def getK2(self):
k2 = DEFAULT_K2
try:
k2 = float(self.k2Entry.get())
except:
uiutils.error('You entered an invalid k2! Please try again.')
return k2
def getK1(self):
k1 = DEFAULT_K1
try:
k1 = float(self.k1Entry.get())
except:
uiutils.error('You entered an invalid k1! Please try again.')
return k1
def alignImagesClick(self):
if self.leftImage is None or self.rightImage is None:
uiutils.error(
'Both the images must be selected for alignment to '
'be possible!'
)
else:
self.compute()
def getFocalLength(self):
focalLength = 0
try:
focalLength = float(self.focalLengthEntry.get())
if focalLength > 0:
return focalLength
except:
pass
uiutils.error('You entered an invalid focal length! Please try again.')
return 0
def warpImage(self, *args):
if self.image is not None:
focalLength = float(self.focalLengthEntry.get())
k1 = self.getK1()
k2 = self.getK2()
warpedImage = warp.warpSpherical(self.image, focalLength, k1, k2)
self.setImage(warpedImage)
self.set_status('Warped image with focal length ' + str(focalLength))
elif len(args) == 0: # i.e., click on the button
uiutils.error('Select an image before warping!')
def compute(self, *args):
if self.images is not None and len(self.images) > 0:
f = self.getFocalLength()
if f <= 0:
return
k1 = self.getK1()
k2 = self.getK2()
processedImages = None
if self.motionModelVar.get() == alignment.eTranslate:
processedImages = [
warp.warpSpherical(i, f, k1, k2)
for i in self.images
]
else:
processedImages = self.images
t = np.eye(3)
ipv = []
for i in range(0, len(processedImages) - 1):
self.set_status(
'Computing mapping from {0} to {1}'.format(i, i+1)
)
ipv.append(
blend.ImageInfo('', processedImages[i], np.linalg.inv(t))
)
t = self.computeMapping(
processedImages[i], processedImages[i+1]
).dot(t)
ipv.append(blend.ImageInfo(
'', processedImages[len(processedImages)-1], np.linalg.inv(t))
)
t = self.computeMapping(
processedImages[len(processedImages)-1],
processedImages[0]
).dot(t)
if self.is360Var.get():
ipv.append(blend.ImageInfo(
'', processedImages[0], np.linalg.inv(t))
)
self.set_status('Blending Images')
self.setImage(blend.blendImages(
ipv, int(self.blendWidthSlider.get()),
self.is360Var.get() == 1
))
self.set_status('Panorama generated')
else:
uiutils.error(
'Select a folder with images before creating the panorama!'
)
def saveScreenshot(self):
if self.imageCanvas.has_image():
filename = tkFileDialog.asksaveasfilename(
parent=self, filetypes=uiutils.supportedFiletypes,
defaultextension=".png"
)
if filename:
self.imageCanvas.write_to_file(filename)
self.set_status('Saved screenshot to ' + filename)
else:
uiutils.error('Load image before taking a screenshot!')
def applyHomography(self):
if self.image is not None:
homography = uiutils.showMatrixDialog(
self, text='Apply', rows=3, columns=3
)
if homography is not None:
height, width, _ = self.image.shape
self.setImage(cv2.warpPerspective(
self.image, homography, (width, height))
)
self.set_status('Applied the homography.')
else:
uiutils.error('Select an image before applying a homography!')
def get_mapping(self):
if not (self.left_image_widget.has_image()
and self.right_image_widget.has_image()):
return None
left = self.left_image_widget.get_clicked_points_in_image_coordinates()
right = self.right_image_widget.get_clicked_points_in_image_coordinates(
)
num_points = min(len(left), len(right))
if num_points != 3:
uiutils.error(
'Please click on at exactly three corresponding points.')
return None
left = left[:num_points]
right = right[:num_points]
left = np.array([[x, y] for y, x in left], np.float32)
right = np.array([[x, y] for y, x in right], np.float32)
at = cv2.getAffineTransform(right, left)
return at
def get_mapping(self):
if not (self.left_image_widget.has_image() and
self.right_image_widget.has_image()):
return None
left = self.left_image_widget.get_clicked_points_in_image_coordinates()
right = self.right_image_widget.get_clicked_points_in_image_coordinates(
)
num_points = min(len(left), len(right))
if num_points != 3:
uiutils.error(
'Please click on at exactly three corresponding points.')
return None
left = left[:num_points]
right = right[:num_points]
left = np.array([[x, y] for y, x in left], np.float32)
right = np.array([[x, y] for y, x in right], np.float32)
at = cv2.getAffineTransform(right, left)
return at