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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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