# Copyright 2022 AI Singapore
#
# 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
#
# https://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,
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"""
Draws large bounding boxes with tags, over identified groups of bounding boxes.
"""
from typing import Any, Dict, List
import numpy as np
from peekingduck.pipeline.nodes.abstract_node import AbstractNode
from peekingduck.pipeline.nodes.draw.utils.bbox import draw_bboxes, draw_tags
from peekingduck.pipeline.nodes.draw.utils.constants import TOMATO
[docs]class Node(AbstractNode):
"""Draws large bounding boxes with tags over multiple object bounding boxes
which have been identified as belonging to the same group.
The :term:`large_groups` data type from :mod:`dabble.check_large_groups`,
and the ``groups`` key of the :term:`obj_attrs` data type from
:mod:`dabble.group_nearby_objs`, are inputs for this node which identifies
the different groups, and the group associated with each bounding box.
For better understanding, refer to
the :doc:`Group Size Checking use case </use_cases/group_size_checking>`.
Inputs:
|img_data|
|bboxes_data|
|obj_attrs_data|
:mod:`draw.group_bbox_and_tag` requires the ``groups`` attribute from
:mod:`dabble.group_nearby_objs`.
|large_groups_data|
Outputs:
|none_output_data|
Configs:
tag (:obj:`str`): **default = "LARGE GROUP!"**. |br|
The string message printed when a large group is detected.
.. versionchanged:: 1.2.0
:mod:`draw.group_bbox_and_tag` used to take in ``obj_tags``
(:obj:`List[str]`) as an input data type, which has been deprecated and
now subsumed under :term:`obj_attrs`. The same attribute is accessed by
using the ``groups`` key of :term:`obj_attrs`.
"""
def __init__(self, config: Dict[str, Any] = None, **kwargs: Any) -> None:
super().__init__(config, node_path=__name__, **kwargs)
def run(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
"""Draws large bounding boxes over multiple object bounding boxes
which have been identified as belonging to large groups.
Args:
inputs (dict): Dictionary with keys "img", "bboxes", "obj_attrs",
"large_groups".
Returns:
outputs (dict): Dictionary with keys "none".
"""
group_bboxes = self._get_group_bbox_coords(
inputs["large_groups"], inputs["bboxes"], inputs["obj_attrs"]["groups"]
)
group_tags = self._get_group_tags(inputs["large_groups"], self.tag)
# show labels set to False to reduce clutter on display
draw_bboxes(inputs["img"], group_bboxes, [], False, TOMATO)
draw_tags(inputs["img"], group_bboxes, group_tags, TOMATO)
return {}
def _get_config_types(self) -> Dict[str, Any]:
"""Returns dictionary mapping the node's config keys to respective types."""
return {"tag": str}
@staticmethod
def _get_group_bbox_coords(
large_groups: List[int], bboxes: List[np.ndarray], obj_groups: List[int]
) -> List[np.ndarray]:
"""For bboxes that belong to the same large group, get the coordinates of
a large bbox that combines all these individual bboxes. Repeat for all large
groups.
"""
group_bboxes = []
bboxes = np.array(bboxes)
obj_groups = np.array(obj_groups)
for group in large_groups:
# filter relevant bboxes, select top-left and bot-right corners
group_bbox = np.array([1.0, 1.0, 0.0, 0.0])
selected_bboxes = bboxes[obj_groups == group]
group_bbox[:2] = np.amin(selected_bboxes, axis=0)[:2]
group_bbox[2:] = np.amax(selected_bboxes, axis=0)[2:]
group_bboxes.append(group_bbox)
return group_bboxes
@staticmethod
def _get_group_tags(large_groups: List[int], tag: str) -> List[str]:
"""Creates a list of tags to be used for the draw_tags function."""
group_tags = [tag for _ in range(len(large_groups))]
return group_tags