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# 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.
# ==============================================================================
"""Records previous preprocessing operations and allows them to be repeated.
Used with object_detection.core.preprocessor. Passing a PreprocessorCache
into individual data augmentation functions or the general preprocess() function
will store all randomly generated variables in the PreprocessorCache. When
a preprocessor function is called multiple times with the same
PreprocessorCache object, that function will perform the same augmentation
on all calls.
"""
from collections import defaultdict
class PreprocessorCache(object):
"""Dictionary wrapper storing random variables generated during preprocessing.
"""
# Constant keys representing different preprocessing functions
ROTATION90 = 'rotation90'
HORIZONTAL_FLIP = 'horizontal_flip'
VERTICAL_FLIP = 'vertical_flip'
PIXEL_VALUE_SCALE = 'pixel_value_scale'
IMAGE_SCALE = 'image_scale'
RGB_TO_GRAY = 'rgb_to_gray'
ADJUST_BRIGHTNESS = 'adjust_brightness'
ADJUST_CONTRAST = 'adjust_contrast'
ADJUST_HUE = 'adjust_hue'
ADJUST_SATURATION = 'adjust_saturation'
DISTORT_COLOR = 'distort_color'
STRICT_CROP_IMAGE = 'strict_crop_image'
CROP_IMAGE = 'crop_image'
PAD_IMAGE = 'pad_image'
CROP_TO_ASPECT_RATIO = 'crop_to_aspect_ratio'
RESIZE_METHOD = 'resize_method'
PAD_TO_ASPECT_RATIO = 'pad_to_aspect_ratio'
BLACK_PATCHES = 'black_patches'
ADD_BLACK_PATCH = 'add_black_patch'
SELECTOR = 'selector'
SELECTOR_TUPLES = 'selector_tuples'
SELF_CONCAT_IMAGE = 'self_concat_image'
SSD_CROP_SELECTOR_ID = 'ssd_crop_selector_id'
SSD_CROP_PAD_SELECTOR_ID = 'ssd_crop_pad_selector_id'
# 23 permitted function ids
_VALID_FNS = [ROTATION90, HORIZONTAL_FLIP, VERTICAL_FLIP, PIXEL_VALUE_SCALE,
IMAGE_SCALE, RGB_TO_GRAY, ADJUST_BRIGHTNESS, ADJUST_CONTRAST,
ADJUST_HUE, ADJUST_SATURATION, DISTORT_COLOR, STRICT_CROP_IMAGE,
CROP_IMAGE, PAD_IMAGE, CROP_TO_ASPECT_RATIO, RESIZE_METHOD,
PAD_TO_ASPECT_RATIO, BLACK_PATCHES, ADD_BLACK_PATCH, SELECTOR,
SELECTOR_TUPLES, SELF_CONCAT_IMAGE, SSD_CROP_SELECTOR_ID,
SSD_CROP_PAD_SELECTOR_ID]
def __init__(self):
self._history = defaultdict(dict)
def clear(self):
"""Resets cache."""
self._history = defaultdict(dict)
def get(self, function_id, key):
"""Gets stored value given a function id and key.
Args:
function_id: identifier for the preprocessing function used.
key: identifier for the variable stored.
Returns:
value: the corresponding value, expected to be a tensor or
nested structure of tensors.
Raises:
ValueError: if function_id is not one of the 23 valid function ids.
"""
if function_id not in self._VALID_FNS:
raise ValueError('Function id not recognized: %s.' % str(function_id))
return self._history[function_id].get(key)
def update(self, function_id, key, value):
"""Adds a value to the dictionary.
Args:
function_id: identifier for the preprocessing function used.
key: identifier for the variable stored.
value: the value to store, expected to be a tensor or nested structure
of tensors.
Raises:
ValueError: if function_id is not one of the 23 valid function ids.
"""
if function_id not in self._VALID_FNS:
raise ValueError('Function id not recognized: %s.' % str(function_id))
self._history[function_id][key] = value
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