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east_utils.py
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import numpy as np
USE_POLYGON=False
if USE_POLYGON:
import Polygon
else:
from poly_iou import poly_iou
__all__ = [
'restore_rectangle',
'nms_locality',
]
def restore_rectangle_rbox(origin, geometry):
d = geometry[:, :4]
angle = geometry[:, 4]
# for angle > 0
origin_0 = origin[angle >= 0]
d_0 = d[angle >= 0]
angle_0 = angle[angle >= 0]
if origin_0.shape[0] > 0:
p = np.array([np.zeros(d_0.shape[0]), -d_0[:, 0] - d_0[:, 2],
d_0[:, 1] + d_0[:, 3], -d_0[:, 0] - d_0[:, 2],
d_0[:, 1] + d_0[:, 3], np.zeros(d_0.shape[0]),
np.zeros(d_0.shape[0]), np.zeros(d_0.shape[0]),
d_0[:, 3], -d_0[:, 2]])
p = p.transpose((1, 0)).reshape((-1, 5, 2)) # N*5*2
rotate_matrix_x = np.array([np.cos(angle_0), np.sin(angle_0)]).transpose((1, 0))
rotate_matrix_x = np.repeat(rotate_matrix_x, 5, axis=1).reshape(-1, 2, 5).transpose((0, 2, 1)) # N*5*2
rotate_matrix_y = np.array([-np.sin(angle_0), np.cos(angle_0)]).transpose((1, 0))
rotate_matrix_y = np.repeat(rotate_matrix_y, 5, axis=1).reshape(-1, 2, 5).transpose((0, 2, 1))
p_rotate_x = np.sum(rotate_matrix_x * p, axis=2)[:, :, np.newaxis] # N*5*1
p_rotate_y = np.sum(rotate_matrix_y * p, axis=2)[:, :, np.newaxis] # N*5*1
p_rotate = np.concatenate([p_rotate_x, p_rotate_y], axis=2) # N*5*2
p3_in_origin = origin_0 - p_rotate[:, 4, :]
new_p0 = p_rotate[:, 0, :] + p3_in_origin # N*2
new_p1 = p_rotate[:, 1, :] + p3_in_origin
new_p2 = p_rotate[:, 2, :] + p3_in_origin
new_p3 = p_rotate[:, 3, :] + p3_in_origin
new_p_0 = np.concatenate([new_p0[:, np.newaxis, :], new_p1[:, np.newaxis, :],
new_p2[:, np.newaxis, :], new_p3[:, np.newaxis, :]], axis=1) # N*4*2
else:
new_p_0 = np.zeros((0, 4, 2))
# for angle < 0
origin_1 = origin[angle < 0]
d_1 = d[angle < 0]
angle_1 = angle[angle < 0]
if origin_1.shape[0] > 0:
p = np.array([-d_1[:, 1] - d_1[:, 3], -d_1[:, 0] - d_1[:, 2],
np.zeros(d_1.shape[0]), -d_1[:, 0] - d_1[:, 2],
np.zeros(d_1.shape[0]), np.zeros(d_1.shape[0]),
-d_1[:, 1] - d_1[:, 3], np.zeros(d_1.shape[0]),
-d_1[:, 1], -d_1[:, 2]])
p = p.transpose((1, 0)).reshape((-1, 5, 2)) # N*5*2
rotate_matrix_x = np.array([np.cos(-angle_1), -np.sin(-angle_1)]).transpose((1, 0))
rotate_matrix_x = np.repeat(rotate_matrix_x, 5, axis=1).reshape(-1, 2, 5).transpose((0, 2, 1)) # N*5*2
rotate_matrix_y = np.array([np.sin(-angle_1), np.cos(-angle_1)]).transpose((1, 0))
rotate_matrix_y = np.repeat(rotate_matrix_y, 5, axis=1).reshape(-1, 2, 5).transpose((0, 2, 1))
p_rotate_x = np.sum(rotate_matrix_x * p, axis=2)[:, :, np.newaxis] # N*5*1
p_rotate_y = np.sum(rotate_matrix_y * p, axis=2)[:, :, np.newaxis] # N*5*1
p_rotate = np.concatenate([p_rotate_x, p_rotate_y], axis=2) # N*5*2
p3_in_origin = origin_1 - p_rotate[:, 4, :]
new_p0 = p_rotate[:, 0, :] + p3_in_origin # N*2
new_p1 = p_rotate[:, 1, :] + p3_in_origin
new_p2 = p_rotate[:, 2, :] + p3_in_origin
new_p3 = p_rotate[:, 3, :] + p3_in_origin
new_p_1 = np.concatenate([new_p0[:, np.newaxis, :], new_p1[:, np.newaxis, :],
new_p2[:, np.newaxis, :], new_p3[:, np.newaxis, :]], axis=1) # N*4*2
else:
new_p_1 = np.zeros((0, 4, 2))
return np.concatenate([new_p_0, new_p_1])
def restore_rectangle(origin, geometry):
return restore_rectangle_rbox(origin, geometry)
def intersection(g, p):
if USE_POLYGON:
g = Polygon.Polygon(g[:8].reshape((4, 2)))
p = Polygon.Polygon(p[:8].reshape((4, 2)))
inter = (g & p).area()
union = g.area() + p.area() - inter
if union == 0:
return 0
else:
return inter / union
else:
g = g[:8].reshape((4, 2))
p = p[:8].reshape((4, 2))
return poly_iou(g, p)
def weighted_merge(g, p):
g[:8] = (g[8] * g[:8] + p[8] * p[:8]) / (g[8] + p[8])
g[8] = (g[8] + p[8])
return g
def standard_nms(S, thres):
order = np.argsort(S[:, 8])[::-1]
keep = []
while order.size > 0:
i = order[0]
keep.append(i)
ovr = np.array([intersection(S[i], S[t]) for t in order[1:]])
inds = np.where(ovr <= thres)[0]
order = order[inds + 1]
return S[keep]
def nms_locality(polys, thres=0.3):
'''
locality aware nms of EAST
:param polys: a N*9 numpy array. first 8 coordinates, then prob
:return: boxes after nms
'''
S = []
p = None
for g in polys:
if p is not None and intersection(g, p) > thres:
p = weighted_merge(g, p)
else:
if p is not None:
S.append(p)
p = g
if p is not None:
S.append(p)
if len(S) == 0:
return np.array([])
return standard_nms(np.array(S), thres)