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"""ArCamera based of ArUco markers technology."""
"""
This program is free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or (at your option) any later
version.
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with
this program. If not, see <https://www.gnu.org/licenses/>.
"""
__author__ = "Théo de la Hogue"
__credits__ = []
__copyright__ = "Copyright 2023, Ecole Nationale de l'Aviation Civile (ENAC)"
__license__ = "GPLv3"
import logging
import cv2
import numpy
from argaze import ArFeatures, DataFeatures
from argaze.ArUcoMarker import ArUcoDetector, ArUcoOpticCalibrator, ArUcoScene
from argaze.AreaOfInterest import AOI2DScene
# Define default ArUcoCamera image_parameters values
DEFAULT_ARUCOCAMERA_IMAGE_PARAMETERS = {
"draw_detected_markers": {
"color": (0, 255, 0),
"draw_axes": {
"thickness": 3
}
}
}
class ArUcoCamera(ArFeatures.ArCamera):
"""
Define an ArCamera based on ArUco marker detection.
"""
@DataFeatures.PipelineStepInit
def __init__(self, **kwargs):
"""Initialize ArUcoCamera"""
# Init ArCamera class
super().__init__()
# Init private attribute
self.__aruco_detector = None
self.__sides_mask = 0
# Init protected attributes
self._image_parameters = {**ArFeatures.DEFAULT_ARFRAME_IMAGE_PARAMETERS, **DEFAULT_ARUCOCAMERA_IMAGE_PARAMETERS}
@property
def aruco_detector(self) -> ArUcoDetector.ArUcoDetector:
"""ArUco marker detector."""
return self.__aruco_detector
@aruco_detector.setter
@DataFeatures.PipelineStepAttributeSetter
def aruco_detector(self, aruco_detector: ArUcoDetector.ArUcoDetector):
self.__aruco_detector = aruco_detector
# Check optic parameters
if self.__aruco_detector.optic_parameters is not None:
# Optic parameters dimensions should be equal to camera frame size
if self.__aruco_detector.optic_parameters.dimensions != self.size:
raise DataFeatures.PipelineStepLoadingFail('ArUcoCamera: aruco_detector.optic_parameters.dimensions have to be equal to size.')
# No optic parameters loaded
else:
# Create default optic parameters adapted to frame size
# Note: The choice of 1000 for default focal length should be discussed...
self.__aruco_detector.optic_parameters = ArUcoOpticCalibrator.OpticParameters(rms=-1, dimensions=self.size, K=ArUcoOpticCalibrator.K0(focal_length=(1000., 1000.), width=self.size[0], height=self.size[1]))
# Edit parent
if self.__aruco_detector is not None:
self.__aruco_detector.parent = self
@property
def sides_mask(self) -> int:
"""Size of mask (pixel) to hide video left and right sides."""
return self.__sides_mask
@sides_mask.setter
def sides_mask(self, size: int):
self.__sides_mask = size
@ArFeatures.ArCamera.scenes.setter
@DataFeatures.PipelineStepAttributeSetter
def scenes(self, scenes: dict):
self._scenes = {}
for scene_name, scene_data in scenes.items():
self._scenes[scene_name] = ArUcoScene.ArUcoScene(name=scene_name, **scene_data)
# Edit parent
for name, scene in self._scenes.items():
scene.parent = self
# Update expected and excluded aoi
self._update_expected_and_excluded_aoi()
@DataFeatures.PipelineStepMethod
@DataFeatures.PipelineStepExecutionTime
def watch(self, image: DataFeatures.TimestampedImage):
"""Detect environment aruco markers from image and project scenes into camera frame."""
logging.debug('ArUcoCamera.watch')
# Use camera frame lock feature
with self._lock:
# Draw black rectangles to mask sides
if self.__sides_mask > 0:
logging.debug('\t> drawing sides mask (%i px)', self.__sides_mask)
height, width, _ = image.shape
cv2.rectangle(image, (0, 0), (self.__sides_mask, height), (0, 0, 0), -1)
cv2.rectangle(image, (width - self.__sides_mask, 0), (width, height), (0, 0, 0), -1)
# Fill camera frame background with timestamped image
self.background = image
# Read projection from the cache if required
if not self._read_projection_cache(image.timestamp):
# Detect aruco markers
logging.debug('\t> detect markers')
self.__aruco_detector.detect_markers(image)
# Clear former layers projection into camera frame
self._clear_projection()
# Project each aoi 3d scene into camera frame
for scene_name, scene in self.scenes.items():
''' TODO: Enable aruco_aoi processing
if scene.aruco_aoi:
try:
# Build AOI scene directly from detected ArUco marker corners
self.layers[??].aoi_2d_scene |= scene.build_aruco_aoi_scene(self.__aruco_detector.detected_markers())
except ArFeatures.PoseEstimationFailed:
pass
'''
# Estimate scene pose from detected scene markers
logging.debug('\t> estimate %s scene pose', scene_name)
try:
tvec, rmat, _ = scene.estimate_pose(self.__aruco_detector.detected_markers(), timestamp=image.timestamp)
# Project scene into camera frame according estimated pose
for layer_name, layer_projection in scene.project(tvec, rmat, self.visual_hfov, self.visual_vfov, timestamp=image.timestamp):
logging.debug('\t> project %s scene %s layer', scene_name, layer_name)
try:
# Update camera layer aoi
self.layers[layer_name].aoi_scene |= layer_projection
# Timestamp camera layer
self.layers[layer_name].timestamp = image.timestamp
except KeyError:
pass
# Write projection into the cache if required
self._write_projection_cache(image.timestamp)
except DataFeatures.TimestampedException as e:
# Write exception into the cache if required
self._write_projection_cache(image.timestamp, e)
# Raise exception
raise e
# Copy camera frame background into scene frames background if required
if self.copy_background_into_scenes_frames:
self._copy_background_into_scenes_frames()
@DataFeatures.PipelineStepImage
@DataFeatures.PipelineStepExecutionTime
def image(self, draw_detected_markers: dict = None, draw_scenes: dict = None,
draw_optic_parameters_grid: dict = None, **kwargs: dict) -> numpy.array:
"""Get frame image with ArUco detection visualization.
Parameters:
draw_detected_markers: ArucoMarker.draw parameters (if None, no marker drawn)
draw_scenes: ArUcoScene.draw parameters (if None, no scene drawn)
draw_optic_parameters_grid: OpticParameter.draw parameters (if None, no grid drawn)
kwargs: ArCamera.image parameters
"""
logging.debug('ArUcoCamera.image %s', self.name)
# Get camera frame image
# Note: don't lock/unlock camera frame here as super().image manage it.
image = super().image(**kwargs)
# Use frame lock feature
with self._lock:
# Draw optic parameters grid if required
if draw_optic_parameters_grid is not None:
logging.debug('\t> drawing optic parameters')
self.__aruco_detector.optic_parameters.draw(image, **draw_optic_parameters_grid)
# Draw scenes if required
if draw_scenes is not None:
for scene_name, draw_scenes_parameters in draw_scenes.items():
logging.debug('\t> drawing %s scene', scene_name)
self.scenes[scene_name].draw(image, **draw_scenes_parameters)
# Draw detected markers if required
if draw_detected_markers is not None:
logging.debug('\t> drawing detected markers')
self.__aruco_detector.draw_detected_markers(image, draw_detected_markers)
return image
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