1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
|
Markers scene description
=========================
The ArGaze toolkit provides [ArUcoMarkersGroup](../../argaze.md/#argaze.ArUcoMarkers.ArUcoMarkersGroup) class to describe where [ArUcoMarkers](../../argaze.md/#argaze.ArUcoMarkers.ArUcoMarker) are placed into a 3D model.
[ArUcoMarkersGroup](../../argaze.md/#argaze.ArUcoMarkers.ArUcoMarkersGroup) is useful to:
* filter markers that belongs to this predefined scene,
* check the consistency of detected markers according the place where each marker is expected to be,
* estimate the pose of the scene from the pose of detected markers.
## Scene creation
### from OBJ
ArUco scene description uses common OBJ file format that can be exported from most 3D editors. Notice that plane normals (vn) needs to be exported.
``` obj
o DICT_APRILTAG_16h5#0_Marker
v -3.004536 0.022876 2.995370
v 2.995335 -0.015498 3.004618
v -2.995335 0.015498 -3.004618
v 3.004536 -0.022876 -2.995370
vn 0.0064 1.0000 -0.0012
s off
f 1//1 2//1 4//1 3//1
o DICT_APRILTAG_16h5#1_Marker
v -33.799068 46.450645 -32.200436
v -27.852505 47.243549 -32.102116
v -34.593925 52.396473 -32.076626
v -28.647360 53.189377 -31.978306
vn -0.0135 -0.0226 0.9997
s off
f 5//2 6//2 8//2 7//2
...
```
Here is a sample of code to show the loading of an [ArUcoMarkersGroup](../../argaze.md/#argaze.ArUcoMarkers.ArUcoMarkersGroup) OBJ file description:
``` python
from argaze.ArUcoMarkers import ArUcoMarkersGroup
# Create an ArUco scene from a OBJ file description
aruco_markers_group = ArUcoMarkersGroup.ArUcoMarkersGroup.from_obj('./markers.obj')
# Print loaded marker places
for place_id, place in aruco_markers_group.places.items():
print(f'place {place_id} for marker: ', place.marker.identifier)
print(f'place {place_id} translation: ', place.translation)
print(f'place {place_id} rotation: ', place.rotation)
```
### from JSON
[ArUcoMarkersGroup](../../argaze.md/#argaze.ArUcoMarkers.ArUcoMarkersGroup) description can also be written in a JSON file format.
``` json
{
"dictionary": "DICT_ARUCO_ORIGINAL",
"marker_size": 1,
"places": {
"0": {
"translation": [0, 0, 0],
"rotation": [0, 0, 0]
},
"1": {
"translation": [10, 10, 0],
"rotation": [0, 0, 0]
},
"2": {
"translation": [0, 10, 0],
"rotation": [0, 0, 0]
}
}
}
```
### from detected markers
Here is a more advanced usage where ArUco scene is built from markers detected into an image:
``` python
from argaze.ArUcoMarkers import ArUcoMarkersGroup
# Assuming markers have been detected and their pose estimated thanks to ArUcoDetector
...
# Build ArUco scene from detected markers
aruco_markers_group = ArUcoMarkersGroup.ArUcoMarkersGroup(aruco_detector.marker_size, aruco_detector.dictionary, aruco_detector.detected_markers)
```
## Markers filtering
Considering markers are detected, here is how to filter them to consider only those which belongs to the scene:
``` python
scene_markers, remaining_markers = aruco_markers_group.filter_markers(aruco_detector.detected_markers)
```
## Marker poses consistency
Then, scene markers poses can be validated by verifying their spatial consistency considering angle and distance tolerance. This is particularly useful to discard ambiguous marker pose estimations when markers are parallel to camera plane (see [issue on OpenCV Contribution repository](https://github.com/opencv/opencv_contrib/issues/3190#issuecomment-1181970839)).
``` python
# Check scene markers consistency with 10° angle tolerance and 1 cm distance tolerance
consistent_markers, unconsistent_markers, unconsistencies = aruco_markers_group.check_markers_consistency(scene_markers, 10, 1)
```
## Scene pose estimation
Several approaches are available to perform [ArUcoMarkersGroup](../../argaze.md/#argaze.ArUcoMarkers.ArUcoMarkersGroup) pose estimation from markers belonging to the scene.
The first approach considers that scene pose can be estimated **from a single marker pose**:
``` python
# Let's select one consistent scene marker
marker_id, marker = consistent_markers.popitem()
# Estimate scene pose from a single marker
tvec, rmat = self.aruco_markers_group.estimate_pose_from_single_marker(marker)
```
The second approach considers that scene pose can be estimated by **averaging several marker poses**:
``` python
# Estimate scene pose from all consistent scene markers
tvec, rmat = self.aruco_markers_group.estimate_pose_from_markers(consistent_markers)
```
The third approach is only available when ArUco markers are placed in such a configuration that is possible to **define orthogonal axis**:
``` python
tvec, rmat = self.aruco_markers_group.estimate_pose_from_axis_markers(origin_marker, horizontal_axis_marker, vertical_axis_marker)
```
## Scene exportation
As ArUco scene can be exported to OBJ file description to import it into most 3D editors.
``` python
# Export an ArUco scene as OBJ file description
aruco_markers_group.to_obj('markers.obj')
```
|
