leopoldo-zugasti
3 年前
当前提交
30dc05b5
共有 11 个文件被更改，包括 747 次插入 和 105 次删除
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5com.unity.perception/Editor/Pyrception/PyrceptionInstaller.cs
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261com.unity.perception/Editor/Pyrception/pyrception-utils/pyrception_utils/preview.py
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73com.unity.perception/Editor/Pyrception/pyrception-utils/pyrception_utils/pyrception.py
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2com.unity.perception/Editor/Pyrception/pyrception-utils/requirements.txt
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2com.unity.perception/Editor/Pyrception/pyrception-utils/setup.py
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2com.unity.perception/Runtime/GroundTruth/Labelers/BoundingBox3DLabeler.cs
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3com.unity.perception/Runtime/GroundTruth/PerceptionCamera.cs
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311com.unity.perception/Editor/Pyrception/pyrception-utils/pyrception_utils/bbox.py
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7com.unity.perception/Editor/Pyrception/pyrception-utils/pyrception_utils/bbox.py.meta
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179com.unity.perception/Editor/Pyrception/pyrception-utils/pyrception_utils/bbox3d_plot.py
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7com.unity.perception/Editor/Pyrception/pyrception-utils/pyrception_utils/bbox3d_plot.py.meta
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import math |
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import numpy as np |
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from pyquaternion import Quaternion |
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def group_bbox2d_per_label(bboxes): |
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"""Group 2D bounding boxes with same label. |
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Args: |
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bboxes (list[BBox2D]): a list of 2D bounding boxes |
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Returns: |
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dict: a dictionary of 2d boundign box group. |
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{label1: [bbox1, bboxes2, ...], label2: [bbox1, ...]} |
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""" |
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bboxes_per_label = {} |
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for box in bboxes: |
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if box.label not in bboxes_per_label: |
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bboxes_per_label[box.label] = [] |
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bboxes_per_label[box.label].append(box) |
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return bboxes_per_label |
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class BBox2D: |
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"""Canonical Representation of a 2D bounding box. |
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Attributes: |
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label (str): string representation of the label. |
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x (float): x pixel coordinate of the upper left corner. |
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y (float): y pixel coordinate of the upper left corner. |
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w (float): width (number of pixels)of the bounding box. |
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h (float): height (number of pixels) of the bounding box. |
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score (float): detection confidence score. Default is set to score=1. |
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if this is a ground truth bounding box. |
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Examples: |
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Here is an example about how to use this class. |
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.. code-block:: |
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>>> gt_bbox = BBox2D(label='car', x=2, y=6, w=2, h=4) |
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>>> gt_bbox |
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"label='car'|score=1.0|x=2.0|y=6.0|w=2.0|h=4.0" |
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>>> pred_bbox = BBox2D(label='car', x=2, y=5, w=2, h=4, score=0.79) |
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>>> pred_bbox.area |
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8 |
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>>> pred_bbox.intersect_with(gt_bbox) |
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True |
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>>> pred_bbox.intersection(gt_bbox) |
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6 |
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>>> pred_bbox.union(gt_bbox) |
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10 |
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>>> pred_bbox.iou(gt_bbox) |
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0.6 |
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""" |
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def __init__(self, label, x, y, w, h, score=1.0): |
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""" Initialize 2D bounding box object |
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Args: |
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label (str): string representation of the label |
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x (float): x pixel coordinate of the upper left corner |
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y (float): y pixel coordinate of the upper left corner |
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w (float): width (number of pixels)of the bounding box |
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h (float): height (number of pixels) of the bounding box |
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score (float): detection confidence score |
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""" |
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self.label = label |
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self.x = x |
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self.y = y |
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self.w = w |
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self.h = h |
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self.score = score |
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|
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def __repr__(self): |
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return ( |
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f"label={self.label}|score={self.score:.2f}|" |
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f"x={self.x:.2f}|y={self.y:.2f}|w={self.w:.2f}|h={self.h:.2f}" |
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) |
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def __eq__(self, other): |
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return ( |
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self.x == other.x |
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and self.y == other.y |
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and self.w == other.w |
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and self.h == other.h |
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and self.label == other.label |
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and math.isclose(self.score, other.score, rel_tol=1e-07) |
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) |
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@property |
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def area(self): |
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"""Calculate area of this bounding box |
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Returns: |
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width x height of the bound box |
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""" |
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return self.w * self.h |
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def intersect_with(self, other): |
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"""Check whether this box intersects with other bounding box |
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Args: |
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other (BBox2D): other bounding box object to check intersection |
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Returns: |
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True if two bounding boxes intersect, False otherwise |
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""" |
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if self.x > other.x + other.w: |
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return False |
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if other.x > self.x + self.w: |
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return False |
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if self.y + self.h < other.y: |
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return False |
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if self.y > other.y + other.h: |
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return False |
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return True |
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def intersection(self, other): |
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"""Calculate the intersection area with other bounding box |
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Args: |
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other (BBox2D): other bounding box object to calculate intersection |
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Returns: |
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float of the intersection area for two bounding boxes |
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""" |
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x1 = max(self.x, other.x) |
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y1 = max(self.y, other.y) |
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x2 = min(self.x + self.w, other.x + other.w) |
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y2 = min(self.y + self.h, other.y + other.h) |
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return (x2 - x1) * (y2 - y1) |
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def union(self, other, intersection_area=None): |
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"""Calculate union area with other bounding box |
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Args: |
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other (BBox2D): other bounding box object to calculate union |
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intersection_area (float): pre-calculated area of intersection |
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Returns: |
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float of the union area for two bounding boxes |
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""" |
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area_a = self.area |
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area_b = other.area |
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if not intersection_area: |
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intersection_area = self.intersection(other) |
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return float(area_a + area_b - intersection_area) |
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def iou(self, other): |
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"""Calculate intersection over union area with other bounding box |
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.. math:: |
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IOU = \\frac{intersection}{union} |
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Args: |
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other (BBox2D): other bounding box object to calculate iou |
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Returns: |
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float of the union area for two bounding boxes |
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""" |
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# if boxes don't intersect |
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if not self.intersect_with(other): |
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return 0 |
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intersection_area = self.intersection(other) |
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union_area = self.union(other, intersection_area=intersection_area) |
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# intersection over union |
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iou = intersection_area / union_area |
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return iou |
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class BBox3D: |
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""" |
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Class for 3d bounding boxes which can either be predictions or |
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ground-truths. This class is the primary representation in this repo of 3d |
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bounding boxes and is based off of the Nuscenes style dataset. |
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""" |
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def __init__( |
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self, |
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translation, |
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size, |
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label, |
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sample_token, |
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score=1, |
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rotation: Quaternion = Quaternion(), |
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velocity=(np.nan, np.nan, np.nan), |
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): |
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self.sample_token = sample_token |
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self.translation = translation |
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self.size = size |
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self.width, self.height, self.length = size |
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self.rotation = rotation |
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self.velocity = velocity |
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self.label = label |
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self.score = score |
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def _local2world_coordinate(self, x): |
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""" |
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Args: |
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x: vector describing point (x,y,z) in local coordinates (where the |
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center of the box is 0,0,0) |
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Returns: the x,y,z coordinates of the input point in global coordinates |
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""" |
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y = np.array(self.translation) + self.rotation.rotate(x) |
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return y |
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@property |
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def back_left_bottom_pt(self): |
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""" |
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Returns: :py:class:`float`: Back-left-bottom point. |
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""" |
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p = np.array([-self.width / 2, -self.height / 2, -self.length / 2]) |
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p = self._local2world_coordinate(p) |
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return p |
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@property |
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def front_left_bottom_pt(self): |
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""" |
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:py:class:`float`: Front-left-bottom point. |
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""" |
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p = np.array([-self.width / 2, -self.height / 2, self.length / 2]) |
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p = self._local2world_coordinate(p) |
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return p |
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@property |
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def front_right_bottom_pt(self): |
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""" |
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:py:class:`float`: Front-right-bottom point. |
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""" |
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p = np.array([self.width / 2, -self.height / 2, self.length / 2]) |
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p = self._local2world_coordinate(p) |
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return p |
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@property |
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def back_right_bottom_pt(self): |
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""" |
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:py:class:`float`: Back-right-bottom point. |
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""" |
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p = np.array([self.width / 2, -self.height / 2, -self.length / 2]) |
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p = self._local2world_coordinate(p) |
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return p |
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@property |
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def back_left_top_pt(self): |
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""" |
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:py:class:`float`: Back-left-top point. |
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""" |
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p = np.array([-self.width / 2, self.height / 2, -self.length / 2]) |
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p = self._local2world_coordinate(p) |
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return p |
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@property |
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def front_left_top_pt(self): |
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""" |
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:py:class:`float`: Front-left-top point. |
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""" |
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p = np.array([-self.width / 2, self.height / 2, self.length / 2]) |
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p = self._local2world_coordinate(p) |
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return p |
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@property |
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def front_right_top_pt(self): |
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""" |
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:py:class:`float`: Front-right-top point. |
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""" |
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p = np.array([self.width / 2, self.height / 2, self.length / 2]) |
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p = self._local2world_coordinate(p) |
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return p |
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@property |
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def back_right_top_pt(self): |
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""" |
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:py:class:`float`: Back-right-top point. |
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""" |
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p = np.array([self.width / 2, self.height / 2, -self.length / 2]) |
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p = self._local2world_coordinate(p) |
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return p |
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@property |
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def p(self) -> np.ndarray: |
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""" |
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Returns: list of all 8 corners of the box beginning with the the bottom |
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four corners and then the top |
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four corners, both in counterclockwise order (from birds eye view) |
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beginning with the back-left corner |
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""" |
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x = np.vstack( |
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[ |
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self.back_left_bottom_pt, |
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self.front_left_bottom_pt, |
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self.front_right_bottom_pt, |
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self.back_right_bottom_pt, |
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self.back_left_top_pt, |
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self.front_left_top_pt, |
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self.front_right_top_pt, |
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self.back_right_top_pt, |
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] |
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) |
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return x |
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|
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fileFormatVersion: 2 |
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guid: 4122f2f81144716438e5281967ce7272 |
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DefaultImporter: |
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externalObjects: {} |
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userData: |
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assetBundleName: |
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assetBundleVariant: |
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|
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""" Helper bounding box 3d library to plot pretty 3D boundign |
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boxes with a simple Python API. |
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""" |
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import cv2 |
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import numpy |
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import streamlit as st |
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def _add_single_bbox3d_on_image( |
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image, |
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front_bottom_left, |
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front_upper_left, |
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front_upper_right, |
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front_bottom_right, |
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back_bottom_left, |
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back_upper_left, |
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back_upper_right, |
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back_bottom_right, |
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color=None, |
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box_line_width=2, |
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): |
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""" Add a single 3D bounding box to the passed in image. |
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For this version of the method, all of the passed in coordinates should be |
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integer tuples already projected in image pixel coordinate space. |
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Args: |
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image (numpy array): numpy array version of the image |
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front_bottom_left (int tuple): Front bottom left coordinate of the 3D |
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bounding box in pixel space |
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front_upper_left (int tuple): Front upper left coordinate of the 3D |
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bounding box in pixel space |
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front_upper_right (int tuple): Front upper right coordinate of the 3D |
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bounding box in pixel space |
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front_bottom_right (int tuple): Front bottom right coordinate of the 3D |
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bounding box in pixel space |
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back_bottom_left (int tuple): Back bottom left coordinate of the 3D |
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bounding box in pixel space |
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back_upper_left (int tuple): Back bottom left coordinate of the 3D |
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bounding box in pixel space |
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back_upper_right (int tuple): Back bottom left coordinate of the 3D |
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bounding box in pixel space |
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back_bottom_right (int tuple): Back bottom left coordinate of the 3D |
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bounding box in pixel space |
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color (tuple): RGBA color of the bounding box. Defaults to None. If |
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color = None the the tuple of [0, 255, 0, 255] (Green) will be used. |
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box_line_width: The width of the drawn box. Defaults to 2. |
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""" |
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try: |
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fbl = (front_bottom_left[0], front_bottom_left[1]) |
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ful = (front_upper_left[0], front_upper_left[1]) |
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fur = (front_upper_right[0], front_upper_right[1]) |
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fbr = (front_bottom_right[0], front_bottom_right[1]) |
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bbl = (back_bottom_left[0], back_bottom_left[1]) |
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bul = (back_upper_left[0], back_upper_left[1]) |
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bur = (back_upper_right[0], back_upper_right[1]) |
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bbr = (back_bottom_right[0], back_bottom_right[1]) |
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except ValueError: |
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raise TypeError("all box coorinates must be a number") |
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if color is None: |
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color = [0, 255, 0, 255] |
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cv2.line(image, fbl, ful, color, box_line_width) # front left |
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cv2.line(image, ful, fur, color, box_line_width) # front top |
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cv2.line(image, fbr, fur, color, box_line_width) # front right |
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cv2.line(image, fbl, fbr, color, box_line_width) # front bottom |
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cv2.line(image, bbl, bul, color, box_line_width) # back left |
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cv2.line(image, bul, bur, color, box_line_width) # back top |
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cv2.line(image, bbr, bur, color, box_line_width) # back right |
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cv2.line(image, bbl, bbr, color, box_line_width) # back bottom |
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cv2.line(image, ful, bul, color, box_line_width) # top left |
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cv2.line(image, fur, bur, color, box_line_width) # top right |
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cv2.line(image, fbl, bbl, color, box_line_width) # bottom left |
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cv2.line(image, fbr, bbr, color, box_line_width) # bottom right |
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|
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def add_single_bbox3d_on_image( |
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image, box, proj, color=None, orthographic=False, box_line_width=2, |
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): |
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"""" Add single 3D bounding box on a given image. |
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|
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Args: |
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image (numpy array): a numpy array for an image |
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box (BBox3D): a 3D bounding box in camera's coordinate system |
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proj (numpy 2D array): camera's 3x3 projection matrix |
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color(tuple): RGBA color of the bounding box. Defaults to None. If |
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color = None the the tuple of [0, 255, 0, 255] (Green) will be used. |
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box_line_width (int): line width of the bounding boxes. Defaults to 2. |
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""" |
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img_height, img_width, _ = image.shape |
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|
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fll = box.back_left_bottom_pt |
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ful = box.back_left_top_pt |
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fur = box.back_right_top_pt |
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flr = box.back_right_bottom_pt |
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|
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bll = box.front_left_bottom_pt |
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bul = box.front_left_top_pt |
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bur = box.front_right_top_pt |
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blr = box.front_right_bottom_pt |
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pixel_location_fun = _project_pt_to_pixel_location_orthographic if orthographic else _project_pt_to_pixel_location |
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fll_raster = pixel_location_fun(fll, proj, img_height, img_width) |
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ful_raster = pixel_location_fun(ful, proj, img_height, img_width) |
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fur_raster = pixel_location_fun(fur, proj, img_height, img_width) |
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flr_raster = pixel_location_fun(flr, proj, img_height, img_width) |
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bll_raster = pixel_location_fun(bll, proj, img_height, img_width) |
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bul_raster = pixel_location_fun(bul, proj, img_height, img_width) |
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bur_raster = pixel_location_fun(bur, proj, img_height, img_width) |
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blr_raster = pixel_location_fun(blr, proj, img_height, img_width) |
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|
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_add_single_bbox3d_on_image( |
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image, |
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fll_raster, |
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ful_raster, |
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fur_raster, |
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flr_raster, |
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bll_raster, |
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bul_raster, |
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bur_raster, |
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blr_raster, |
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color, |
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box_line_width, |
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) |
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|
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def _project_pt_to_pixel_location(pt, projection, img_height, img_width): |
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""" Projects a 3D coordinate into a pixel location. |
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|
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Applies the passed in projection matrix to project a point from the camera's |
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coordinate space into pixel space. |
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|
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For a description of the math used in this method, see: |
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https://www.scratchapixel.com/lessons/3d-basic-rendering/computing-pixel-coordinates-of-3d-point/ |
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|
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Args: |
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pt (numpy array): The 3D point to project. |
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projection (numpy 2D array): The camera's 3x3 projection matrix. |
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img_height (int): The height of the image in pixels. |
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img_width (int): The width of the image in pixels. |
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|
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Returns: |
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numpy array: a one-dimensional array with two values (x and y) |
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representing a point's pixel coordinate in an image. |
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""" |
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|
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_pt = projection.dot(pt) |
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|
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# compute the perspective divide. Near clipping plane should take care of |
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# divide by zero cases, but we will check to be sure |
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if _pt[2] != 0: |
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_pt /= _pt[2] |
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|
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return numpy.array( |
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[ |
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int(-(_pt[0] * img_width) / 2.0 + (img_width * 0.5)), |
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int((_pt[1] * img_height) / 2.0 + (img_height * 0.5)), |
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] |
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) |
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|
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def _project_pt_to_pixel_location_orthographic(pt, projection, img_height, img_width): |
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projection = numpy.array([ |
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[projection[0][0], 0, 0], |
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[0, -projection[1][1], 0], |
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[0, 0, projection[2][2]] |
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]) |
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temp = projection.dot(pt) |
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|
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pixel = [ |
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int((temp[0] + 1)*0.5 * img_width), |
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int((temp[1] + 1)*0.5 * img_height) |
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] |
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return pixel |
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|
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fileFormatVersion: 2 |
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guid: 6ebe9fac6325103488e689f91f4e486e |
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DefaultImporter: |
|||
externalObjects: {} |
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userData: |
|||
assetBundleName: |
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assetBundleVariant: |
|||
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