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author | Théo de la Hogue | 2023-09-06 07:39:03 +0200 |
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committer | Théo de la Hogue | 2023-09-06 07:39:03 +0200 |
commit | 0aa693d8bac1143253f8c478c71830db2997fe0e (patch) | |
tree | c86fb41b8ec8a4aa6fbef349f206b4be1c56152a /docs/user_guide/augmented_reality_pipeline | |
parent | 9e98398413fec13a3eec9051b974db93dd73483c (diff) | |
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Renaming camera_calibration.md into optic_parameters_calibration.md.
Diffstat (limited to 'docs/user_guide/augmented_reality_pipeline')
-rw-r--r-- | docs/user_guide/augmented_reality_pipeline/optic_parameters_calibration.md | 133 |
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diff --git a/docs/user_guide/augmented_reality_pipeline/optic_parameters_calibration.md b/docs/user_guide/augmented_reality_pipeline/optic_parameters_calibration.md new file mode 100644 index 0000000..0561112 --- /dev/null +++ b/docs/user_guide/augmented_reality_pipeline/optic_parameters_calibration.md @@ -0,0 +1,133 @@ +Calibrate optic parameters +========================== + +A camera device have to be calibrated to compensate its optical distorsion. + +![Optic parameters calibration](../../img/optic_calibration.png) + +## Print calibration board + +The first step to calibrate a camera is to create an [ArUcoBoard](../../argaze.md/#argaze.ArUcoMarkers.ArUcoBoard) like in the code below: + +``` python +from argaze.ArUcoMarkers import ArUcoMarkersDictionary, ArUcoBoard + +# Create ArUco dictionary +aruco_dictionary = ArUcoMarkersDictionary.ArUcoMarkersDictionary('DICT_APRILTAG_16h5') + +# Create an ArUco board of 7 columns and 5 rows with 5 cm squares with 3cm ArUco markers inside +aruco_board = ArUcoBoard.ArUcoBoard(7, 5, 5, 3, aruco_dictionary) + +# Export ArUco board with 300 dpi resolution +aruco_board.save('./calibration_board.png', 300) +``` + +!!! note + There is **A3_DICT_APRILTAG_16h5_3cm_35cmx25cm.pdf** file located in *./src/argaze/ArUcoMarkers/utils/* folder ready to be printed on A3 paper sheet. + +Let's print the calibration board before to go further. + +## Capture board pictures + +Then, the calibration process needs to make many different captures of an [ArUcoBoard](../../argaze.md/#argaze.ArUcoMarkers.ArUcoBoard) through the camera and then, pass them to an [ArUcoDetector](../../argaze.md/#argaze.ArUcoMarkers.ArUcoDetector.ArUcoDetector) instance to detect board corners and store them as calibration data into an [ArUcoOpticCalibrator](../../argaze.md/#argaze.ArUcoMarkers.ArUcoOpticCalibrator) for final calibration process. + +![Calibration step](../../img/optic_calibration_step.png) + +The sample of code below illustrates how to: + +* load all required ArGaze objects, +* detect board corners into a Full HD camera video stream, +* store detected corners as calibration data then, +* once enough captures are made, process them to find optic parameters and, +* finally, save optic parameters into a JSON file. + +``` python +from argaze.ArUcoMarkers import ArUcoMarkersDictionary, ArUcoOpticCalibrator, ArUcoBoard, ArUcoDetector + +# Create ArUco dictionary +aruco_dictionary = ArUcoMarkersDictionary.ArUcoMarkersDictionary('DICT_APRILTAG_16h5') + +# Create ArUco optic calibrator +aruco_optic_calibrator = ArUcoOpticCalibrator.ArUcoOpticCalibrator() + +# Create ArUco board of 7 columns and 5 rows with 5 cm squares with 3cm aruco markers inside +# Note: This board is the one expected during further board tracking +expected_aruco_board = ArUcoBoard.ArUcoBoard(7, 5, 5, 3, aruco_dictionary) + +# Create ArUco detector +aruco_detector = ArUcoDetector.ArUcoDetector(dictionary=aruco_dictionary, marker_size=3) + +# Assuming that live Full HD (1920x1080) video stream is enabled +... + +# Assuming there is a way to escape the while loop +... + + # Capture images from video stream + while video_stream.is_alive(): + + image = video_stream.read() + + # Detect all board corners in image + aruco_detector.detect_board(image, expected_aruco_board, expected_aruco_board.markers_number) + + # If all board corners are detected + if aruco_detector.board_corners_number == expected_aruco_board.corners_number: + + # Draw board corners to show that board tracking succeeded + 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) + +# Start optic calibration processing for Full HD image resolution +print('Calibrating optic...') +optic_parameters = aruco_optic_calibrator.calibrate(aruco_board, dimensions=(1920, 1080)) + +if optic_parameters: + + # Export optic parameters + optic_parameters.to_json('./optic_parameters.json') + + print('Calibration succeeded: optic_parameters.json file exported.') + +else: + + print('Calibration failed.') +``` + +Below, an optic_parameters JSON file example: + +```json +{ + "rms": 0.6688921504088245, + "dimensions": [ + 1920, + 1080 + ], + "K": [ + [ + 1135.6524381415752, + 0.0, + 956.0685325355497 + ], + [ + 0.0, + 1135.9272506869524, + 560.059099810324 + ], + [ + 0.0, + 0.0, + 1.0 + ] + ], + "D": [ + 0.01655492265003404, + 0.1985524264972037, + 0.002129965902489484, + -0.0019528582922179365, + -0.5792910353639452 + ] +} +``` |