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authorThéo de la Hogue2023-06-07 14:34:14 +0200
committerThéo de la Hogue2023-06-07 14:34:14 +0200
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Writing User guide and use cases section.
Diffstat (limited to 'docs/user_guide/ar_environment')
-rw-r--r--docs/user_guide/ar_environment/environment_exploitation.md36
-rw-r--r--docs/user_guide/ar_environment/environment_setup.md77
-rw-r--r--docs/user_guide/ar_environment/introduction.md6
3 files changed, 119 insertions, 0 deletions
diff --git a/docs/user_guide/ar_environment/environment_exploitation.md b/docs/user_guide/ar_environment/environment_exploitation.md
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--- /dev/null
+++ b/docs/user_guide/ar_environment/environment_exploitation.md
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+Environment exploitation
+========================
+
+Once loaded, AR environment assets can be exploited as illustrated below:
+
+```python
+# Access to AR environment ArUco detector passing it a frame where to detect ArUco markers
+ar_environment.aruco_detector.detect_markers(frame)
+
+# Access to an AR environment scene
+my_first_scene = ar_environment.scenes['my first AR scene']
+
+try:
+
+ # Try to estimate AR scene pose from detected markers
+ tvec, rmat, consistent_markers = my_first_scene.estimate_pose(ar_environment.aruco_detector.detected_markers)
+
+ # Project AR scene into camera frame according estimated pose
+ # Optional visual_hfov argument is set to 160° to clip AOI scene according a cone vision
+ aoi2D_scene = my_first_scene.project(tvec, rmat, visual_hfov=160)
+
+ # Draw estimated AR scene axis
+ my_first_scene.draw_axis(frame)
+
+ # Draw AOI2D scene projection
+ aoi2D_scene.draw(frame)
+
+ # Do something with AOI2D scene projection
+ ...
+
+# Catch exceptions raised by estimate_pose and project methods
+except (ArFeatures.PoseEstimationFailed, ArFeatures.SceneProjectionFailed) as e:
+
+ print(e)
+
+```
diff --git a/docs/user_guide/ar_environment/environment_setup.md b/docs/user_guide/ar_environment/environment_setup.md
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index 0000000..b63f64a
--- /dev/null
+++ b/docs/user_guide/ar_environment/environment_setup.md
@@ -0,0 +1,77 @@
+Environment Setup
+=================
+
+AR environment setup is loaded from JSON file format.
+
+Each AR environment defines a unique ArUco detector dedicated to detection of markers from a specific ArUco dictionary and with a given size. However, it is possible to load multiple AR scenes into a same AR environment.
+
+Here is JSON environment file example where it is assumed that mentioned .obj files are located relatively to the environment file on disk.
+
+```
+{
+ "name": "my AR environment",
+ "aruco_detector": {
+ "dictionary": {
+ "name": "DICT_APRILTAG_16h5"
+ }
+ "marker_size": 5,
+ "camera": {
+ "rms": 0.6,
+ "dimensions": [
+ 1920,
+ 1080
+ ],
+ "K": [
+ [
+ 1135,
+ 0.0,
+ 956
+ ],
+ [
+ 0.0,
+ 1135,
+ 560
+ ],
+ [
+ 0.0,
+ 0.0,
+ 1.0
+ ]
+ ],
+ "D": [
+ 0.01655492265003404,
+ 0.1985524264972037,
+ 0.002129965902489484,
+ -0.0019528582922179365,
+ -0.5792910353639452
+ ]
+ },
+ "parameters": {
+ "cornerRefinementMethod": 3,
+ "aprilTagQuadSigma": 2,
+ "aprilTagDeglitch": 1
+ }
+ },
+ "scenes": {
+ "my first AR scene" : {
+ "aruco_scene": "./first_scene/markers.obj",
+ "aoi_scene": "./first_scene/aoi.obj",
+ "angle_tolerance": 15.0,
+ "distance_tolerance": 2.54
+ },
+ "my second AR scene" : {
+ "aruco_scene": "./second_scene/markers.obj",
+ "aoi_scene": "./second_scene/aoi.obj",
+ "angle_tolerance": 15.0,
+ "distance_tolerance": 2.54
+ }
+ }
+}
+```
+
+```python
+from argaze import ArFeatures
+
+# Load AR environment
+ar_environment = ArFeatures.ArEnvironment.from_json('./environment.json')
+```
diff --git a/docs/user_guide/ar_environment/introduction.md b/docs/user_guide/ar_environment/introduction.md
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--- /dev/null
+++ b/docs/user_guide/ar_environment/introduction.md
@@ -0,0 +1,6 @@
+AR environment setup
+====================
+
+ArGaze toolkit eases ArUco and AOI management in a single AR environment setup.
+
+This section refers to [ArFeatures](/aragaze/#argaze.ArFeatures).