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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)
```
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