Camera calibration
==================

Any camera device have to be calibrated to compensate its optical distorsion.

![Camera calibration](../../img/camera_calibration.png)

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.

![Calibration step](../../img/camera_calibration_step.png)

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')
```