def redraw(self):
edge_img = cv.Mat()
# 边缘检测
cv.Canny(self.img_gray, edge_img, self.th1, self.th2)
3 ###
# 计算结果图
if self.show_canny:
show_img = cv.Mat()
cv.cvtColor(edge_img, show_img, cv.CV_GRAY2BGR)
else:
show_img = self.img.clone()
4 ###
# 线段检测
theta = self.theta / 180.0 * np.pi
lines = cv.HoughLinesP(edge_img, self.rho, theta, self.hough_th,
self.minlen, self.maxgap)
for line in lines:
cv.line(show_img, cv.asPoint(line[:2]), cv.asPoint(line[2:]),
cv.CV_RGB(255, 0, 0), 2)
5 ###
# 圆形检测
circles = cv.HoughCircles(self.img_smooth,
3,
self.dp,
self.mindist,
param1=self.param1,
param2=self.param2)
for circle in circles:
cv.circle(show_img, cv.Point(int(circle[0]), int(circle[1])),
int(circle[2]), cv.CV_RGB(0, 255, 0), 2)
cv.imshow("Hough Demo", show_img)
def mouse_call_back(event, x, y, flags, user_data):
global seed
# 右键松开时，初始化种子图像
if event == cv.CV_EVENT_RBUTTONUP:
img2[:] = img[:]
markers[:] = 0
seed = 1
cv.imshow("Watershed Demo", img2)
if seed == len(marks_color): return
# 左键按下时，在种子图像上添加种子
if flags == cv.CV_EVENT_FLAG_LBUTTON:
pt = cv.Point(x, y)
cv.circle(markers, pt, 5, cv.Scalar(seed, seed, seed, seed),
cv.CV_FILLED)
cv.circle(img2, pt, 5, marks_color[seed], cv.CV_FILLED)
cv.imshow("Watershed Demo", img2)
# 左键松开时，使用watershed进行图像分割
if event == cv.CV_EVENT_LBUTTONUP:
seed += 1
tmp_markers = markers.clone()
cv.watershed(img, tmp_markers)
color_map = tmp_markers[:].astype(np.int)
img3 = img2.clone()
img4 = cv.asMat(palette[color_map])
cv.addWeighted(img3, 1.0, img4, mask_opacity, 0, img3)
cv.imshow("Watershed Demo", img3)
def mouse_call_back(event, x, y, flags, user_data):
global seed
# 右键松开时，初始化种子图像
if event == cv.CV_EVENT_RBUTTONUP:
img2[:] = img[:]
markers[:] = 0
seed = 1
cv.imshow("Watershed Demo", img2)
if seed == len(marks_color): return
# 左键按下时，在种子图像上添加种子
if flags == cv.CV_EVENT_FLAG_LBUTTON:
pt = cv.Point(x, y)
cv.circle(markers, pt, 5, cv.Scalar(seed,seed,seed,seed), cv.CV_FILLED)
cv.circle(img2, pt, 5, marks_color[seed], cv.CV_FILLED)
cv.imshow("Watershed Demo", img2)
# 左键松开时，使用watershed进行图像分割
if event == cv.CV_EVENT_LBUTTONUP:
seed += 1
tmp_markers = markers.clone()
cv.watershed(img, tmp_markers)
color_map = tmp_markers[:].astype(np.int)
img3 = img2.clone()
img4 = cv.asMat( palette[color_map] )
cv.addWeighted(img3, 1.0, img4, mask_opacity, 0, img3)
cv.imshow("Watershed Demo", img3)
def redraw(self):
edge_img = cv.Mat()
# 边缘检测
cv.Canny(self.img_gray, edge_img, self.th1, self.th2)
3###
# 计算结果图
if self.show_canny:
show_img = cv.Mat()
cv.cvtColor(edge_img, show_img, cv.CV_GRAY2BGR)
else:
show_img = self.img.clone()
4###
# 线段检测
theta = self.theta / 180.0 * np.pi
lines = cv.HoughLinesP(edge_img,
self.rho, theta, self.hough_th, self.minlen, self.maxgap)
for line in lines:
cv.line(show_img,
cv.asPoint(line[:2]),
cv.asPoint(line[2:]),
cv.CV_RGB(255, 0, 0), 2)
5###
# 圆形检测
circles = cv.HoughCircles(self.img_smooth, 3,
self.dp, self.mindist, param1=self.param1, param2=self.param2)
for circle in circles:
cv.circle(show_img,
cv.Point(int(circle[0]), int(circle[1])), int(circle[2]),
cv.CV_RGB(0, 255, 0), 2)
cv.imshow("Hough Demo", show_img)
def painter_updated(self):
for _, _, x, y in self.painter.track:
# 在储存选区的mask上绘制圆形
cv.circle(self.mask, cv.Point(int(x), int(y)), int(self.painter.r),
cv.Scalar(255,255,255,255), thickness=-1) # 宽度为负表示填充圆形
self.inpaint()
self.painter.track = []
self.painter.request_redraw()
def draw_circle(src, center, radius, color=(255.0, 0, 0), thickness=1):
if isinstance(center, tuple):
center = new_point(*center)
cv.circle(src, center, radius,
convert_color(color),
thickness=thickness,
lineType=cv.CV_AA
)
def draw_point(src, pt, color=(255, 0, 0), thickness= -1):
'''
'''
if isinstance(pt, (tuple, list)):
# pt = [int(pi for pi in pt]
pt = cv.Point2d(*pt)
color = convert_color(color)
cv.circle(src, pt, 5, color, thickness=thickness)
def painter_updated(self):
for _, _, x, y in self.painter.track:
# 在储存选区的mask上绘制圆形
cv.circle(self.mask,
cv.Point(int(x), int(y)),
int(self.painter.r),
cv.Scalar(255, 255, 255, 255),
thickness=-1) # 宽度为负表示填充圆形
self.inpaint()
self.painter.track = []
self.painter.request_redraw()
def draw_keypoints(self, img, keypoints, offset):
for kp in keypoints:
center = cv.Point(int(kp.pt.x) + offset, int(kp.pt.y))
cv.circle(img, center, int(kp.size * 0.25), cv.CV_RGB(255, 255, 0))
correspond[:object.rows, :object.cols] = object[:]
correspond[object.rows:, :image.cols] = image[:]
# find pairs
ptpairs = findPairs(surf, objectKeypoints, objectDescriptors,
imageKeypoints, imageDescriptors)
for pair in ptpairs:
cv.line(correspond, cv.asPoint(pair[0]),
cv.Point(int(pair[1].x), int(pair[1].y + object.rows)),
colors[8])
# locate planar object
if locatePlanarObject(ptpairs, src_corners, dst_corners):
for i in range(4):
r1 = dst_corners[i]
r2 = dst_corners[(i + 1) % 4]
cv.line(correspond, cv.Point(r1.x, r1.y + object.rows),
cv.Point(r2.x, r2.y + object.rows), colors[8])
# show the object correspondents
cv.imshow("Object Correspond", correspond)
# draw circles
for keypt in objectKeypoints:
cv.circle(object_color, cv.asPoint(keypt.pt),
int(keypt.size * 1.2 / 9. * 2), colors[0], 1, 8, 0)
cv.imshow("Object", object_color)
cv.waitKey(0)
def draw_keypoints(self, img, keypoints, offset):
for kp in keypoints:
center = cv.Point(int(kp.pt.x)+offset, int(kp.pt.y))
cv.circle(img, center, int(kp.size*0.25), cv.CV_RGB(255,255,0))
# create a correspond Mat
correspond = cv.Mat(image.rows+object.rows, image.cols, cv.CV_8UC1, cv.Scalar(0))
# copy the images to correspond -- numpy way
correspond[:object.rows, :object.cols] = object[:]
correspond[object.rows:, :image.cols] = image[:]
# find pairs
ptpairs = findPairs(surf, objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors)
for pair in ptpairs:
cv.line( correspond, cv.asPoint(pair[0]), cv.Point(int(pair[1].x), int(pair[1].y+object.rows)), colors[8] )
# locate planar object
if locatePlanarObject( ptpairs, src_corners, dst_corners ):
for i in range(4):
r1 = dst_corners[i]
r2 = dst_corners[(i+1)%4]
cv.line( correspond, cv.Point(r1.x, r1.y+object.rows ), cv.Point(r2.x, r2.y+object.rows ), colors[8] )
# show the object correspondents
cv.imshow("Object Correspond", correspond)
# draw circles
for keypt in objectKeypoints:
cv.circle(object_color, cv.asPoint(keypt.pt), int(keypt.size*1.2/9.*2), colors[0], 1, 8, 0)
cv.imshow("Object", object_color)
cv.waitKey(0)
