def __findkp__(self, givenpoint):
boxsize = 15
refmatcher = ORB_matcher(nfeatures=20, scaleFactor=1.1,
nlevels=5) # 重要参数：推荐nfeature为tolerence的两倍
defmatcher = ORB_matcher(nfeatures=20, scaleFactor=1.1, nlevels=5)
while boxsize < 100:
refbox = [(givenpoint[0] - boxsize, givenpoint[1] - boxsize),
(givenpoint[0] + boxsize + 1,
givenpoint[1] + boxsize + 1)]
if any(refbox) < 0:
break
refblock = self.refimg[refbox[0][1]:refbox[1][1],
refbox[0][0]:refbox[1][0]]
kp1, des1 = refmatcher.detect(refblock, show=0)
if des1 is not None:
defbox = [(givenpoint[0] - boxsize - 50,
givenpoint[1] - boxsize - 50),
(givenpoint[0] + boxsize + 51,
givenpoint[1] + boxsize + 51)]
defblock = self.defimg[defbox[0][1]:defbox[1][1],
defbox[0][0]:defbox[1][0]]
if any(defbox) < 0:
print("out of range")
break
kp2, des2 = defmatcher.detect(defblock, show=0)
defmatcher.match(des1, des2)
if len(
defmatcher.matches
) > 10: # 重要参数：增大会增加匹配精度，但会减少匹配数量；根据特征点稀疏状况调整，特征点稀疏位置不方便使用太大
return kp1, kp2, des1, defmatcher.matches, boxsize
boxsize += 5
print("Key Point Not Found!")
return None, None, None, None, None
def __refreshdisp__(self, show):
matcher = ORB_matcher(nfeatures=100, scaleFactor=1.2, nlevels=10)
tempshowimg = self.showimg.copy()
for i in range(len(self.refpoints)):
defbox = [(int(self.refpoints[i][0][0]) - 200,
int(self.refpoints[i][0][1]) - 200),
(int(self.refpoints[i][0][0]) + 200,
int(self.refpoints[i][0][1]) + 200)]
defblock = self.defimg[defbox[0][1]:defbox[1][1],
defbox[0][0]:defbox[1][0]]
if any(defbox) < 0:
print("out of range")
break
kp2, des2 = matcher.detect(defblock, show=0)
des1 = self.refpoints[i][1].astype("uint8")
matcher.match(des1, des2)
if matcher.matches is not None:
distance = matcher.matches[0].distance
for j in range(len(matcher.matches)):
id2 = matcher.matches[0].trainIdx
if matcher.matches[j].distance < distance:
distance = matcher.matches[j].distance
id2 = matcher.matches[j].trainIdx
x_ref = self.refpoints[i][0][0]
y_ref = self.refpoints[i][0][1]
x_def = kp2[id2].pt[0] - 200 + int(self.refpoints[i][0][0])
y_def = kp2[id2].pt[1] - 200 + int(self.refpoints[i][0][1])
u = x_def - x_ref
v = y_def - y_ref
self.refpoints[i][2] = [u, v]
cv2.circle(tempshowimg, (int(x_ref / 3), int(y_ref / 3)), 1,
(255, 255, 255), 2)
cv2.circle(tempshowimg, (int(x_def / 3), int(y_def / 3)), 1,
(255, 255, 255), 2)
if show:
position1 = (int(self.refpoints[i][0][0] / 3) + 5,
int(self.refpoints[i][0][1] / 3) - 10)
position2 = (int(self.refpoints[i][0][0] / 3) + 5,
int(self.refpoints[i][0][1] / 3) + 10)
text1 = "U=" + str(np.round(u, 3))
text2 = "V=" + str(np.round(v, 3))
cv2.putText(tempshowimg,
text1,
position1,
fontFace=cv2.FONT_HERSHEY_COMPLEX,
fontScale=0.5,
color=(255, 255, 255),
thickness=1)
cv2.putText(tempshowimg,
text2,
position2,
fontFace=cv2.FONT_HERSHEY_COMPLEX,
fontScale=0.5,
color=(255, 255, 255),
thickness=1)
self.tempshowimg = tempshowimg