zishuo/crnn_plate_recognition
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plate augment

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we0091234
2022-11-15 21:05:11 +08:00
parent cce10c303b
commit 20267d3154
49 changed files with 25465 additions and 2 deletions
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Text-Image-Augmentation-python-master/warp_mls.py Normal file
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# -*- coding:utf-8 -*-
# Author: RubanSeven
import math
import numpy as np
class WarpMLS:
def __init__(self, src, src_pts, dst_pts, dst_w, dst_h, trans_ratio=1.):
self.src = src
self.src_pts = src_pts
self.dst_pts = dst_pts
self.pt_count = len(self.dst_pts)
self.dst_w = dst_w
self.dst_h = dst_h
self.trans_ratio = trans_ratio
self.grid_size = 100
self.rdx = np.zeros((self.dst_h, self.dst_w))
self.rdy = np.zeros((self.dst_h, self.dst_w))
@staticmethod
def __bilinear_interp(x, y, v11, v12, v21, v22):
return (v11 * (1 - y) + v12 * y) * (1 - x) + (v21 * (1 - y) + v22 * y) * x
def generate(self):
self.calc_delta()
return self.gen_img()
def calc_delta(self):
w = np.zeros(self.pt_count, dtype=np.float32)
if self.pt_count < 2:
return
i = 0
while 1:
if self.dst_w <= i < self.dst_w + self.grid_size - 1:
i = self.dst_w - 1
elif i >= self.dst_w:
break
j = 0
while 1:
if self.dst_h <= j < self.dst_h + self.grid_size - 1:
j = self.dst_h - 1
elif j >= self.dst_h:
break
sw = 0
swp = np.zeros(2, dtype=np.float32)
swq = np.zeros(2, dtype=np.float32)
new_pt = np.zeros(2, dtype=np.float32)
cur_pt = np.array([i, j], dtype=np.float32)
k = 0
for k in range(self.pt_count):
if i == self.dst_pts[k][0] and j == self.dst_pts[k][1]:
break
w[k] = 1. / ((i - self.dst_pts[k][0]) * (i - self.dst_pts[k][0]) +
(j - self.dst_pts[k][1]) * (j - self.dst_pts[k][1]))
sw += w[k]
swp = swp + w[k] * np.array(self.dst_pts[k])
swq = swq + w[k] * np.array(self.src_pts[k])
if k == self.pt_count - 1:
pstar = 1 / sw * swp
qstar = 1 / sw * swq
miu_s = 0
for k in range(self.pt_count):
if i == self.dst_pts[k][0] and j == self.dst_pts[k][1]:
continue
pt_i = self.dst_pts[k] - pstar
miu_s += w[k] * np.sum(pt_i * pt_i)
cur_pt -= pstar
cur_pt_j = np.array([-cur_pt[1], cur_pt[0]])
for k in range(self.pt_count):
if i == self.dst_pts[k][0] and j == self.dst_pts[k][1]:
continue
pt_i = self.dst_pts[k] - pstar
pt_j = np.array([-pt_i[1], pt_i[0]])
tmp_pt = np.zeros(2, dtype=np.float32)
tmp_pt[0] = np.sum(pt_i * cur_pt) * self.src_pts[k][0] - \
np.sum(pt_j * cur_pt) * self.src_pts[k][1]
tmp_pt[1] = -np.sum(pt_i * cur_pt_j) * self.src_pts[k][0] + \
np.sum(pt_j * cur_pt_j) * self.src_pts[k][1]
tmp_pt *= (w[k] / miu_s)
new_pt += tmp_pt
new_pt += qstar
else:
new_pt = self.src_pts[k]
self.rdx[j, i] = new_pt[0] - i
self.rdy[j, i] = new_pt[1] - j
j += self.grid_size
i += self.grid_size
def gen_img(self):
src_h, src_w = self.src.shape[:2]
dst = np.zeros_like(self.src, dtype=np.float32)
for i in np.arange(0, self.dst_h, self.grid_size):
for j in np.arange(0, self.dst_w, self.grid_size):
ni = i + self.grid_size
nj = j + self.grid_size
w = h = self.grid_size
if ni >= self.dst_h:
ni = self.dst_h - 1
h = ni - i + 1
if nj >= self.dst_w:
nj = self.dst_w - 1
w = nj - j + 1
di = np.reshape(np.arange(h), (-1, 1))
dj = np.reshape(np.arange(w), (1, -1))
delta_x = self.__bilinear_interp(di / h, dj / w,
self.rdx[i, j], self.rdx[i, nj],
self.rdx[ni, j], self.rdx[ni, nj])
delta_y = self.__bilinear_interp(di / h, dj / w,
self.rdy[i, j], self.rdy[i, nj],
self.rdy[ni, j], self.rdy[ni, nj])
nx = j + dj + delta_x * self.trans_ratio
ny = i + di + delta_y * self.trans_ratio
nx = np.clip(nx, 0, src_w - 1)
ny = np.clip(ny, 0, src_h - 1)
nxi = np.array(np.floor(nx), dtype=np.int32)
nyi = np.array(np.floor(ny), dtype=np.int32)
nxi1 = np.array(np.ceil(nx), dtype=np.int32)
nyi1 = np.array(np.ceil(ny), dtype=np.int32)
if len(self.src.shape) == 3:
x = np.tile(np.expand_dims(ny - nyi, axis=-1), (1, 1, 3))
y = np.tile(np.expand_dims(nx - nxi, axis=-1), (1, 1, 3))
else:
x = ny - nyi
y = nx - nxi
dst[i:i + h, j:j + w] = self.__bilinear_interp(x,
y,
self.src[nyi, nxi],
self.src[nyi, nxi1],
self.src[nyi1, nxi],
self.src[nyi1, nxi1]
)
# for di in range(h):
# for dj in range(w):
# # print(ni, nj, i, j)
# delta_x = self.__bilinear_interp(di / h, dj / w, self.rdx[i, j], self.rdx[i, nj],
# self.rdx[ni, j], self.rdx[ni, nj])
# delta_y = self.__bilinear_interp(di / h, dj / w, self.rdy[i, j], self.rdy[i, nj],
# self.rdy[ni, j], self.rdy[ni, nj])
# nx = j + dj + delta_x * self.trans_ratio
# ny = i + di + delta_y * self.trans_ratio
# nx = min(src_w - 1, max(0, nx))
# ny = min(src_h - 1, max(0, ny))
# nxi = int(nx)
# nyi = int(ny)
# nxi1 = math.ceil(nx)
# nyi1 = math.ceil(ny)
#
# dst[i + di, j + dj] = self.__bilinear_interp(ny - nyi, nx - nxi,
# self.src[nyi, nxi],
# self.src[nyi, nxi1],
# self.src[nyi1, nxi],
# self.src[nyi1, nxi1]
# )
dst = np.clip(dst, 0, 255)
dst = np.array(dst, dtype=np.uint8)
return dst