def main():
folder = 'test_img/'
filename = '1Hill.JPG'
img_left = Image.open(folder + filename).convert('RGB')
img_left = np.array(img_left)
filename = '2Hill.JPG'
img_center = Image.open(folder + filename).convert('RGB')
img_center = np.array(img_center)
filename = '3Hill.JPG'
img_right = Image.open(folder + filename).convert('RGB')
img_right = np.array(img_right)
imgs = np.array(np.zeros((3)), dtype=object)
imgs[0] = img_left
imgs[1] = img_center
imgs[2] = img_right
img_mosaic = mymosaic(imgs)
plt.title('Final image')
plt.imshow(img_mosaic)
plt.show()
def stitching():
# load images
print("Opening images...")
sample1 = np.array(Image.open("test_img/1L.jpg").convert('RGB'))
sample2 = np.array(Image.open("test_img/1M.jpg").convert('RGB'))
sample3 = np.array(Image.open("test_img/1R.jpg").convert('RGB'))
philly1 = np.array(Image.open("images/philly-3.jpg").convert('RGB'))
philly2 = np.array(Image.open("images/philly-4.jpg").convert('RGB'))
philly3 = np.array(Image.open("images/philly-5.jpg").convert('RGB'))
# First mosaic: sample pics
image_inputs = np.array([sample1, sample2, sample3]).astype(np.ndarray)
mosaic1 = mymosaic(image_inputs)
# Second mosaic: custom pics
image_inputs = np.array([philly1, philly2, philly3]).astype(np.ndarray)
mosaic2 = mymosaic(image_inputs)
im_path = os.path.join(folder, filename)
reader = imageio.get_reader(im_path)
# if it is the first video
if numV == 0:
for i, im in enumerate(reader):
img_input.append([im])
lastone = im
lennow = len(reader)
while lennow < maxi:
img_input.append([lastone])
lennow = lennow + 1
numV = numV + 1
# next videos
else:
for i, im in enumerate(reader):
img_input[i].append(im)
lastone = im
lennow = len(reader)
while lennow < maxi:
img_input[lennow].append(lastone)
lennow = lennow + 1
img_input1 = []
for i in range(0, len(img_input) // 5):
img_input1.append(img_input[i * 5])
print("import video done!")
img_mosaic = mymosaic(img_input1)
myvideomosaic(img_mosaic)
import numpy as np
from PIL import Image
from mymosaic import mymosaic
import scipy.misc
if __name__ == '__main__':
I0 = np.array(Image.open("Test1_left.jpg").convert('RGB'))
I0 = scipy.misc.imresize(I0, [300, 400])
I1 = np.array(Image.open("Test1_middle.jpg").convert('RGB'))
I1 = scipy.misc.imresize(I1, [300, 400])
I2 = np.array(Image.open("Test1_right.jpg").convert('RGB'))
I2 = scipy.misc.imresize(I2, [300, 400])
input_img = [I0, I1, I2]
mymosaic(input_img)
x1 = x1[goodmask]
y1 = y1[goodmask]
X1 = np.copy(x1)
Y1 = np.copy(y1)
X2 = np.zeros((x1.shape))
Y2 = np.zeros((y1.shape))
X2 = x2[npgood]
Y2 = y2[npgood]
H32, inlier_ind = ransac_est_homography(X1, Y1, X2, Y2, 0.7)
print(H32)
plot_image_matching(X1, Y1, X2, Y2, img3_cyl, img2_cyl)
################################################################################
# img1 = cv2.imread('hill1.jpg')
# img2 = cv2.imread('hill2.jpg')
# img3 = cv2.imread('hill3.jpg')
# img1 = cv2.imread('.png')
# img2 = cv2.imread('hill2_cyl.png')
# img3 = cv2.imread('hill3_cyl.png')
finalOP = mymosaic(img1_cyl, img2_cyl, img3_cyl, H12, H32)
cv2.imwrite("collegeGreen_affine_final_uncarved.jpg", finalOP)
# if __name__ == '__main__':
# img1 = cv2.imread('hill1_cyl.png')
# img2 = cv2.imread('hill2_cyl.png')
# img3 = cv2.imread('hill3_cyl.png')
def main():
max_pts = 1000
left_image_filename = 'building1.JPG'
middle_image_filename = 'building2.JPG'
right_image_filename = 'building3.JPG'
img_left, gray_left = open_image(left_image_filename)
img_middle, gray_middle = open_image(middle_image_filename)
img_right, gray_right = open_image(right_image_filename)
corners_left = corner_detector(gray_left)
corners_middle = corner_detector(gray_middle)
corners_right = corner_detector(gray_right)
plotting_img_left = np.copy(img_left)
plotting_img_middle = np.copy(img_middle)
plotting_img_right = np.copy(img_right)
print('co', corners_left, corners_left.shape)
plotting_img_left[corners_left >= 0.01 * np.max(corners_left)] = [
255, 0, 0
]
plotting_img_middle[corners_middle >= 0.01 * np.max(corners_left)] = [
255, 0, 0
]
plotting_img_right[corners_right >= 0.01 * np.max(corners_left)] = [
255, 0, 0
]
plot_corner_harris(plotting_img_left, 'corner_harris_left_2')
plot_corner_harris(plotting_img_middle, 'corner_harris_middle_2')
plot_corner_harris(plotting_img_right, 'corner_harris_right_2')
x_left, y_left = anms(corners_left, max_pts)
x_middle, y_middle = anms(corners_middle, max_pts)
x_right, y_right = anms(corners_right, max_pts)
plot_anms(img_left, x_left, y_left)
plot_anms(img_middle, x_middle, y_middle)
plot_anms(img_right, x_right, y_right)
desc_left = feat_desc(gray_left, x_left, y_left)
desc_middle = feat_desc(gray_middle, x_middle, y_middle)
desc_right = feat_desc(gray_right, x_right, y_right)
matched_index_left_middle = feat_match(desc_left, desc_middle)
x1 = x_left[matched_index_left_middle != -1]
y1 = y_left[matched_index_left_middle != -1]
x2 = x_middle[matched_index_left_middle[matched_index_left_middle != -1]]
y2 = y_middle[matched_index_left_middle[matched_index_left_middle != -1]]
thresh = 0.5
H12, inlier_ind = ransac_est_homography(x1, y1, x2, y2, thresh)
bx1 = x1[inlier_ind == 0]
by1 = y1[inlier_ind == 0]
bx2 = x2[inlier_ind == 0]
by2 = y2[inlier_ind == 0]
x1 = x1[inlier_ind != 0]
y1 = y1[inlier_ind != 0]
x2 = x2[inlier_ind != 0]
y2 = y2[inlier_ind != 0]
plot_image_matching(x1, y1, x2, y2, bx1, by1, bx2, by2, img_left,
img_middle)
matched_index_right_middle = feat_match(desc_right, desc_middle)
x1 = x_right[matched_index_right_middle != -1]
y1 = y_right[matched_index_right_middle != -1]
x2 = x_middle[matched_index_right_middle[matched_index_right_middle != -1]]
y2 = y_middle[matched_index_right_middle[matched_index_right_middle != -1]]
thresh = 1
H32, inlier_ind = ransac_est_homography(x1, y1, x2, y2, thresh)
bx1 = x1[inlier_ind == 0]
by1 = y1[inlier_ind == 0]
bx2 = x2[inlier_ind == 0]
by2 = y2[inlier_ind == 0]
x1 = x1[inlier_ind != 0]
y1 = y1[inlier_ind != 0]
x2 = x2[inlier_ind != 0]
y2 = y2[inlier_ind != 0]
plot_image_matching(x1, y1, x2, y2, bx1, by1, bx2, by2, img_right,
img_middle)
mymosaic(img_left, img_middle, img_right, H12, H32)