def processImages(self, image1):
"""
The rest of the logic to stitch the image
Args:
image1: image from camera 1
Returns:
finalImage: image to be displayed to user to confirm it is correct
"""
configCom = ConfigCommunicator()
# Grabs skew info from config, and creates instance of ScannerCamera()
skewObject = ScannerCamera(1)
mtx, dist, newmtx = configCom.getSkew(1)
skewObject.setSkewMtx(mtx, dist, newmtx)
# Process board image
image1 = skew_correction(image1, skewObject)
# Grabs scale info from config
dictionary = configCom.getScale()
scale_detect = ScaleDetection()
scale_detect.setScale(dictionary['x_scale'], dictionary['y_scale'], dictionary['units'])
#finalImage = stitch_images(image1, image2)
finalImage = image1
cv2.imwrite('FinalImage.jpg', finalImage)
contours, contourImage = find_contours(np.array(finalImage, dtype=np.uint8))
xscale, yscale, units = get_scale(scale_detect)
export_json(contours, xscale, yscale, units) #do I need to do something with return value?
return contourImage #do we want to show the contours on this as well?
def skew_calibration(calibImages, camera_number, scanner_camera):
"""
Calculate skew correction values
Args:
calibImages
camera_number
Returns:
None
"""
scanner_camera.setSkewCorrectionValues(calibImages)
# Config file
configCom = ConfigCommunicator()
configCom.setSkew(scanner_camera.skew_mtx, scanner_camera.skew_dist, scanner_camera.skew_newcameramtx, camera_number)
configCom.saveConfig()
def scale_calibration(scaleDetect, image, objx, objy, units):
"""
calibrates the scale and saves to config file
Args:
scaleDetect (ScaleDetection):
image: the calibration image
objx: width of calibration object
objy: height of calibration object
units (string): units to use
Returns:
True on success, False on failure
"""
configCom = ConfigCommunicator()
success = scaleDetect.calibrate(image, objx, objy, units)
dictionary = {'x_scale': str(scaleDetect.x_scale), 'y_scale': str(scaleDetect.y_scale), 'units': scaleDetect.units}
configCom.setScale(dictionary)
configCom.saveConfig()
return success
