# Revision history [back]

### WarpAfffine blurs the image

I am trying to rotate an image based on the rotation matrix I get from the camera. It does it good, however at every loop my image gets more blurry. What might be the reason? I've tried all the tags of WarpAffine, no luck. Here is my code:

        toBeRotatedShuttle = shuttleIcon.copy()
rows, cols, w = toBeRotatedShuttle.shape
angle = get_camera_rotation(smoothenedMatrix)
angleInDegrees = round(math.degrees(math.asin(angle)),2) # convert radian to degrees
rotationMatrix = cv2.getRotationMatrix2D((cols / 2, rows / 2), angleInDegrees, 1)
shuttleIcon = cv2.warpAffine(toBeRotatedShuttle, rotationMatrix, (cols, rows), cv2.INTER_AREA)


and here is my rotation matrix function:

'''Takes 2 vectors and returns the rotation matrix between these 2 vectors'''
def get_camera_rotation(homographyMatrix):
# Points in the camera frame
camera_pts = np.float32([[round(CAM_WIDTH / 2), round(CAM_HEIGHT / 2)],
[round(10 + CAM_WIDTH / 2), round(10 + CAM_HEIGHT / 2)]]).reshape(-1, 1, 2)
# Find these points in the projector image
proj_pts = cv2.perspectiveTransform(camera_pts, homographyMatrix)

# Find the vectors between the sets of points
camera_vector = (camera_pts[0][0][0] - camera_pts[1][0][0], camera_pts[0][0][1] - camera_pts[1][0][1])
proj_vector = (proj_pts[0][0][0] - proj_pts[1][0][0], proj_pts[0][0][1] - proj_pts[1][0][1])

# change the vectors to unit vectors
camera_vector = camera_vector / np.absolute(np.linalg.norm(camera_vector))
proj_vector = proj_vector / np.absolute(np.linalg.norm(proj_vector))

# calculate the angle between the 2 vectors
# Change the sign of the angle if the rocket is turning the opposite way to desired
#sine of the angle
sinAngle = camera_vector[0] * proj_vector[1] - camera_vector[1] * proj_vector[0]
#angle between the vectors
angle = np.arcsin(np.clip(sinAngle, -1.0, 1.0))

#print("The angle between the camera and the projector is:")
#print(angle)
# calculate the 2D rotation matrix from this angle
rotation_matrix = np.matrix([[np.cos(angle), -1 * np.sin(angle)], [np.sin(angle), np.cos(angle)]])
return angle


Any thoughts?

### WarpAfffine blurs the image

I am trying to rotate an image based on the rotation matrix I get from the camera. It does it good, however at every loop my image gets more blurry. What might be the reason? I've tried all the tags of WarpAffine, no luck. Here is my code:

        toBeRotatedShuttle = shuttleIcon.copy()
rows, cols, w = toBeRotatedShuttle.shape
angle = get_camera_rotation(smoothenedMatrix)
angleInDegrees = round(math.degrees(math.asin(angle)),2) # convert radian to degrees
rotationMatrix = cv2.getRotationMatrix2D((cols / 2, rows / 2), angleInDegrees, 1)
shuttleIcon = cv2.warpAffine(toBeRotatedShuttle, rotationMatrix, (cols, rows), cv2.INTER_AREA)


and here is my rotation matrix function:

'''Takes 2 vectors and returns the rotation matrix between these 2 vectors'''
def get_camera_rotation(homographyMatrix):
# Points in the camera frame
camera_pts = np.float32([[round(CAM_WIDTH / 2), round(CAM_HEIGHT / 2)],
[round(10 + CAM_WIDTH / 2), round(10 + CAM_HEIGHT / 2)]]).reshape(-1, 1, 2)
# Find these points in the projector image
proj_pts = cv2.perspectiveTransform(camera_pts, homographyMatrix)

# Find the vectors between the sets of points
camera_vector = (camera_pts[0][0][0] - camera_pts[1][0][0], camera_pts[0][0][1] - camera_pts[1][0][1])
proj_vector = (proj_pts[0][0][0] - proj_pts[1][0][0], proj_pts[0][0][1] - proj_pts[1][0][1])

# change the vectors to unit vectors
camera_vector = camera_vector / np.absolute(np.linalg.norm(camera_vector))
proj_vector = proj_vector / np.absolute(np.linalg.norm(proj_vector))

# calculate the angle between the 2 vectors
# Change the sign of the angle if the rocket is turning the opposite way to desired
#sine of the angle
sinAngle = camera_vector[0] * proj_vector[1] - camera_vector[1] * proj_vector[0]
#angle between the vectors
angle = np.arcsin(np.clip(sinAngle, -1.0, 1.0))

#print("The angle between the camera and the projector is:")
#print(angle)
# calculate the 2D rotation matrix from this angle
rotation_matrix = np.matrix([[np.cos(angle), -1 * np.sin(angle)], [np.sin(angle), np.cos(angle)]])
return angle


Any thoughts?

### WarpAfffine blurs the image

I am trying to rotate an image based on the rotation matrix I get from the camera. It does it good, however at every loop my image gets more blurry. What might be the reason? I've tried all the tags of WarpAffine, no luck. Here is my code:

        toBeRotatedShuttle = shuttleIcon.copy()
rows, cols, w = toBeRotatedShuttle.shape
angle = get_camera_rotation(smoothenedMatrix)
angleInDegrees = round(math.degrees(math.asin(angle)),2) # convert radian to degrees
rotationMatrix = cv2.getRotationMatrix2D((cols / 2, rows / 2), angleInDegrees, 1)
shuttleIcon = cv2.warpAffine(toBeRotatedShuttle, rotationMatrix, (cols, rows), cv2.INTER_AREA)


and here is my rotation matrix function:

'''Takes 2 vectors and returns the rotation matrix between these 2 vectors'''
def get_camera_rotation(homographyMatrix):
# Points in the camera frame
camera_pts = np.float32([[round(CAM_WIDTH / 2), round(CAM_HEIGHT / 2)],
[round(10 + CAM_WIDTH / 2), round(10 + CAM_HEIGHT / 2)]]).reshape(-1, 1, 2)
# Find these points in the projector image
proj_pts = cv2.perspectiveTransform(camera_pts, homographyMatrix)

# Find the vectors between the sets of points
camera_vector = (camera_pts[0][0][0] - camera_pts[1][0][0], camera_pts[0][0][1] - camera_pts[1][0][1])
proj_vector = (proj_pts[0][0][0] - proj_pts[1][0][0], proj_pts[0][0][1] - proj_pts[1][0][1])

# change the vectors to unit vectors
camera_vector = camera_vector / np.absolute(np.linalg.norm(camera_vector))
proj_vector = proj_vector / np.absolute(np.linalg.norm(proj_vector))

# calculate the angle between the 2 vectors
# Change the sign of the angle if the rocket is turning the opposite way to desired
#sine of the angle
sinAngle = camera_vector[0] * proj_vector[1] - camera_vector[1] * proj_vector[0]
#angle between the vectors
angle = np.arcsin(np.clip(sinAngle, -1.0, 1.0))

#print("The angle between the camera and the projector is:")
#print(angle)
# calculate the 2D rotation matrix from this angle
rotation_matrix = np.matrix([[np.cos(angle), -1 * np.sin(angle)], [np.sin(angle), np.cos(angle)]])
return angle


Any thoughts?