mirror of
https://github.com/infiniteCable2/openpilot.git
synced 2026-09-07 08:43:40 +08:00
Dean Lee
1221821761
* rebase * cache metrics * measure text * type hint * improve * fix roundness * rebase
193 lines
7.3 KiB
Python
193 lines
7.3 KiB
Python
import numpy as np
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import pyray as rl
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from enum import Enum
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from cereal import messaging, log
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from msgq.visionipc import VisionStreamType
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from openpilot.system.ui.onroad.alert_renderer import AlertRenderer
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from openpilot.system.ui.onroad.driver_state import DriverStateRenderer
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from openpilot.system.ui.onroad.hud_renderer import HudRenderer
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from openpilot.system.ui.onroad.model_renderer import ModelRenderer
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from openpilot.system.ui.widgets.cameraview import CameraView
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from openpilot.system.ui.lib.application import gui_app
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from openpilot.common.transformations.camera import DEVICE_CAMERAS, DeviceCameraConfig, view_frame_from_device_frame
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from openpilot.common.transformations.orientation import rot_from_euler
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OpState = log.SelfdriveState.OpenpilotState
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CALIBRATED = log.LiveCalibrationData.Status.calibrated
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DEFAULT_DEVICE_CAMERA = DEVICE_CAMERAS["tici", "ar0231"]
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UI_BORDER_SIZE = 30
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class BorderStatus(Enum):
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DISENGAGED = rl.Color(0x17, 0x33, 0x49, 0xc8) # Blue for disengaged state
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OVERRIDE = rl.Color(0x91, 0x9b, 0x95, 0xf1) # Gray for override state
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ENGAGED = rl.Color(0x17, 0x86, 0x44, 0xf1) # Green for engaged state
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class AugmentedRoadView(CameraView):
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def __init__(self, sm: messaging.SubMaster, stream_type: VisionStreamType):
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super().__init__("camerad", stream_type)
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self.sm = sm
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self.stream_type = stream_type
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self.is_wide_camera = stream_type == VisionStreamType.VISION_STREAM_WIDE_ROAD
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self.device_camera: DeviceCameraConfig | None = None
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self.view_from_calib = view_frame_from_device_frame.copy()
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self.view_from_wide_calib = view_frame_from_device_frame.copy()
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self._last_calib_time: float = 0
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self._last_rect_dims = (0.0, 0.0)
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self._cached_matrix: np.ndarray | None = None
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self._content_rect = rl.Rectangle()
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self.model_renderer = ModelRenderer()
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self._hud_renderer = HudRenderer()
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self.alert_renderer = AlertRenderer()
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self.driver_state_renderer = DriverStateRenderer()
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def render(self, rect):
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# Update calibration before rendering
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self._update_calibration()
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# Create inner content area with border padding
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self._content_rect = rl.Rectangle(
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rect.x + UI_BORDER_SIZE,
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rect.y + UI_BORDER_SIZE,
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rect.width - 2 * UI_BORDER_SIZE,
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rect.height - 2 * UI_BORDER_SIZE,
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)
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# Draw colored border based on driving state
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self._draw_border(rect)
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# Enable scissor mode to clip all rendering within content rectangle boundaries
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# This creates a rendering viewport that prevents graphics from drawing outside the border
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rl.begin_scissor_mode(
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int(self._content_rect.x),
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int(self._content_rect.y),
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int(self._content_rect.width),
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int(self._content_rect.height)
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)
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# Render the base camera view
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super().render(rect)
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# Draw all UI overlays
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self.model_renderer.draw(self._content_rect, self.sm)
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self._hud_renderer.draw(self._content_rect, self.sm)
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self.alert_renderer.draw(self._content_rect, self.sm)
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self.driver_state_renderer.draw(self._content_rect, self.sm)
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# Custom UI extension point - add custom overlays here
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# Use self._content_rect for positioning within camera bounds
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# End clipping region
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rl.end_scissor_mode()
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def _draw_border(self, rect: rl.Rectangle):
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state = self.sm["selfdriveState"]
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if state.state in (OpState.preEnabled, OpState.overriding):
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status = BorderStatus.OVERRIDE
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elif state.enabled:
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status = BorderStatus.ENGAGED
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else:
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status = BorderStatus.DISENGAGED
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rl.draw_rectangle_lines_ex(rect, UI_BORDER_SIZE, status.value)
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def _update_calibration(self):
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# Update device camera if not already set
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if not self.device_camera and sm.seen['roadCameraState'] and sm.seen['deviceState']:
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self.device_camera = DEVICE_CAMERAS[(str(sm['deviceState'].deviceType), str(sm['roadCameraState'].sensor))]
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# Check if live calibration data is available and valid
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if not (sm.updated["liveCalibration"] and sm.valid['liveCalibration']):
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return
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calib = self.sm['liveCalibration']
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if len(calib.rpyCalib) != 3 or calib.calStatus != CALIBRATED:
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return
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# Update view_from_calib matrix
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device_from_calib = rot_from_euler(calib.rpyCalib)
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self.view_from_calib = view_frame_from_device_frame @ device_from_calib
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# Update wide calibration if available
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if hasattr(calib, 'wideFromDeviceEuler') and len(calib.wideFromDeviceEuler) == 3:
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wide_from_device = rot_from_euler(calib.wideFromDeviceEuler)
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self.view_from_wide_calib = view_frame_from_device_frame @ wide_from_device @ device_from_calib
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def _calc_frame_matrix(self, rect: rl.Rectangle) -> np.ndarray:
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# Check if we can use cached matrix
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calib_time = self.sm.recv_frame['liveCalibration']
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current_dims = (self._content_rect.width, self._content_rect.height)
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if (self._last_calib_time == calib_time and
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self._last_rect_dims == current_dims and
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self._cached_matrix is not None):
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return self._cached_matrix
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# Get camera configuration
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device_camera = self.device_camera or DEFAULT_DEVICE_CAMERA
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intrinsic = device_camera.ecam.intrinsics if self.is_wide_camera else device_camera.fcam.intrinsics
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calibration = self.view_from_wide_calib if self.is_wide_camera else self.view_from_calib
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zoom = 2.0 if self.is_wide_camera else 1.1
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# Calculate transforms for vanishing point
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inf_point = np.array([1000.0, 0.0, 0.0])
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calib_transform = intrinsic @ calibration
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kep = calib_transform @ inf_point
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# Calculate center points and dimensions
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x, y = self._content_rect.x, self._content_rect.y
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w, h = self._content_rect.width, self._content_rect.height
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cx, cy = intrinsic[0, 2], intrinsic[1, 2]
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# Calculate max allowed offsets with margins
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margin = 5
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max_x_offset = cx * zoom - w / 2 - margin
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max_y_offset = cy * zoom - h / 2 - margin
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# Calculate and clamp offsets to prevent out-of-bounds issues
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try:
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if abs(kep[2]) > 1e-6:
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x_offset = np.clip((kep[0] / kep[2] - cx) * zoom, -max_x_offset, max_x_offset)
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y_offset = np.clip((kep[1] / kep[2] - cy) * zoom, -max_y_offset, max_y_offset)
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else:
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x_offset, y_offset = 0, 0
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except (ZeroDivisionError, OverflowError):
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x_offset, y_offset = 0, 0
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# Update cache values
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self._last_calib_time = calib_time
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self._last_rect_dims = current_dims
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self._cached_matrix = np.array([
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[zoom * 2 * cx / w, 0, -x_offset / w * 2],
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[0, zoom * 2 * cy / h, -y_offset / h * 2],
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[0, 0, 1.0]
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])
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video_transform = np.array([
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[zoom, 0.0, (w / 2 + x - x_offset) - (cx * zoom)],
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[0.0, zoom, (h / 2 + y - y_offset) - (cy * zoom)],
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[0.0, 0.0, 1.0]
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])
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self.model_renderer.set_transform(video_transform @ calib_transform)
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return self._cached_matrix
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if __name__ == "__main__":
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gui_app.init_window("OnRoad Camera View")
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sm = messaging.SubMaster(["modelV2", "controlsState", "liveCalibration", "radarState", "deviceState",
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"pandaStates", "carParams", "driverMonitoringState", "carState", "driverStateV2",
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"roadCameraState", "wideRoadCameraState", "managerState", "selfdriveState", "longitudinalPlan"])
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road_camera_view = AugmentedRoadView(sm, VisionStreamType.VISION_STREAM_ROAD)
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try:
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for _ in gui_app.render():
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sm.update(0)
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road_camera_view.render(rl.Rectangle(0, 0, gui_app.width, gui_app.height))
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finally:
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road_camera_view.close()
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