
    --logtostderr \
    --pipeline_config_path=${PATH_TO_YOUR_PIPELINE_CONFIG} \
    --checkpoint_dir=${PATH_TO_TRAIN_DIR} \
    --eval_dir=${PATH_TO_TRAIN_DIR}

python object_detection/export_inference_graph.py \
    --input_type image_tensor \
    --pipeline_config_path=${PATH_TO_YOUR_PIPELINE_CONFIG} \
    --trained_checkpoint_prefix=${TRAIN_PATH} \
    --output_directory=${EXPORT_DIR}