def test_warpImagePair():
image_1 = cv2.imread("images/source/panorama_1/1.jpg")
image_2 = cv2.imread("images/source/panorama_1/2.jpg")
image_1_kp, image_2_kp, matches = assignment8.findMatchesBetweenImages(
image_1, image_2, 20)
homography = assignment8.findHomography(image_1_kp, image_2_kp, matches)
warped_image = assignment8.warpImagePair(image_1, image_2, homography)
# Read in answer that has the correct type / shape.
type_answer = cv2.imread("images/testing/warped_image_1_2.jpg")
print "Evaluating warpImagePair."
# Test for type.
if not type(warped_image) == type(type_answer):
raise TypeError(
("Error - warped_image has type {}. " +
"Expected type is {}.").format(type(warped_image),
type(type_answer)))
# Test for shape.
if abs(np.sum(np.subtract(warped_image.shape, type_answer.shape))) > 200:
print("WARNING - warped_image has shape {}. " +
"Expected shape is around {}.").format(warped_image.shape,
type_answer.shape)
print "warpImagePair testing passed."
return True
def main(image_files, output_folder):
""" Generate a panorama from the images in the source folder """
inputs = ((name, cv2.imread(name)) for name in sorted(image_files)
if path.splitext(name)[-1][1:].lower() in EXTENSIONS)
# start with the first image in the folder and process each image in order
name, pano = inputs.next()
print "\n Starting with: {}".format(name)
for name, next_img in inputs:
if next_img is None:
print "\nUnable to proceed: {} failed to load.".format(name)
return
print " Adding: {}".format(name)
kp1, kp2, matches = a8.findMatchesBetweenImages(pano, next_img, 10)
homography = a8.findHomography(kp1, kp2, matches)
min_xy, max_xy = a8.getBoundingCorners(pano, next_img, homography)
pano = a8.warpCanvas(pano, homography, min_xy, max_xy)
pano = a8.blendImagePair(pano, next_img, -min_xy)
cv2.imwrite(path.join(output_folder, "output.jpg"), pano)
print " Done!"
def test_warpImagePair():
image_1 = cv2.imread("images/source/panorama_1/1.jpg")
image_2 = cv2.imread("images/source/panorama_1/2.jpg")
image_1_kp, image_2_kp, matches = assignment8.findMatchesBetweenImages(
image_1, image_2, 20)
homography = assignment8.findHomography(image_1_kp, image_2_kp, matches)
warped_image = assignment8.warpImagePair(image_1, image_2, homography)
# Read in answer that has the correct type / shape.
type_answer = cv2.imread("images/testing/warped_image_1_2.jpg")
print "Evaluating warpImagePair."
# Test for type.
if not type(warped_image) == type(type_answer):
raise TypeError(
("Error - warped_image has type {}. " +
"Expected type is {}.").format(type(warped_image),
type(type_answer)))
# Test for shape.
if abs(np.sum(np.subtract(warped_image.shape, type_answer.shape))) > 200:
print ("WARNING - warped_image has shape {}. " +
"Expected shape is around {}.").format(warped_image.shape,
type_answer.shape)
print "warpImagePair testing passed."
return True
def test_findMatchesBetweenImages():
""" This script will perform a unit test on the matching function.
"""
# Hard code output matches.
image_1 = cv2.imread("images/source/panorama_1/1.jpg")
image_2 = cv2.imread("images/source/panorama_1/2.jpg")
print "Evaluating findMatchesBetweenImages."
image_1_kp, image_2_kp, matches = \
assignment8.findMatchesBetweenImages(image_1, image_2, 20)
if not type(image_1_kp) == list:
raise TypeError(
"Error - image_1_kp has type {}. Expected type is {}.".format(
type(image_1_kp), list))
if len(image_1_kp) > 0 and \
not type(image_1_kp[0]) == type(cv2.KeyPoint()):
raise TypeError(("Error - The items in image_1_kp have type {}. " + \
"Expected type is {}.").format(type(image_1_kp[0]),
type(cv2.KeyPoint())))
if not type(image_2_kp) == list:
raise TypeError(
"Error - image_2_kp has type {}. Expected type is {}.".format(
type(image_2_kp), list))
if len(image_2_kp) > 0 and \
not type(image_2_kp[0]) == type(cv2.KeyPoint()):
raise TypeError(("Error - The items in image_2_kp have type {}. " + \
"Expected type is {}.").format(type(image_2_kp[0]),
type(cv2.KeyPoint())))
if not type(matches) == list:
raise TypeError(
"Error - matches has type {}. Expected type is {}. ".format(
type(matches), list))
if len(matches) > 0 and not type(matches[0]) == type(cv2.DMatch()):
raise TypeError(("Error - The items in matches have type {}. " + \
"Expected type is {}.").format(type(matches[0]),
type(cv2.DMatch())))
print "findMatchesBetweenImages testing passed."
return True
def test_findMatchesBetweenImages():
""" This script will perform a unit test on the matching function.
"""
# Hard code output matches.
image_1 = cv2.imread("images/source/panorama_1/1.jpg")
image_2 = cv2.imread("images/source/panorama_1/2.jpg")
print "Evaluating findMatchesBetweenImages."
image_1_kp, image_2_kp, matches = \
assignment8.findMatchesBetweenImages(image_1, image_2, 20)
if not type(image_1_kp) == list:
raise TypeError(
"Error - image_1_kp has type {}. Expected type is {}.".format(
type(image_1_kp), list))
if len(image_1_kp) > 0 and \
not type(image_1_kp[0]) == type(cv2.KeyPoint()):
raise TypeError(("Error - The items in image_1_kp have type {}. " + \
"Expected type is {}.").format(type(image_1_kp[0]),
type(cv2.KeyPoint())))
if not type(image_2_kp) == list:
raise TypeError(
"Error - image_2_kp has type {}. Expected type is {}.".format(
type(image_2_kp), list))
if len(image_2_kp) > 0 and \
not type(image_2_kp[0]) == type(cv2.KeyPoint()):
raise TypeError(("Error - The items in image_2_kp have type {}. " + \
"Expected type is {}.").format(type(image_2_kp[0]),
type(cv2.KeyPoint())))
if not type(matches) == list:
raise TypeError(
"Error - matches has type {}. Expected type is {}. ".format(
type(matches), list))
if len(matches) > 0 and not type(matches[0]) == type(cv2.DMatch()):
raise TypeError(("Error - The items in matches have type {}. " + \
"Expected type is {}.").format(type(matches[0]),
type(cv2.DMatch())))
print "findMatchesBetweenImages testing passed."
return True
def test_findHomography():
# Hard code output matches.
image_1 = cv2.imread("images/source/panorama_1/1.jpg")
image_2 = cv2.imread("images/source/panorama_1/2.jpg")
image_1_kp, image_2_kp, matches = assignment8.findMatchesBetweenImages(
image_1, image_2, 20)
homography = assignment8.findHomography(image_1_kp, image_2_kp, matches)
ans = np.array([[1.43341688e+00, 2.97957049e-02, -1.10725647e+03],
[1.71655562e-01, 1.36708332e+00, -5.06635922e+02],
[1.06589023e-04, 6.16589688e-05, 1.00000000e+00]])
print "Evaluating findHomography."
# Test for type.
if not type(homography) == type(ans):
raise TypeError(
("Error - homography has type {}. " +
"Expected type is {}.").format(type(homography), type(ans)))
# Test for shape.
if not homography.shape == ans.shape:
raise ValueError(
("Error - homography has shape {}." +
" Expected shape is {}.").format(homography.shape, ans.shape))
if not type(homography[0][0]) == type(ans[0][0]):
raise TypeError(
("Error - The items in homography have type {}. " +
"Expected type is {}.").format(type(homography), type(ans)))
# if not np.max(abs(np.subtract(homography, ans))) < 2.0:
# print "If your homography looks significantly different make sure " + \
# "you look at the warped image output. That is the only way " + \
# "of knowing if it is correct. Images should be aligned well. " + \
# "We expect ORB & SIFT to output equivalent homographies, but " + \
# "if you run into this error please take a look at your output."
# raise ValueError(
# ("Error - your output seems to be significantly different, " +
# "please verify this yourself. \n Given output {}. \n" +
# "Expected output {}. \n").format(homography, ans))
print "findHomography testing passed."
return True
def test_findHomography():
# Hard code output matches.
image_1 = cv2.imread("images/source/panorama_1/1.jpg")
image_2 = cv2.imread("images/source/panorama_1/2.jpg")
image_1_kp, image_2_kp, matches = assignment8.findMatchesBetweenImages(
image_1, image_2, 20)
homography = assignment8.findHomography(image_1_kp, image_2_kp, matches)
ans = np.array([[1.43341688e+00, 2.97957049e-02, -1.10725647e+03],
[1.71655562e-01, 1.36708332e+00, -5.06635922e+02],
[1.06589023e-04, 6.16589688e-05, 1.00000000e+00]])
print "Evaluating findHomography."
# Test for type.
if not type(homography) == type(ans):
raise TypeError(
("Error - homography has type {}. " +
"Expected type is {}.").format(type(homography), type(ans)))
# Test for shape.
if not homography.shape == ans.shape:
raise ValueError(
("Error - homography has shape {}." +
" Expected shape is {}.").format(homography.shape, ans.shape))
if not type(homography[0][0]) == type(ans[0][0]):
raise TypeError(
("Error - The items in homography have type {}. " +
"Expected type is {}.").format(type(homography), type(ans)))
# if not np.max(abs(np.subtract(homography, ans))) < 2.0:
# print "If your homography looks significantly different make sure " + \
# "you look at the warped image output. That is the only way " + \
# "of knowing if it is correct. Images should be aligned well. " + \
# "We expect ORB & SIFT to output equivalent homographies, but " + \
# "if you run into this error please take a look at your output."
# raise ValueError(
# ("Error - your output seems to be significantly different, " +
# "please verify this yourself. \n Given output {}. \n" +
# "Expected output {}. \n").format(homography, ans))
print "findHomography testing passed."
return True
panorama_filepaths = []
for filename in filenames:
name, ext = os.path.splitext(filename)
if ext.lower() in exts:
panorama_filepaths.append(os.path.join(dirname, filename))
panorama_filepaths.sort()
for pan_fp in panorama_filepaths:
panorama_inputs.append(cv2.imread(pan_fp))
if len(panorama_inputs) > 1:
print ("Found {} images in folder {}. " + \
"Processing them.").format(len(panorama_inputs), dirname)
else:
continue
print "Computing matches."
cur_img = panorama_inputs[0]
for new_img in panorama_inputs[1:]:
image_1_kp, image_2_kp, matches = \
assignment8.findMatchesBetweenImages(cur_img, new_img, 20)
print "Computing homography."
homography = assignment8.findHomography(image_1_kp, image_2_kp,
matches)
print "Warping the image pair."
cur_img = assignment8.warpImagePair(cur_img, new_img, homography)
print "Writing output image to {}".format(outfolder)
cv2.imwrite(os.path.join(outfolder, setname) + ".jpg", cur_img)
panorama_filepaths = []
for filename in filenames:
name, ext = os.path.splitext(filename)
if ext.lower() in exts:
panorama_filepaths.append(os.path.join(dirname, filename))
panorama_filepaths.sort()
for pan_fp in panorama_filepaths:
panorama_inputs.append(cv2.imread(pan_fp))
if len(panorama_inputs) > 1:
print ("Found {} images in folder {}. " + \
"Processing them.").format(len(panorama_inputs), dirname)
else:
continue
print "Computing matches."
cur_img = panorama_inputs[0]
for new_img in panorama_inputs[1:]:
image_1_kp, image_2_kp, matches = \
assignment8.findMatchesBetweenImages(cur_img, new_img, 20)
print "Computing homography."
homography = assignment8.findHomography(image_1_kp, image_2_kp,
matches)
print "Warping the image pair."
cur_img = assignment8.warpImagePair(cur_img, new_img, homography)
print "Writing output image to {}".format(outfolder)
cv2.imwrite(os.path.join(outfolder, setname) + ".jpg", cur_img)