diff options
Diffstat (limited to 'docs/user_guide')
8 files changed, 22 insertions, 22 deletions
diff --git a/docs/user_guide/ar_environment/environment_exploitation.md b/docs/user_guide/ar_environment/environment_exploitation.md index f07d150..a4013ea 100644 --- a/docs/user_guide/ar_environment/environment_exploitation.md +++ b/docs/user_guide/ar_environment/environment_exploitation.md @@ -4,8 +4,8 @@ Environment exploitation Once loaded, [ArEnvironment](../../../argaze/#argaze.ArFeatures.ArEnvironment) 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 AR environment ArUco detector passing it a image where to detect ArUco markers +ar_environment.aruco_detector.detect_markers(image) # Access to an AR environment scene my_first_scene = ar_environment.scenes['my first AR scene'] @@ -15,15 +15,15 @@ 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 + # 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(frame) + my_first_scene.draw_axis(image) # Draw AOI2D scene projection - aoi2D_scene.draw(frame) + aoi2D_scene.draw(image) # Do something with AOI2D scene projection ... diff --git a/docs/user_guide/areas_of_interest/aoi_matching.md b/docs/user_guide/areas_of_interest/aoi_matching.md index 1e18238..ff658a2 100644 --- a/docs/user_guide/areas_of_interest/aoi_matching.md +++ b/docs/user_guide/areas_of_interest/aoi_matching.md @@ -5,7 +5,7 @@ title: AOI matching AOI matching ============ -Once [AOI3DScene](../../../argaze/#argaze.AreaOfInterest.AOI3DScene) is projected into a frame as [AOI2DScene](../../../argaze/#argaze.AreaOfInterest.AOI2DScene), it could be needed to know which AOI is looked. +Once [AOI3DScene](../../../argaze/#argaze.AreaOfInterest.AOI3DScene) is projected as [AOI2DScene](../../../argaze/#argaze.AreaOfInterest.AOI2DScene), it could be needed to know which AOI is looked. The [AreaOfInterest](../../../argaze/#argaze.AreaOfInterest.AOIFeatures.AreaOfInterest) class in [AOIFeatures](../../../argaze/#argaze.AreaOfInterest.AOIFeatures) provides two ways to accomplish such task. diff --git a/docs/user_guide/areas_of_interest/aoi_scene_projection.md b/docs/user_guide/areas_of_interest/aoi_scene_projection.md index ad50f6f..bdb3fe0 100644 --- a/docs/user_guide/areas_of_interest/aoi_scene_projection.md +++ b/docs/user_guide/areas_of_interest/aoi_scene_projection.md @@ -5,7 +5,7 @@ title: AOI scene projection AOI scene projection ==================== -An [AOI3DScene](../../../argaze/#argaze.AreaOfInterest.AOI3DScene) can be rotated and translated according to a pose estimation before to project it onto camera frame as an [AOI2DScene](../../../argaze/#argaze.AreaOfInterest.AOI2DScene). +An [AOI3DScene](../../../argaze/#argaze.AreaOfInterest.AOI3DScene) can be rotated and translated according to a pose estimation before to project it onto camera image as an [AOI2DScene](../../../argaze/#argaze.AreaOfInterest.AOI2DScene).  @@ -18,5 +18,5 @@ An [AOI3DScene](../../../argaze/#argaze.AreaOfInterest.AOI3DScene) can be rotate aoi2D_scene = aoi3D_scene.project(tvec, rmat, optic_parameters.K) # Draw AOI 2D scene -aoi2D_scene.draw(frame) +aoi2D_scene.draw(image) ``` diff --git a/docs/user_guide/aruco_markers/camera_calibration.md b/docs/user_guide/aruco_markers/camera_calibration.md index 7bff480..1019fc1 100644 --- a/docs/user_guide/aruco_markers/camera_calibration.md +++ b/docs/user_guide/aruco_markers/camera_calibration.md @@ -24,7 +24,7 @@ Then, the calibration process needs to make many different captures of an [ArUco  -The sample of code below shows how to detect board corners into camera frames, store detected corners then process them to build calibration data and, finally, save it into a JSON file: +The sample of code below shows how to detect board corners into camera images, store detected corners then process them to build calibration data and, finally, save it into a JSON file: ``` python from argaze.ArUcoMarkers import ArUcoMarkersDictionary, ArUcoOpticCalibrator, ArUcoBoard, ArUcoDetector @@ -42,19 +42,19 @@ expected_aruco_board = ArUcoBoard.ArUcoBoard(7, 5, 5, 3, aruco_dictionary) # Create ArUco detector aruco_detector = ArUcoDetector.ArUcoDetector(dictionary=aruco_dictionary, marker_size=3) -# Capture frames from a live Full HD video stream (1920x1080) +# Capture images from a live Full HD video stream (1920x1080) while video_stream.is_alive(): - frame = video_stream.read() + image = video_stream.read() - # Detect all board corners in frame - aruco_detector.detect_board(frame, expected_aruco_board, expected_aruco_board.markers_number) + # Detect all board corners in image + aruco_detector.detect_board(image, expected_aruco_board, expected_aruco_board.markers_number) # If board corners are detected if aruco_detector.board_corners_number > 0: # Draw board corners to show that board tracking succeeded - aruco_detector.draw_board(frame) + aruco_detector.draw_board(image) # Append tracked board data for further calibration processing aruco_optic_calibrator.store_calibration_data(aruco_detector.board_corners, aruco_detector.board_corners_identifier) diff --git a/docs/user_guide/aruco_markers/markers_detection.md b/docs/user_guide/aruco_markers/markers_detection.md index 3851cb4..9a3bc9f 100644 --- a/docs/user_guide/aruco_markers/markers_detection.md +++ b/docs/user_guide/aruco_markers/markers_detection.md @@ -29,14 +29,14 @@ Here is [DetectorParameters](../../../argaze/#argaze.ArUcoMarkers.ArUcoDetector. } ``` -The [ArUcoDetector](../../../argaze/#argaze.ArUcoMarkers.ArUcoDetector.ArUcoDetector) processes frame to detect markers and allows to draw detection results onto it: +The [ArUcoDetector](../../../argaze/#argaze.ArUcoMarkers.ArUcoDetector.ArUcoDetector) processes image to detect markers and allows to draw detection results onto it: ``` python -# Detect markers into a frame and draw them -aruco_detector.detect_markers(frame) -aruco_detector.draw_detected_markers(frame) +# Detect markers into image and draw them +aruco_detector.detect_markers(image) +aruco_detector.draw_detected_markers(image) -# Get corners position into frame related to each detected markers +# Get corners position into image related to each detected markers for marker_id, marker in aruco_detector.detected_markers.items(): print(f'marker {marker_id} corners: ', marker.corners) diff --git a/docs/user_guide/timestamped_data/introduction.md b/docs/user_guide/timestamped_data/introduction.md index ed13d85..a36daca 100644 --- a/docs/user_guide/timestamped_data/introduction.md +++ b/docs/user_guide/timestamped_data/introduction.md @@ -1,6 +1,6 @@ Timestamped data ================ -Working with wearable eye tracker devices implies to handle various timestamped data like frames, gaze positions, pupils diameter, fixations, saccades, ... +Working with wearable eye tracker devices implies to handle various timestamped data like gaze positions, pupils diameter, fixations, saccades, ... This section mainly refers to [DataStructures.TimeStampedBuffer](../../../argaze/#argaze.DataStructures.TimeStampedBuffer) class. diff --git a/docs/user_guide/utils/demonstrations_scripts.md b/docs/user_guide/utils/demonstrations_scripts.md index adcc8b3..5de2927 100644 --- a/docs/user_guide/utils/demonstrations_scripts.md +++ b/docs/user_guide/utils/demonstrations_scripts.md @@ -11,7 +11,7 @@ Collection of command-line scripts for demonstration purpose. ## AR environment demonstration -Load AR environment from **setup.json** file, detect ArUco markers into camera device (-d DEVICE) frames and estimate envirnoment pose. +Load AR environment from **setup.json** file, detect ArUco markers into camera device (-d DEVICE) images and estimate envirnoment pose. ```shell python ./src/argaze/utils/demo_ar_features_run.py -d DEVICE diff --git a/docs/user_guide/utils/ready-made_scripts.md b/docs/user_guide/utils/ready-made_scripts.md index 035d697..afc5749 100644 --- a/docs/user_guide/utils/ready-made_scripts.md +++ b/docs/user_guide/utils/ready-made_scripts.md @@ -36,7 +36,7 @@ python ./src/argaze/utils/camera_calibrate.py 7 5 5 3 DICT_APRILTAG_16h5 -d DEVI ## ArUco scene exporter -Load a MOVIE with ArUco markers inside and select a frame into it, detect ArUco markers belonging to DICT_APRILTAG_16h5 dictionary with 5cm size into the selected frame thanks to given OPTIC_PARAMETERS and DETECTOR_PARAMETERS then, export detected ArUco markers scene as .obj file into an *./src/argaze/utils/_export/scenes* folder. +Load a MOVIE with ArUco markers inside and select image into it, detect ArUco markers belonging to DICT_APRILTAG_16h5 dictionary with 5cm size into the selected image thanks to given OPTIC_PARAMETERS and DETECTOR_PARAMETERS then, export detected ArUco markers scene as .obj file into an *./src/argaze/utils/_export/scenes* folder. ```shell python ./src/argaze/utils/aruco_markers_scene_export.py MOVIE DICT_APRILTAG_16h5 5 OPTIC_PARAMETERS DETECTOR_PARAMETERS -o ./src/argaze/utils/_export/scenes |