def on_timer(self, *args):
if not self.need_redraw: return
self.need_redraw = False
self.mask.fill(0)
length = len(self.lasso_selection.dataspace_points)
if length == 0: return
def convert_poly(poly):
tmp = cv.asvector_Point2i(poly)
return cv.vector_vector_Point2i([tmp])
# 在遮罩数组上绘制套索多边形
for poly in self.lasso_selection.disjoint_selections:
poly = poly.astype(np.int)
print poly.shape
cv.fillPoly(self.mask_img, convert_poly(poly),
cv.Scalar(1, 1, 1, 1))
poly = N - poly # 绘制对称多边形
cv.fillPoly(self.mask_img, convert_poly(poly),
cv.Scalar(1, 1, 1, 1))
# 更新遮罩图像
self.data["mask_img"] = self.mask
# 更新滤波图像
data = self.data["filtered_img"]
data[:] = fft.ifft2(self.fimg * fft.fftshift(self.mask)).real
self.data["filtered_img"] = data
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):
img = self.img.clone()
cv.floodFill(img,
cv.Point(*self.point),
cv.Scalar(255, 0, 0, 255),
loDiff=cv.asScalar(self.lo_diff[0]),
upDiff=cv.asScalar(self.hi_diff[0]),
flags=self.option_)
self.data["img"] = img[:, :, ::-1]
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()
w, h = img.size().width, img.size().height
def blend(img, img2):
"""
混合两幅图像, 其中img2有4个通道
"""
#使用alpha通道计算img2的混和值
b = img2[:,:,3:] / 255.0
a = 1 - b # img的混合值
#混合两幅图像
img[:,:,:3] *= a
img[:,:,:3] += b * img2[:,:,:3]
img2[:] = 0
for i in xrange(0, w, w/10):
cv.line(img2, cv.Point(i,0), cv.Point(i, h),
cv.Scalar(0, 0, 255, i*255/w), 5)
blend(img, img2)
img2[:] = 0
for i in xrange(0, h, h/10):
cv.line(img2, cv.Point(0,i), cv.Point(w, i),
cv.Scalar(0, 255, 0, i*255/h), 5)
blend(img, img2)
cv.namedWindow("Draw Demo")
cv.imshow("Draw Demo", img)
cv.waitKey(0)
return 1
if __name__ == '__main__':
if len(sys.argv) == 3:
object_filename = sys.argv[1]
scene_filename = sys.argv[2]
else:
object_filename = "box.png"
scene_filename = "box_in_scene.png"
cv.namedWindow("Object", 1)
cv.namedWindow("Object Correspond", 1)
colors = [
cv.Scalar(0, 0, 255),
cv.Scalar(0, 128, 255),
cv.Scalar(0, 255, 255),
cv.Scalar(0, 255, 0),
cv.Scalar(255, 128, 0),
cv.Scalar(255, 255, 0),
cv.Scalar(255, 0, 0),
cv.Scalar(255, 0, 255),
cv.Scalar(255, 255, 255),
]
# read the two images
object_color = cv.imread(object_filename, cv.CV_LOAD_IMAGE_COLOR)
image = cv.imread(scene_filename, cv.CV_LOAD_IMAGE_GRAYSCALE)
if not object_color or not image:
print("Can not load %s and/or %s\n" \