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#!/usr/bin/env python
"""ArCamera based of ArUco markers technology."""
__author__ = "Théo de la Hogue"
__credits__ = []
__copyright__ = "Copyright 2023, Ecole Nationale de l'Aviation Civile (ENAC)"
__license__ = "BSD"
from typing import TypeVar, Tuple
from dataclasses import dataclass, field
import json
import os
from argaze import ArFeatures, DataStructures
from argaze.ArUcoMarkers import ArUcoMarkersDictionary, ArUcoDetector, ArUcoOpticCalibrator, ArUcoScene
from argaze.AreaOfInterest import AOI2DScene
import cv2
import numpy
ArUcoCameraType = TypeVar('ArUcoCamera', bound="ArUcoCamera")
# Type definition for type annotation convenience
# Define default ArUcoCamera image_paremeters values
DEFAULT_ARUCOCAMERA_IMAGE_PARAMETERS = {
"draw_detected_markers": {
"color": (0, 255, 0),
"draw_axes": {
"thickness": 3
}
}
}
@dataclass
class ArUcoCamera(ArFeatures.ArCamera):
"""
Define an ArCamera based on ArUco marker detection.
aruco_detector: ArUco marker detector
"""
aruco_detector: ArUcoDetector.ArUcoDetector = field(default_factory=ArUcoDetector.ArUcoDetector)
def __post_init__(self):
super().__post_init__()
# 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 ArFeatures.LoadingFailed('ArUcoCamera: aruco_detector.optic_parameters.dimensions have to be equal to size.')
# No optic parameters loaded
else:
# TODO: Create default optic parameters adapted to frame size
raise ArFeatures.LoadingFailed('ArUcoCamera: no aruco_detector.optic_parameters.')
def __str__(self) -> str:
"""
Returns:
String representation
"""
output = super().__str__()
output += f'ArUcoDetector:\n{self.aruco_detector}\n'
return output
@classmethod
def from_dict(self, aruco_camera_data, working_directory: str = None) -> ArUcoCameraType:
"""
Load ArUcoCamera from dictionary.
Parameters:
aruco_camera_data: dictionary
working_directory: folder path where to load files when a dictionary value is a relative filepath.
"""
# Load ArUco detector
new_aruco_detector = ArUcoDetector.ArUcoDetector.from_dict(aruco_camera_data.pop('aruco_detector'), working_directory)
# Load ArUcoScenes
new_scenes = {}
try:
for aruco_scene_name, aruco_scene_data in aruco_camera_data.pop('scenes').items():
# Append name
aruco_scene_data['name'] = aruco_scene_name
# Create new aruco scene
new_aruco_scene = ArUcoScene.ArUcoScene.from_dict(aruco_scene_data, working_directory)
# Append new scene
new_scenes[aruco_scene_name] = new_aruco_scene
except KeyError:
pass
# Set image_parameters to default if there is not
if 'image_parameters' not in aruco_camera_data.keys():
aruco_camera_data['image_parameters'] = {**ArFeatures.DEFAULT_ARFRAME_IMAGE_PARAMETERS, **DEFAULT_ARUCOCAMERA_IMAGE_PARAMETERS}
# Set draw_layers to default if there is not
if 'draw_layers' not in aruco_camera_data['image_parameters'].keys():
aruco_camera_data['image_parameters']['draw_layers'] = {}
for layer_name, layer_data in aruco_camera_data['layers'].items():
aruco_camera_data['image_parameters']['draw_layers'][layer_name] = ArFeatures.DEFAULT_ARLAYER_DRAW_PARAMETERS
# Get values of temporary ar frame created from aruco_camera_data
temp_ar_frame_values = DataStructures.as_dict(ArFeatures.ArFrame.from_dict(aruco_camera_data, working_directory))
# Create new aruco camera using temporary ar frame values
return ArUcoCamera(aruco_detector=new_aruco_detector, scenes=new_scenes, **temp_ar_frame_values)
@classmethod
def from_json(self, json_filepath: str) -> ArUcoCameraType:
"""
Load ArUcoCamera from .json file.
Parameters:
json_filepath: path to json file
"""
with open(json_filepath) as configuration_file:
aruco_camera_data = json.load(configuration_file)
working_directory = os.path.dirname(json_filepath)
return ArUcoCamera.from_dict(aruco_camera_data, working_directory)
def watch(self, image: numpy.array) -> Tuple[float, dict]:
"""Detect environment aruco markers from image and project scenes into camera frame.
Returns:
- detection_time: aruco marker detection time in ms
- exceptions: dictionary with exception raised per scene
"""
# Detect aruco markers
detection_time = self.aruco_detector.detect_markers(image)
# Lock camera frame exploitation
self._frame_lock.acquire()
# Fill camera frame background with image
self.background = image
# Clear former layers projection into camera frame
for layer_name, layer in self.layers.items():
layer.aoi_scene = AOI2DScene.AOI2DScene()
# Store exceptions for each scene
exceptions = {}
# 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
'''
try:
# Estimate scene markers poses
self.aruco_detector.estimate_markers_pose(scene.aruco_markers_group.identifiers)
# Estimate scene pose from detected scene markers
tvec, rmat, _, _ = scene.estimate_pose(self.aruco_detector.detected_markers)
# Project scene into camera frame according estimated pose
for layer_name, layer_projection in scene.project(tvec, rmat):
try:
self.layers[layer_name].aoi_scene |= layer_projection
except KeyError:
pass
# Store exceptions and continue
except Exception as e:
exceptions[scene_name] = e
# Unlock camera frame exploitation
self._frame_lock.release()
# Return dection time and exceptions
return detection_time, exceptions
def __image(self, draw_detected_markers: dict = None, draw_optic_parameters_grid: dict = None, **kwargs) -> numpy.array:
"""Get frame image with ArUco detection visualisation.
Parameters:
draw_detected_markers: ArucoMarker.draw parameters (if None, no marker drawn)
draw_optic_parameters_grid: OpticParameter.draw parameters (if None, no grid drawn)
kwargs: ArCamera.image parameters
"""
# Can't use camera frame when it is locked
if self._frame_lock.locked():
return
# Lock camera frame exploitation
self._frame_lock.acquire()
# Get camera frame image
image = super().image(**kwargs)
# Draw detected markers if required
if draw_detected_markers is not None:
self.aruco_detector.draw_detected_markers(image, draw_detected_markers)
# Draw optic parameters grid if required
if draw_optic_parameters_grid is not None:
self.aruco_detector.optic_parameters.draw(image, **draw_optic_parameters_grid)
# Unlock camera frame exploitation
self._frame_lock.release()
return image
def image(self, **kwargs) -> numpy.array:
"""
Get frame image.
Parameters:
kwargs: ArUcoCamera.__image parameters
"""
# Use image_parameters attribute if no kwargs
if kwargs:
return self.__image(**kwargs)
return self.__image(**self.image_parameters)
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