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#!/usr/bin/env python
""" """
__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
from collections import Counter
import time
from argaze.ArUcoMarkers import ArUcoMarkersDictionary, ArUcoMarker, ArUcoOpticCalibrator
import numpy
import cv2 as cv
import cv2.aruco as aruco
ArUcoMarkerDictionaryType = TypeVar('ArUcoMarkerDictionary', bound="ArUcoMarkerDictionary")
# Type definition for type annotation convenience
ArUcoMarkerType = TypeVar('ArUcoMarker', bound="ArUcoMarker")
# Type definition for type annotation convenience
OpticParametersType = TypeVar('OpticParameters', bound="OpticParameters")
# Type definition for type annotation convenience
DetectorParametersType = TypeVar('DetectorParameters', bound="DetectorParameters")
# Type definition for type annotation convenience
ArUcoDetectorType = TypeVar('ArUcoDetector', bound="ArUcoDetector")
# Type definition for type annotation convenience
class DetectorParameters():
"""Wrapper class around ArUco marker detector parameters.
.. note:: More details on [opencv page](https://docs.opencv.org/4.x/d1/dcd/structcv_1_1aruco_1_1DetectorParameters.html)
"""
__parameters = aruco.DetectorParameters()
__parameters_names = [
'adaptiveThreshConstant',
'adaptiveThreshWinSizeMax',
'adaptiveThreshWinSizeMin',
'adaptiveThreshWinSizeStep',
'aprilTagCriticalRad',
'aprilTagDeglitch',
'aprilTagMaxLineFitMse',
'aprilTagMaxNmaxima',
'aprilTagMinClusterPixels',
'aprilTagMinWhiteBlackDiff',
'aprilTagQuadDecimate',
'aprilTagQuadSigma',
'cornerRefinementMaxIterations',
'cornerRefinementMethod',
'cornerRefinementMinAccuracy',
'cornerRefinementWinSize',
'markerBorderBits',
'minMarkerPerimeterRate',
'maxMarkerPerimeterRate',
'minMarkerDistanceRate',
'detectInvertedMarker',
'errorCorrectionRate',
'maxErroneousBitsInBorderRate',
'minCornerDistanceRate',
'minDistanceToBorder',
'minOtsuStdDev',
'perspectiveRemoveIgnoredMarginPerCell',
'perspectiveRemovePixelPerCell',
'polygonalApproxAccuracyRate'
]
def __init__(self, **kwargs):
for parameter, value in kwargs.items():
setattr(self.__parameters, parameter, value)
self.__dict__.update(kwargs)
def __setattr__(self, parameter, value):
setattr(self.__parameters, parameter, value)
def __getattr__(self, parameter):
return getattr(self.__parameters, parameter)
@classmethod
def from_json(self, json_filepath) -> DetectorParametersType:
"""Load detector parameters from .json file."""
with open(json_filepath) as configuration_file:
return DetectorParameters(**json.load(configuration_file))
def __str__(self, print_all=False) -> str:
"""Detector paremeters string representation."""
output = ''
for parameter in self.__parameters_names:
if parameter in self.__dict__.keys():
output += f'\t*{parameter}: {getattr(self.__parameters, parameter)}\n'
elif print_all:
output += f'\t{parameter}: {getattr(self.__parameters, parameter)}\n'
return output
@property
def internal(self):
return self.__parameters
@dataclass
class ArUcoDetector():
"""ArUco markers detector."""
dictionary: ArUcoMarkersDictionary.ArUcoMarkersDictionary = field(default_factory=ArUcoMarkersDictionary.ArUcoMarkersDictionary)
"""ArUco markers dictionary to detect."""
marker_size: float = field(default=0.)
"""Size of ArUco markers to detect in centimeter."""
optic_parameters: ArUcoOpticCalibrator.OpticParameters = field(default_factory=ArUcoOpticCalibrator.OpticParameters)
"""Optic parameters to use for ArUco detection into image."""
parameters: DetectorParameters = field(default_factory=DetectorParameters)
"""ArUco detector parameters."""
def __post_init__(self):
# Init detected markers data
self.__detected_markers = {}
self.__detected_markers_corners = []
self.__detected_markers_ids = []
# Init detected board data
self.__board = None
self.__board_corners_number = 0
self.__board_corners = []
self.__board_corners_ids = []
# Init detect metrics data
self.__detection_count = 0
self.__detected_ids = []
@classmethod
def from_json(self, json_filepath: str) -> ArUcoDetectorType:
"""Load ArUcoDetector setup from .json file."""
with open(json_filepath) as configuration_file:
data = json.load(configuration_file)
new_dictionary = ArUcoMarkersDictionary.ArUcoMarkersDictionary(**data.pop('dictionary'))
new_marker_size = data.pop('marker_size')
new_optic_parameters = ArUcoOpticCalibrator.OpticParameters(**data.pop('optic_parameters'))
new_parameters = DetectorParameters(**data.pop('parameters'))
return ArUcoDetector(new_dictionary, new_marker_size, new_optic_parameters, new_parameters)
def __str__(self) -> str:
"""String display"""
output = f'\n\tDictionary: {self.dictionary}\n'
output += f'\tMarker size: {self.marker_size} cm\n\n'
output += f'\tOptic parameters:\n{self.optic_parameters}\n'
output += f'\tDetection Parameters:\n{self.parameters}'
return output
def detect_markers(self, image: numpy.array) -> float:
"""Detect all ArUco markers into an image.
.. danger:: DON'T MIRROR IMAGE
It makes the markers detection to fail.
Returns:
- detection time: marker detection time in ms
"""
# Reset detected markers data
self.__detected_markers, self.__detected_markers_corners, self.__detected_markers_ids = {}, [], []
# Store marker detection start date
detection_start = time.time()
# Detect markers into gray picture
self.__detected_markers_corners, self.__detected_markers_ids, _ = aruco.detectMarkers(cv.cvtColor(image, cv.COLOR_BGR2GRAY), self.dictionary.markers, parameters = self.parameters.internal)
# Assess marker detection time in ms
detection_time = (time.time() - detection_start) * 1e3
# Is there detected markers ?
if len(self.__detected_markers_corners) > 0:
# Transform markers ids array into list
self.__detected_markers_ids = self.__detected_markers_ids.T[0]
# Gather detected markers data and update metrics
self.__detection_count += 1
for i, marker_id in enumerate(self.__detected_markers_ids):
marker = ArUcoMarker.ArUcoMarker(self.dictionary, marker_id, self.marker_size)
marker.corners = self.__detected_markers_corners[i]
# No pose estimation: call estimate_markers_pose to get one
marker.translation = numpy.empty([0])
marker.rotation = numpy.empty([0])
marker.points = numpy.empty([0])
self.__detected_markers[marker_id] = marker
self.__detected_ids.append(marker_id)
return detection_time
def estimate_markers_pose(self, markers_ids: list = []):
"""Estimate pose of current detected markers or of given markers id list."""
# Is there detected markers ?
if len(self.__detected_markers_corners) > 0:
# Is there a marker selection ?
if len(markers_ids) > 0:
selected_markers_corners = tuple()
selected_markers_ids = []
for i, marker_id in enumerate(self.__detected_markers_ids):
if marker_id in markers_ids:
selected_markers_corners += (self.__detected_markers_corners[i],)
selected_markers_ids.append(marker_id)
# Otherwise, estimate pose of all markers
else:
selected_markers_corners = self.__detected_markers_corners
selected_markers_ids = self.__detected_markers_ids
# Estimate pose of selected markers
if len(selected_markers_corners) > 0:
markers_rvecs, markers_tvecs, markers_points = aruco.estimatePoseSingleMarkers(selected_markers_corners, self.marker_size, numpy.array(self.optic_parameters.K), numpy.array(self.optic_parameters.D))
for i, marker_id in enumerate(selected_markers_ids):
marker = self.__detected_markers[marker_id]
marker.translation = markers_tvecs[i][0]
marker.rotation, _ = cv.Rodrigues(markers_rvecs[i][0])
marker.points = markers_points.reshape(4, 3)
@property
def detected_markers(self) -> dict[ArUcoMarkerType]:
"""Access to detected markers dictionary."""
return self.__detected_markers
@property
def detected_markers_number(self) -> int:
"""Return detected markers number."""
return len(list(self.__detected_markers.keys()))
def draw_detected_markers(self, image: numpy.array):
"""Draw traked markers."""
for marker_id, marker in self.__detected_markers.items():
marker.draw(image, self.optic_parameters.K, self.optic_parameters.D)
def detect_board(self, image: numpy.array, board, expected_markers_number):
"""Detect ArUco markers board in image setting up the number of detected markers needed to agree detection.
.. danger:: DON'T MIRROR IMAGE
It makes the markers detection to fail.
"""
# detect markers from gray picture
gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
self.__detected_markers_corners, self.__detected_markers_ids, _ = aruco.detectMarkers(gray, self.dictionary.markers, parameters = self.parameters.internal)
# if all board markers are detected
if len(self.__detected_markers_corners) == expected_markers_number:
self.__board = board
self.__board_corners_number, self.__board_corners, self.__board_corners_ids = aruco.interpolateCornersCharuco(self.__detected_markers_corners, self.__detected_markers_ids, gray, self.__board.model)
else:
self.__board = None
self.__board_corners_number = 0
self.__board_corners = []
self.__board_corners_ids = []
def draw_board(self, image: numpy.array):
"""Draw detected board corners in image."""
if self.__board != None:
cv.drawChessboardCorners(image, ((self.__board.size[0] - 1 ), (self.__board.size[1] - 1)), self.__board_corners, True)
def reset_detection_metrics(self):
"""Enable marker detection metrics."""
self.__detection_count = 0
self.__detected_ids = []
@property
def detection_metrics(self) -> Tuple[int, dict]:
"""Get marker detection metrics.
Returns:
number of detect function call
dict with number of detection for each marker identifier"""
return self.__detection_count, Counter(self.__detected_ids)
@property
def board_corners_number(self) -> int:
"""Get detected board corners number."""
return self.__board_corners_number
@property
def board_corners_identifier(self) -> list[int]:
"""Get detected board corners identifier."""
return self.__board_corners_ids
@property
def board_corners(self) -> list:
"""Get detected board corners."""
return self.__board_corners
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