# Copyright 2017 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.
# ==============================================================================
"""Extracts DELF features from a list of images, saving them to file.

The images must be in JPG format. The program checks if descriptors already
exist, and skips computation for those.
"""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import argparse
import os
import sys
import time

import numpy as np
from six.moves import range
import tensorflow as tf

from google.protobuf import text_format
from tensorflow.python.platform import app
from delf import delf_config_pb2
from delf import feature_io
from delf import utils
from delf import extractor

cmd_args = None

# Extension of feature files.
_DELF_EXT = '.delf'

# Pace to report extraction log.
_STATUS_CHECK_ITERATIONS = 100


def _ReadImageList(list_path):
  """Helper function to read image paths.

  Args:
    list_path: Path to list of images, one image path per line.

  Returns:
    image_paths: List of image paths.
  """
  with tf.io.gfile.GFile(list_path, 'r') as f:
    image_paths = f.readlines()
  image_paths = [entry.rstrip() for entry in image_paths]
  return image_paths


def main(unused_argv):
  # Read list of images.
  print('Reading list of images...')
  image_paths = _ReadImageList(cmd_args.list_images_path)
  num_images = len(image_paths)
  print(f'done! Found {num_images} images')

  # Parse DelfConfig proto.
  config = delf_config_pb2.DelfConfig()
  with tf.io.gfile.GFile(cmd_args.config_path, 'r') as f:
    text_format.Merge(f.read(), config)

  # Create output directory if necessary.
  if not tf.io.gfile.exists(cmd_args.output_dir):
    tf.io.gfile.makedirs(cmd_args.output_dir)

  # Tell TensorFlow that the model will be built into the default Graph.
  with tf.Graph().as_default():
    with tf.compat.v1.Session() as sess:
      init_op = tf.compat.v1.global_variables_initializer()
      sess.run(init_op)

      extractor_fn = extractor.MakeExtractor(sess, config)

      start = time.clock()
      for i in range(num_images):
        # Write to log-info once in a while.
        if i == 0:
          print('Starting to extract DELF features from images...')
        elif i % _STATUS_CHECK_ITERATIONS == 0:
          elapsed = (time.clock() - start)
          print(
              f'Processing image {i} out of {num_images}, last '
              f'{_STATUS_CHECK_ITERATIONS} images took {elapsed} seconds'
              )
          start = time.clock()

        # If descriptor already exists, skip its computation.
        out_desc_filename = os.path.splitext(os.path.basename(
            image_paths[i]))[0] + _DELF_EXT
        out_desc_fullpath = os.path.join(cmd_args.output_dir, out_desc_filename)
        if tf.io.gfile.exists(out_desc_fullpath):
          print(f'Skipping {image_paths[i]}')
          continue

        im = np.array(utils.RgbLoader(image_paths[i]))

        # Extract and save features.
        extracted_features = extractor_fn(im)
        locations_out = extracted_features['local_features']['locations']
        descriptors_out = extracted_features['local_features']['descriptors']
        feature_scales_out = extracted_features['local_features']['scales']
        attention_out = extracted_features['local_features']['attention']

        feature_io.WriteToFile(out_desc_fullpath, locations_out,
                               feature_scales_out, descriptors_out,
                               attention_out)


if __name__ == '__main__':
  parser = argparse.ArgumentParser()
  parser.register('type', 'bool', lambda v: v.lower() == 'true')
  parser.add_argument(
      '--config_path',
      type=str,
      default='delf_config_example.pbtxt',
      help="""
      Path to DelfConfig proto text file with configuration to be used for DELF
      extraction.
      """)
  parser.add_argument(
      '--list_images_path',
      type=str,
      default='list_images.txt',
      help="""
      Path to list of images whose DELF features will be extracted.
      """)
  parser.add_argument(
      '--output_dir',
      type=str,
      default='test_features',
      help="""
      Directory where DELF features will be written to. Each image's features
      will be written to a file with same name, and extension replaced by .delf.
      """)
  cmd_args, unparsed = parser.parse_known_args()
  app.run(main=main, argv=[sys.argv[0]] + unparsed)
