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133 lines
4.4 KiB
133 lines
4.4 KiB
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Numpy BoxList classes and functions."""
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import numpy as np
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class BoxList(object):
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"""Box collection.
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BoxList represents a list of bounding boxes as numpy array, where each
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bounding box is represented as a row of 4 numbers,
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[y_min, x_min, y_max, x_max]. It is assumed that all bounding boxes within a
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given list correspond to a single image.
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Optionally, users can add additional related fields (such as
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objectness/classification scores).
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"""
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def __init__(self, data):
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"""Constructs box collection.
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Args:
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data: a numpy array of shape [N, 4] representing box coordinates
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Raises:
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ValueError: if bbox data is not a numpy array
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ValueError: if invalid dimensions for bbox data
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"""
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if not isinstance(data, np.ndarray):
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raise ValueError('data must be a numpy array.')
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if len(data.shape) != 2 or data.shape[1] != 4:
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raise ValueError('Invalid dimensions for box data.')
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if data.dtype != np.float32 and data.dtype != np.float64:
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raise ValueError('Invalid data type for box data: float is required.')
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if not self._is_valid_boxes(data):
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raise ValueError('Invalid box data. data must be a numpy array of '
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'N*[y_min, x_min, y_max, x_max]')
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self.data = {'boxes': data}
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def num_boxes(self):
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"""Return number of boxes held in collections."""
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return self.data['boxes'].shape[0]
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def get_extra_fields(self):
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"""Return all non-box fields."""
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return [k for k in self.data.keys() if k != 'boxes']
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def has_field(self, field):
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return field in self.data
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def add_field(self, field, field_data):
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"""Add data to a specified field.
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Args:
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field: a string parameter used to speficy a related field to be accessed.
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field_data: a numpy array of [N, ...] representing the data associated
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with the field.
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Raises:
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ValueError: if the field is already exist or the dimension of the field
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data does not matches the number of boxes.
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"""
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if self.has_field(field):
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raise ValueError('Field ' + field + 'already exists')
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if len(field_data.shape) < 1 or field_data.shape[0] != self.num_boxes():
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raise ValueError('Invalid dimensions for field data')
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self.data[field] = field_data
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def get(self):
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"""Convenience function for accesssing box coordinates.
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Returns:
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a numpy array of shape [N, 4] representing box corners
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"""
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return self.get_field('boxes')
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def get_field(self, field):
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"""Accesses data associated with the specified field in the box collection.
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Args:
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field: a string parameter used to speficy a related field to be accessed.
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Returns:
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a numpy 1-d array representing data of an associated field
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Raises:
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ValueError: if invalid field
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"""
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if not self.has_field(field):
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raise ValueError('field {} does not exist'.format(field))
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return self.data[field]
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def get_coordinates(self):
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"""Get corner coordinates of boxes.
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Returns:
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a list of 4 1-d numpy arrays [y_min, x_min, y_max, x_max]
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"""
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box_coordinates = self.get()
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y_min = box_coordinates[:, 0]
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x_min = box_coordinates[:, 1]
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y_max = box_coordinates[:, 2]
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x_max = box_coordinates[:, 3]
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return [y_min, x_min, y_max, x_max]
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def _is_valid_boxes(self, data):
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"""Check whether data fullfills the format of N*[ymin, xmin, ymax, xmin].
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Args:
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data: a numpy array of shape [N, 4] representing box coordinates
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Returns:
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a boolean indicating whether all ymax of boxes are equal or greater than
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ymin, and all xmax of boxes are equal or greater than xmin.
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"""
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if data.shape[0] > 0:
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for i in range(data.shape[0]):
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if data[i, 0] > data[i, 2] or data[i, 1] > data[i, 3]:
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return False
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return True
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