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firestar5683
a82935f326
Integrate onroad views, configurable widgets, local settings, steering-profile contracts, Bluetooth and Android Auto with their device and runtime services. Co-authored-by: Adeeb Shihadeh <adeebshihadeh@gmail.com> Co-authored-by: Daniel Koepping <elkoled@gmail.com> Co-authored-by: Danny <dannyirwin31@yahoo.com> Co-authored-by: DimitriChrysafis <Dimitri.chrysafis@gmail.com> Co-authored-by: Dom <168790843+firestar5683@users.noreply.github.com> Co-authored-by: Harald Schäfer <harald.the.engineer@gmail.com> Co-authored-by: Prabhaav Pillai <prabhaav@msu.edu> Co-authored-by: Shane Smiskol <shane@smiskol.com> Co-authored-by: dirwin31 <83434411+dirwin31@users.noreply.github.com> Co-authored-by: firestarsdog <229254897+firestarsdog@users.noreply.github.com> Co-authored-by: stef <19478336+stefpi@users.noreply.github.com> Co-authored-by: whoisdomi <dcantu83@gmail.com> Co-authored-by: Intelli <contact@intelli.software> Co-authored-by: pharmacomaniac <blittle65@gmail.com> Co-authored-by: prabhaavp <prabhaav@msu.edu>
61 lines
2.3 KiB
Python
61 lines
2.3 KiB
Python
"""The on-road lane batch keeps line clipping and path projection separate."""
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from types import SimpleNamespace
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from unittest.mock import Mock
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import numpy as np
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from openpilot.selfdrive.ui.onroad.model_renderer import ModelPoints, ModelRenderer
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class CountedTransform:
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def __init__(self):
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self.calls = 0
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def __matmul__(self, points):
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self.calls += 1
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return np.eye(3, dtype=np.float32) @ points
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def renderer():
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view = object.__new__(ModelRenderer)
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vars(view)['_car_space_transform'] = CountedTransform()
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view._clip_region = SimpleNamespace(x=0, y=0, width=30, height=30)
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return view
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def test_six_line_batch_clips_each_polygon_with_one_transform():
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view = renderer()
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lines = [
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np.array([[10, 10, 1], [20, 10, 1], [40, 10, 1]], dtype=np.float32),
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np.empty((0, 3), dtype=np.float32),
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np.array([[10, 50, 1], [20, 5, 1], [40, 5, 1]], dtype=np.float32),
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np.array([[10, 10, 0], [20, 10, 0], [40, 10, 0]], dtype=np.float32),
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np.array([[-10, 10, 1], [-5, 10, 1], [0, 10, 1]], dtype=np.float32),
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np.array([[10, 29, 1], [20, 29, 1], [40, 29, 1]], dtype=np.float32),
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]
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with np.errstate(divide='raise', invalid='raise'):
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polygons = view._map_lines_to_polygons(lines, [2] * 6, 0.0, 1, 35.0)
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assert view._car_space_transform.calls == 1
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np.testing.assert_array_equal(polygons[0], [[10, 8], [20, 8], [20, 12], [10, 12]])
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np.testing.assert_array_equal(polygons[2], [[20, 3], [20, 7]])
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assert all(polygon.shape == (0, 2) for polygon in (polygons[1], polygons[3], polygons[4], polygons[5]))
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def test_model_update_batches_lanes_and_edges_but_keeps_path_separate():
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view = renderer()
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points = np.array([[10, 10, 1], [20, 10, 1], [30, 10, 1]], dtype=np.float32)
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view._path = ModelPoints(raw_points=points.copy())
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view._lane_lines = [ModelPoints(raw_points=points.copy()) for _ in range(4)]
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view._road_edges = [ModelPoints(raw_points=points.copy()) for _ in range(2)]
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view._lane_line_probs = np.ones(4, dtype=np.float32)
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view._path_offset_z = 0.0
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view._update_experimental_gradient = Mock()
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view._update_model(None, points[:, 0])
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assert view._car_space_transform.calls == 2 # one lane/edge batch, one path
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assert all(line.projected_points.size for line in [*view._lane_lines, *view._road_edges])
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assert view._path.projected_points.size
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view._update_experimental_gradient.assert_called_once_with()
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