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Camera calibration
==================
Any camera device have to be calibrated to compensate its optical distorsion.
The first step to calibrate a camera is to create an ArUco calibration board 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)
```
Then, the calibration process needs to make many different captures of an ArUco board through the camera and then, pass them to an ArUco detector instance.
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:
``` python
from argaze.ArUcoMarkers import ArUcoMarkersDictionary, ArUcoCamera, ArUcoBoard, ArUcoDetector
# Create ArUco dictionary
aruco_dictionary = ArUcoMarkersDictionary.ArUcoMarkersDictionary('DICT_APRILTAG_16h5')
# Create ArUco camera
aruco_camera = ArUcoCamera.ArUcoCamera(dimensions=(1920, 1080))
# 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)
# Capture frames from a live Full HD video stream (1920x1080)
while video_stream.is_alive():
frame = video_stream.read()
# Detect all board corners in frame
aruco_detector.detect_board(frame, 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)
# Append tracked board data for further calibration processing
aruco_camera.store_calibration_data(aruco_detector.board_corners, aruco_detector.board_corners_identifier)
# Start camera calibration processing for Full HD image resolution
print('Calibrating camera...')
aruco_camera.calibrate(expected_aruco_board)
# Print camera calibration data
print('Calibration succeeded!')
print(f'RMS:{aruco_camera.rms}')
print(f'Camera matrix:{aruco_camera.K}')
print(f'Distortion coefficients:{aruco_camera.D}')
# Save camera calibration data
aruco_camera.to_json('calibration.json')
```
Then, the camera calibration data are loaded to compensate optical distorsion during ArUco marker detection:
``` python
from argaze.ArUcoMarkers import ArUcoCamera
# Load camera calibration data
aruco_camera = ArUcoCamera.ArUcoCamera.from_json('./calibration.json')
```
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