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import numpy as np
import h5py
import cv2
def normalize_intrinsic(x, K):
# print(x,K)
return (x - K[:2, 2]) / np.diag(K)[:2]
def normalize_size(x, size, scale=1):
size = size.reshape([1, 2])
norm_fac = size.max()
return (x - size / 2 + 0.5) / (norm_fac * scale)
def np_skew_symmetric(v):
zero = np.zeros_like(v[:, 0])
M = np.stack(
[
zero,
-v[:, 2],
v[:, 1],
v[:, 2],
zero,
-v[:, 0],
-v[:, 1],
v[:, 0],
zero,
],
axis=1,
)
return M
def draw_points(img, points, color=(0, 255, 0), radius=3):
dp = [(int(points[i, 0]), int(points[i, 1])) for i in range(points.shape[0])]
for i in range(points.shape[0]):
cv2.circle(img, dp[i], radius=radius, color=color)
return img
def draw_match(
img1,
img2,
corr1,
corr2,
inlier=[True],
color=None,
radius1=1,
radius2=1,
resize=None,
):
if resize is not None:
scale1, scale2 = [img1.shape[1] / resize[0], img1.shape[0] / resize[1]], [
img2.shape[1] / resize[0],
img2.shape[0] / resize[1],
]
img1, img2 = cv2.resize(img1, resize, interpolation=cv2.INTER_AREA), cv2.resize(
img2, resize, interpolation=cv2.INTER_AREA
)
corr1, corr2 = (
corr1 / np.asarray(scale1)[np.newaxis],
corr2 / np.asarray(scale2)[np.newaxis],
)
corr1_key = [
cv2.KeyPoint(corr1[i, 0], corr1[i, 1], radius1) for i in range(corr1.shape[0])
]
corr2_key = [
cv2.KeyPoint(corr2[i, 0], corr2[i, 1], radius2) for i in range(corr2.shape[0])
]
assert len(corr1) == len(corr2)
draw_matches = [cv2.DMatch(i, i, 0) for i in range(len(corr1))]
if color is None:
color = [(0, 255, 0) if cur_inlier else (0, 0, 255) for cur_inlier in inlier]
if len(color) == 1:
display = cv2.drawMatches(
img1,
corr1_key,
img2,
corr2_key,
draw_matches,
None,
matchColor=color[0],
singlePointColor=color[0],
flags=4,
)
else:
height, width = max(img1.shape[0], img2.shape[0]), img1.shape[1] + img2.shape[1]
display = np.zeros([height, width, 3], np.uint8)
display[: img1.shape[0], : img1.shape[1]] = img1
display[: img2.shape[0], img1.shape[1] :] = img2
for i in range(len(corr1)):
left_x, left_y, right_x, right_y = (
int(corr1[i][0]),
int(corr1[i][1]),
int(corr2[i][0] + img1.shape[1]),
int(corr2[i][1]),
)
cur_color = (int(color[i][0]), int(color[i][1]), int(color[i][2]))
cv2.line(
display,
(left_x, left_y),
(right_x, right_y),
cur_color,
1,
lineType=cv2.LINE_AA,
)
return display
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