本文整理汇总了Python中cv2.GC_INIT_WITH_RECT属性的典型用法代码示例。如果您正苦于以下问题：Python cv2.GC_INIT_WITH_RECT属性的具体用法？Python cv2.GC_INIT_WITH_RECT怎么用？Python cv2.GC_INIT_WITH_RECT使用的例子？那么恭喜您, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类cv2的用法示例。
在下文中一共展示了cv2.GC_INIT_WITH_RECT属性的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: run_grabcut
# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import GC_INIT_WITH_RECT [as 别名]
def run_grabcut(img_orig, rect_final):
# Initialize the mask
mask = np.zeros(img_orig.shape[:2],np.uint8)
# Extract the rectangle and set the region of
# interest in the above mask
x,y,w,h = rect_final
mask[y:y+h, x:x+w] = 1
# Initialize background and foreground models
bgdModel = np.zeros((1,65), np.float64)
fgdModel = np.zeros((1,65), np.float64)
# Run Grabcut algorithm
cv2.grabCut(img_orig, mask, rect_final, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)
# Extract new mask
mask2 = np.where((mask==2)|(mask==0),0,1).astype('uint8')
# Apply the above mask to the image
img_orig = img_orig*mask2[:,:,np.newaxis]
# Display the image
cv2.imshow('Output', img_orig) 示例2: image_matting
# 需要导入模块: import cv2 [as 别名]
# 或者: from cv2 import GC_INIT_WITH_RECT [as 别名]
def image_matting(self, image_file, shape, iteration=10):
points = shape['points']
xmin, ymin, xmax, ymax = Grab_cut.convertPoints2BndBox(points)
self.width = xmax - xmin
self.height = ymax - ymin
src_img = cv2.imread(image_file)
mask = np.zeros(src_img.shape[:2], np.uint8)
bgdModel = np.zeros((1, 65), np.float64)
fgdModel = np.zeros((1, 65), np.float64)
rect = (xmin, ymin, self.width, self.height)
# Grabcut
cv2.grabCut(src_img, mask, rect, bgdModel, fgdModel,
iteration, cv2.GC_INIT_WITH_RECT)
r_channel, g_channel, b_channel = cv2.split(src_img)
a_channel = np.where((mask == 2) | (mask == 0), 0, 255).astype('uint8')
# crop image space
for row in range(ymin, ymax):
if sum(r_channel[row, xmin:xmax + 1]) > 0:
out_ymin = row
break
for row in range(ymin, ymax)[::-1]:
if sum(r_channel[row, xmin:xmax + 1]) > 0:
out_ymax = row + 1
break
for col in range(xmin, xmax):
if sum(a_channel[ymin:ymax + 1, col]) > 0:
out_xmin = col
break
for col in range(xmin, xmax)[::-1]:
if sum(a_channel[ymin:ymax + 1, col]) > 0:
out_xmax = col + 1
break
# output image
img_RGBA = cv2.merge((r_channel[out_ymin:out_ymax, out_xmin:out_xmax],
g_channel[out_ymin:out_ymax, out_xmin:out_xmax],
b_channel[out_ymin:out_ymax, out_xmin:out_xmax],
a_channel[out_ymin:out_ymax, out_xmin:out_xmax]))
return img_RGBA