Source code for

# 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.
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# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
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# ==============================================================================
"""Numpy BoxList classes and functions."""

from typing import List, Tuple

import numpy as np

[docs]class BoxList(object): """A list of bounding boxes as a [y_min, x_min, y_max, x_max] numpy array. It is assumed that all bounding boxes within a given list correspond to a single image. Optionally, users can add additional related fields (such as objectness/classification scores). """
[docs] def __init__(self, data: np.ndarray): """Constructor. Args: data (np.ndarray): Box coords as a [N, 4] numpy array. Raises: ValueError: If bbox data is not a numpy array. ValueError: If invalid dimensions for bbox data. """ if not isinstance(data, np.ndarray): raise ValueError('data must be a numpy array.') if len(data.shape) != 2 or data.shape[1] != 4: raise ValueError('Invalid dimensions for box data.') if data.dtype != np.float32 and data.dtype != np.float64: raise ValueError( 'Invalid data type for box data: float is required.') if not self._is_valid_boxes(data): raise ValueError('Invalid box data. data must be a numpy array of ' 'N*[y_min, x_min, y_max, x_max]') = {'boxes': data}
[docs] def num_boxes(self) -> int: """Return number of boxes held in collections.""" return['boxes'].shape[0]
[docs] def get_extra_fields(self) -> List[str]: """Return all non-box fields.""" return [k for k in if k != 'boxes']
[docs] def has_field(self, field) -> bool: return field in
[docs] def add_field(self, name: str, data: np.ndarray) -> None: """Add data to a specified field. Args: name (str): Field name. data (np.ndarray): Field data: box coords as a [N, 4] numpy array. Raises: ValueError: If name already exists. ValueError: If the dimension of the field data does not matche the number of boxes. """ if self.has_field(name): raise ValueError('Field ' + name + 'already exists') if len(data.shape) < 1 or len(data) != self.num_boxes(): raise ValueError('Invalid dimensions for name data')[name] = data
[docs] def get(self): """Shorthand for get_field('boxes').""" return self.get_field('boxes')
[docs] def get_field(self, name: str) -> np.ndarray: """Get data for field. Args: name (str): Field name. Returns: np.ndarray: The data associated with the field. Raises: ValueError: if invalid field. """ try: return[name] except KeyError: raise ValueError(f'field {name} does not exist')
[docs] def get_coordinates( self) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: """Get corner coordinates of boxes. Returns: Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: a 4-tuple of 1-d numpy arrays [y_min, x_min, y_max, x_max]. """ boxes = self.get_field('boxes') return tuple(boxes.T)
def _is_valid_boxes(self, data: np.ndarray) -> bool: """Check whether data fullfills the format of N*[ymin, xmin, ymax, xmin]. Args: data (np.ndarray): Box coords as a [N, 4] numpy array. Returns: bool: Whether ymin <= ymax and xmin <= xmax. """ ymin, xmin, ymax, xmax = data.T return (ymin <= ymax).all() and (xmin <= xmax).all()