本文整理汇总了Python中pyclipper.PyclipperOffset方法的典型用法代码示例。如果您正苦于以下问题:Python pyclipper.PyclipperOffset方法的具体用法?Python pyclipper.PyclipperOffset怎么用?Python pyclipper.PyclipperOffset使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pyclipper
的用法示例。
在下文中一共展示了pyclipper.PyclipperOffset方法的7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: shrink
# 需要导入模块: import pyclipper [as 别名]
# 或者: from pyclipper import PyclipperOffset [as 别名]
def shrink(bboxes, rate, max_shr=20):
rate = rate * rate
shrinked_bboxes = []
for bbox in bboxes:
area = plg.Polygon(bbox).area()
peri = perimeter(bbox)
pco = pyclipper.PyclipperOffset()
pco.AddPath(bbox, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON)
offset = min((int)(area * (1 - rate) / (peri + 0.001) + 0.5), max_shr)
shrinked_bbox = pco.Execute(-offset)
if len(shrinked_bbox) == 0:
shrinked_bboxes.append(bbox)
continue
shrinked_bbox = np.array(shrinked_bbox[0])
if shrinked_bbox.shape[0] <= 2:
shrinked_bboxes.append(bbox)
continue
shrinked_bboxes.append(shrinked_bbox)
return np.array(shrinked_bboxes)
示例2: shrink
# 需要导入模块: import pyclipper [as 别名]
# 或者: from pyclipper import PyclipperOffset [as 别名]
def shrink(bboxes, rate, max_shr=20):
rate = rate * rate
shrinked_bboxes = []
for bbox in bboxes:
area = plg.Polygon(bbox).area()
peri = perimeter(bbox)
pco = pyclipper.PyclipperOffset()
pco.AddPath(bbox, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON)
offset = min((int)(area * (1 - rate) / (peri + 0.001) + 0.5), max_shr)
shrinked_bbox = pco.Execute(-offset)
if len(shrinked_bbox) == 0:
shrinked_bboxes.append(bbox)
continue
shrinked_bbox = np.array(shrinked_bbox)[0]
if shrinked_bbox.shape[0] <= 2:
shrinked_bboxes.append(bbox)
continue
shrinked_bboxes.append(shrinked_bbox)
return np.array(shrinked_bboxes)
示例3: generate_rbox
# 需要导入模块: import pyclipper [as 别名]
# 或者: from pyclipper import PyclipperOffset [as 别名]
def generate_rbox(im_size, text_polys, text_tags, training_mask, shrink_ratio):
"""
生成mask图,白色部分是文本,黑色是北京
:param im_size: 图像的h,w
:param text_polys: 框的坐标
:param text_tags: 标注文本框是否参与训练
:param training_mask: 忽略标注为 DO NOT CARE 的矩阵
:return: 生成的mask图
"""
h, w = im_size
G_s = np.zeros((h, w), dtype=np.float32)
G_d = np.zeros((h, w), dtype=np.float32)
for i, (poly, tag) in enumerate(zip(text_polys, text_tags)):
try:
poly = poly.astype(np.int)
# D = cv2.contourArea(poly) * (1 - shrink_ratio * shrink_ratio) / cv2.arcLength(poly, True)
D = cv2.contourArea(poly) * (1 - shrink_ratio) / cv2.arcLength(poly, True) + 0.5
pco = pyclipper.PyclipperOffset()
pco.AddPath(poly, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON)
shrinked_poly = np.array(pco.Execute(-D))
# dilated_poly = np.array(pco.Execute(D))
dilated_poly = np.array(pco.Execute(0))
cv2.fillPoly(G_s, shrinked_poly, 1)
cv2.fillPoly(G_d, dilated_poly, 1)
if not tag:
cv2.fillPoly(training_mask, shrinked_poly, 0)
except:
print(poly)
# return score_map, training_mask
return G_s, G_d, training_mask
示例4: unclip
# 需要导入模块: import pyclipper [as 别名]
# 或者: from pyclipper import PyclipperOffset [as 别名]
def unclip(self, box, unclip_ratio=1.5):
poly = Polygon(box)
distance = poly.area * unclip_ratio / poly.length
offset = pyclipper.PyclipperOffset()
offset.AddPath(box, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON)
expanded = np.array(offset.Execute(distance))
return expanded
示例5: shrink_polygon_pyclipper
# 需要导入模块: import pyclipper [as 别名]
# 或者: from pyclipper import PyclipperOffset [as 别名]
def shrink_polygon_pyclipper(polygon, shrink_ratio):
from shapely.geometry import Polygon
import pyclipper
polygon_shape = Polygon(polygon)
distance = polygon_shape.area * (1 - np.power(shrink_ratio, 2)) / polygon_shape.length
subject = [tuple(l) for l in polygon]
padding = pyclipper.PyclipperOffset()
padding.AddPath(subject, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON)
shrinked = padding.Execute(-distance)
if shrinked == []:
shrinked = np.array(shrinked)
else:
shrinked = np.array(shrinked[0]).reshape(-1, 2)
return shrinked
示例6: expandPathsToPolygons
# 需要导入模块: import pyclipper [as 别名]
# 或者: from pyclipper import PyclipperOffset [as 别名]
def expandPathsToPolygons(pathList, offset):
import pyclipper
# Use PyclipperOffset to generate polygons that surround the original
# paths with a constant offset all around
co = pyclipper.PyclipperOffset()
for path in pathList: co.AddPath(path, pyclipper.JT_ROUND, pyclipper.ET_OPENROUND)
return co.Execute(offset)
# A small pyclipper wrapper to trim parts of a polygon using another polygon
示例7: draw_border_map
# 需要导入模块: import pyclipper [as 别名]
# 或者: from pyclipper import PyclipperOffset [as 别名]
def draw_border_map(self, polygon, canvas, mask):
polygon = np.array(polygon)
assert polygon.ndim == 2
assert polygon.shape[1] == 2
polygon_shape = Polygon(polygon)
if polygon_shape.area <= 0:
return
distance = polygon_shape.area * (1 - np.power(self.shrink_ratio, 2)) / polygon_shape.length
subject = [tuple(l) for l in polygon]
padding = pyclipper.PyclipperOffset()
padding.AddPath(subject, pyclipper.JT_ROUND,
pyclipper.ET_CLOSEDPOLYGON)
padded_polygon = np.array(padding.Execute(distance)[0])
cv2.fillPoly(mask, [padded_polygon.astype(np.int32)], 1.0)
xmin = padded_polygon[:, 0].min()
xmax = padded_polygon[:, 0].max()
ymin = padded_polygon[:, 1].min()
ymax = padded_polygon[:, 1].max()
width = xmax - xmin + 1
height = ymax - ymin + 1
polygon[:, 0] = polygon[:, 0] - xmin
polygon[:, 1] = polygon[:, 1] - ymin
xs = np.broadcast_to(
np.linspace(0, width - 1, num=width).reshape(1, width), (height, width))
ys = np.broadcast_to(
np.linspace(0, height - 1, num=height).reshape(height, 1), (height, width))
distance_map = np.zeros(
(polygon.shape[0], height, width), dtype=np.float32)
for i in range(polygon.shape[0]):
j = (i + 1) % polygon.shape[0]
absolute_distance = self.distance(xs, ys, polygon[i], polygon[j])
distance_map[i] = np.clip(absolute_distance / distance, 0, 1)
distance_map = distance_map.min(axis=0)
xmin_valid = min(max(0, xmin), canvas.shape[1] - 1)
xmax_valid = min(max(0, xmax), canvas.shape[1] - 1)
ymin_valid = min(max(0, ymin), canvas.shape[0] - 1)
ymax_valid = min(max(0, ymax), canvas.shape[0] - 1)
canvas[ymin_valid:ymax_valid + 1, xmin_valid:xmax_valid + 1] = np.fmax(
1 - distance_map[
ymin_valid - ymin:ymax_valid - ymax + height,
xmin_valid - xmin:xmax_valid - xmax + width],
canvas[ymin_valid:ymax_valid + 1, xmin_valid:xmax_valid + 1])