From 23fa1a7835b3c7cfd976b1d160878289b1f0657c Mon Sep 17 00:00:00 2001
From: Theo De La Hogue
Date: Sat, 23 Sep 2023 07:22:23 +0200
Subject: Fixing code annotation. Removing useless documentation section.
 Fixing documentation cross reference.

---
 .../ar_environment/environment_exploitation.md     | 36 ----------
 .../user_guide/ar_environment/environment_setup.md | 77 ----------------------
 docs/user_guide/ar_environment/introduction.md     |  6 --
 3 files changed, 119 deletions(-)
 delete mode 100644 docs/user_guide/ar_environment/environment_exploitation.md
 delete mode 100644 docs/user_guide/ar_environment/environment_setup.md
 delete mode 100644 docs/user_guide/ar_environment/introduction.md

(limited to 'docs/user_guide/ar_environment')

diff --git a/docs/user_guide/ar_environment/environment_exploitation.md b/docs/user_guide/ar_environment/environment_exploitation.md
deleted file mode 100644
index 9e4b236..0000000
--- a/docs/user_guide/ar_environment/environment_exploitation.md
+++ /dev/null
@@ -1,36 +0,0 @@
-Environment exploitation
-========================
-
-Once loaded, [ArCamera](../../argaze.md/#argaze.ArFeatures.ArCamera) assets can be exploited as illustrated below:
-
-```python
-# Access to AR environment ArUco detector passing it a image where to detect ArUco markers
-ar_camera.aruco_detector.detect_markers(image)
-
-# Access to an AR environment scene
-my_first_scene = ar_camera.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_camera.aruco_detector.detected_markers)
-
-     # Project AR scene into camera image 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(image)
-
-     # Draw AOI2D scene projection
-     aoi2D_scene.draw(image)
-
-     # 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
deleted file mode 100644
index 1f26d26..0000000
--- a/docs/user_guide/ar_environment/environment_setup.md
+++ /dev/null
@@ -1,77 +0,0 @@
-Environment Setup
-=================
-
-[ArCamera](../../argaze.md/#argaze.ArFeatures.ArCamera) setup is loaded from JSON file format.
-
-Each [ArCamera](../../argaze.md/#argaze.ArFeatures.ArCamera) defines a unique [ArUcoDetector](../../argaze.md/#argaze.ArUcoMarkers.ArUcoDetector.ArUcoDetector) dedicated to detection of markers from a specific [ArUcoMarkersDictionary](../../argaze.md/#argaze.ArUcoMarkers.ArUcoMarkersDictionary) and with a given size. However, it is possible to load multiple [ArScene](../../argaze.md/#argaze.ArFeatures.ArScene) into a same [ArCamera](../../argaze.md/#argaze.ArFeatures.ArCamera).
-
-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,
-    	"optic_parameters": {
-            "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_markers_group": "./first_scene/markers.obj",
-            "aoi_scene": "./first_scene/aoi.obj",
-            "angle_tolerance": 15.0,
-            "distance_tolerance": 2.54
-        },
-        "my second AR scene" : {
-            "aruco_markers_group": "./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_camera = ArFeatures.ArCamera.from_json('./environment.json')
-```
diff --git a/docs/user_guide/ar_environment/introduction.md b/docs/user_guide/ar_environment/introduction.md
deleted file mode 100644
index b19383b..0000000
--- a/docs/user_guide/ar_environment/introduction.md
+++ /dev/null
@@ -1,6 +0,0 @@
-AR environment setup
-====================
-
-ArGaze toolkit eases ArUco and AOI management in a single AR environment setup.
-
-This section refers to [ArFeatures](../../argaze.md/#argaze.ArFeatures).
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