#!/bin/bash
# Copyright 2018 The TensorFlow Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
#
# Script to preprocess the Cityscapes dataset. Note (1) the users should register
# the Cityscapes dataset website: https://www.cityscapes-dataset.com/downloads/ to
# download the dataset, and (2) the users should run the script provided by Cityscapes
# `preparation/createTrainIdLabelImgs.py` to generate the training groundtruth.
#
# Usage:
#   bash ./preprocess_cityscapes.sh
#
# The folder structure is assumed to be:
#  + data
#    - build_cityscapes_data.py
#    + cityscapes
#      + cityscapesscripts
#      + gtFine
#      + leftImg8bit
#

# Exit immediately if a command exits with a non-zero status.
set -e

CURRENT_DIR=$(pwd)
WORK_DIR="."

cd "${CURRENT_DIR}"

# Root path for PASCAL VOC 2012 dataset.
CITYSCAPES_ROOT="${WORK_DIR}/cityscapes"

# Build TFRecords of the dataset.
# First, create output directory for storing TFRecords.
OUTPUT_DIR="${CITYSCAPES_ROOT}/tfrecord"
mkdir -p "${OUTPUT_DIR}"

BUILD_SCRIPT="${WORK_DIR}/build_cityscapes_data.py"

echo "Converting Cityscapes dataset..."
python "${BUILD_SCRIPT}" \
  --cityscapes_root="${CITYSCAPES_ROOT}" \
  --output_dir="${OUTPUT_DIR}" \