提交 97a3af3b 编写于 作者: T tink2123

add distort and space

上级 5067126e
...@@ -14,6 +14,7 @@ Global: ...@@ -14,6 +14,7 @@ Global:
character_type: ch character_type: ch
character_dict_path: ./ppocr/utils/ppocr_keys_v1.txt character_dict_path: ./ppocr/utils/ppocr_keys_v1.txt
loss_type: ctc loss_type: ctc
distort: true
reader_yml: ./configs/rec/rec_chinese_reader.yml reader_yml: ./configs/rec/rec_chinese_reader.yml
pretrain_weights: pretrain_weights:
checkpoints: checkpoints:
......
...@@ -13,6 +13,7 @@ Global: ...@@ -13,6 +13,7 @@ Global:
max_text_length: 25 max_text_length: 25
character_type: en character_type: en
loss_type: ctc loss_type: ctc
distort: true
reader_yml: ./configs/rec/rec_icdar15_reader.yml reader_yml: ./configs/rec/rec_icdar15_reader.yml
pretrain_weights: ./pretrain_models/rec_mv3_none_bilstm_ctc/best_accuracy pretrain_weights: ./pretrain_models/rec_mv3_none_bilstm_ctc/best_accuracy
checkpoints: checkpoints:
......
...@@ -45,6 +45,8 @@ class LMDBReader(object): ...@@ -45,6 +45,8 @@ class LMDBReader(object):
self.use_tps = False self.use_tps = False
if "tps" in params: if "tps" in params:
self.ues_tps = True self.ues_tps = True
if "distort" in params:
self.use_distort = params['distort']
if params['mode'] == 'train': if params['mode'] == 'train':
self.batch_size = params['train_batch_size_per_card'] self.batch_size = params['train_batch_size_per_card']
self.drop_last = True self.drop_last = True
...@@ -142,7 +144,8 @@ class LMDBReader(object): ...@@ -142,7 +144,8 @@ class LMDBReader(object):
label=label, label=label,
char_ops=self.char_ops, char_ops=self.char_ops,
loss_type=self.loss_type, loss_type=self.loss_type,
max_text_length=self.max_text_length) max_text_length=self.max_text_length,
distort=self.use_distort)
if outs is None: if outs is None:
continue continue
yield outs yield outs
...@@ -185,6 +188,8 @@ class SimpleReader(object): ...@@ -185,6 +188,8 @@ class SimpleReader(object):
self.use_tps = False self.use_tps = False
if "tps" in params: if "tps" in params:
self.use_tps = True self.use_tps = True
if "distort" in params:
self.use_distort = params['distort']
if params['mode'] == 'train': if params['mode'] == 'train':
self.batch_size = params['train_batch_size_per_card'] self.batch_size = params['train_batch_size_per_card']
self.drop_last = True self.drop_last = True
...@@ -232,9 +237,14 @@ class SimpleReader(object): ...@@ -232,9 +237,14 @@ class SimpleReader(object):
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
label = substr[1] label = substr[1]
outs = process_image(img, self.image_shape, label, outs = process_image(
self.char_ops, self.loss_type, img=img,
self.max_text_length) image_shape=self.image_shape,
label=label,
char_ops=self.char_ops,
loss_type=self.loss_type,
max_text_length=self.max_text_length,
distort=self.use_distort)
if outs is None: if outs is None:
continue continue
yield outs yield outs
......
...@@ -15,6 +15,7 @@ ...@@ -15,6 +15,7 @@
import math import math
import cv2 import cv2
import numpy as np import numpy as np
import random
from ppocr.utils.utility import initial_logger from ppocr.utils.utility import initial_logger
logger = initial_logger() logger = initial_logger()
...@@ -89,6 +90,252 @@ def get_img_data(value): ...@@ -89,6 +90,252 @@ def get_img_data(value):
return imgori return imgori
def flag():
"""
flag
"""
return 1 if random.random() > 0.5000001 else -1
def cvtColor(img):
"""
cvtColor
"""
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
delta = 0.001 * random.random() * flag()
hsv[:, :, 2] = hsv[:, :, 2] * (1 + delta)
new_img = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
return new_img
def blur(img):
"""
blur
"""
h, w, _ = img.shape
if h > 10 and w > 10:
return cv2.GaussianBlur(img, (5, 5), 1)
else:
return img
def doudong(img):
"""
doudong
"""
w, h, _ = img.shape
if h > 10 and w > 10:
thres = min(w, h)
s = int(random.random() * thres * 0.01)
src_img = img.copy()
for i in range(s):
img[i:, i:, :] = src_img[:w - i, :h - i, :]
return img
else:
return img
def add_gasuss_noise(image, mean=0, var=0.1):
noise = np.random.normal(mean, var**0.5, image.shape)
out = image + 0.5 * noise
out = np.clip(out, 0, 255)
out = np.uint8(out)
return out
def get_crop(image):
"""
random crop
"""
h, w, _ = image.shape
top_min = 1
top_max = 8
top_crop = int(random.randint(top_min, top_max))
crop_img = image.copy()
ratio = random.randint(0, 1)
if ratio:
crop_img = crop_img[top_crop:h, :, :]
else:
crop_img = crop_img[0:h - top_crop, :, :]
return crop_img
class Config:
"""
Config
"""
def __init__(self, ):
self.anglex = random.random() * 30
self.angley = random.random() * 15
self.anglez = random.random() * 10
self.fov = 42
self.r = 0
self.shearx = random.random() * 0.3
self.sheary = random.random() * 0.05
self.borderMode = cv2.BORDER_REPLICATE
def make(self, w, h, ang):
"""
make
"""
self.anglex = random.random() * 5 * flag()
self.angley = random.random() * 5 * flag()
self.anglez = -1 * random.random() * int(ang) * flag()
self.fov = 42
self.r = 0
self.shearx = 0
self.sheary = 0
self.borderMode = cv2.BORDER_REPLICATE
self.w = w
self.h = h
self.perspective = True
self.crop = True
self.affine = False
self.reverse = True
self.noise = True
self.dou = False
self.blur = True
self.color = True
def rad(x):
"""
rad
"""
return x * np.pi / 180
def get_warpR(config):
"""
get_warpR
"""
anglex, angley, anglez, fov, w, h, r = \
config.anglex, config.angley, config.anglez, config.fov, config.w, config.h, config.r
if w > 69 and w < 112:
anglex = anglex * 1.5
z = np.sqrt(w**2 + h**2) / 2 / np.tan(rad(fov / 2))
# Homogeneous coordinate transformation matrix
rx = np.array([[1, 0, 0, 0],
[0, np.cos(rad(anglex)), -np.sin(rad(anglex)), 0], [
0,
-np.sin(rad(anglex)),
np.cos(rad(anglex)),
0,
], [0, 0, 0, 1]], np.float32)
ry = np.array([[np.cos(rad(angley)), 0, np.sin(rad(angley)), 0],
[0, 1, 0, 0], [
-np.sin(rad(angley)),
0,
np.cos(rad(angley)),
0,
], [0, 0, 0, 1]], np.float32)
rz = np.array([[np.cos(rad(anglez)), np.sin(rad(anglez)), 0, 0],
[-np.sin(rad(anglez)), np.cos(rad(anglez)), 0, 0],
[0, 0, 1, 0], [0, 0, 0, 1]], np.float32)
r = rx.dot(ry).dot(rz)
# generate 4 points
pcenter = np.array([h / 2, w / 2, 0, 0], np.float32)
p1 = np.array([0, 0, 0, 0], np.float32) - pcenter
p2 = np.array([w, 0, 0, 0], np.float32) - pcenter
p3 = np.array([0, h, 0, 0], np.float32) - pcenter
p4 = np.array([w, h, 0, 0], np.float32) - pcenter
dst1 = r.dot(p1)
dst2 = r.dot(p2)
dst3 = r.dot(p3)
dst4 = r.dot(p4)
list_dst = [dst1, dst2, dst3, dst4]
org = np.array([[0, 0], [w, 0], [0, h], [w, h]], np.float32)
dst = np.zeros((4, 2), np.float32)
# Project onto the image plane
for i in range(4):
dst[i, 0] = list_dst[i][0] * z / (z - list_dst[i][2]) + pcenter[0]
dst[i, 1] = list_dst[i][1] * z / (z - list_dst[i][2]) + pcenter[1]
warpR = cv2.getPerspectiveTransform(org, dst)
dst1, dst2, dst3, dst4 = dst
r1 = int(min(dst1[1], dst2[1]))
r2 = int(max(dst3[1], dst4[1]))
c1 = int(min(dst1[0], dst3[0]))
c2 = int(max(dst2[0], dst4[0]))
try:
ratio = min(1.0 * h / (r2 - r1), 1.0 * w / (c2 - c1))
dx = -c1
dy = -r1
T1 = np.float32([[1., 0, dx], [0, 1., dy], [0, 0, 1.0 / ratio]])
ret = T1.dot(warpR)
except:
ratio = 1.0
T1 = np.float32([[1., 0, 0], [0, 1., 0], [0, 0, 1.]])
ret = T1
return ret, (-r1, -c1), ratio, dst
def get_warpAffine(config):
"""
get_warpAffine
"""
anglez = config.anglez
rz = np.array([[np.cos(rad(anglez)), np.sin(rad(anglez)), 0],
[-np.sin(rad(anglez)), np.cos(rad(anglez)), 0]], np.float32)
return rz
def warp(img, ang):
"""
warp
"""
h, w, _ = img.shape
config = Config()
config.make(w, h, ang)
new_img = img
if config.perspective:
tp = random.randint(1, 100)
if tp >= 50:
warpR, (r1, c1), ratio, dst = get_warpR(config)
new_w = int(np.max(dst[:, 0])) - int(np.min(dst[:, 0]))
new_img = cv2.warpPerspective(
new_img,
warpR, (int(new_w * ratio), h),
borderMode=config.borderMode)
if config.crop:
img_height, img_width = img.shape[0:2]
tp = random.randint(1, 100)
if tp >= 50 and img_height >= 20 and img_width >= 20:
new_img = get_crop(new_img)
if config.affine:
warpT = get_warpAffine(config)
new_img = cv2.warpAffine(
new_img, warpT, (w, h), borderMode=config.borderMode)
if config.blur:
tp = random.randint(1, 100)
if tp >= 50:
new_img = blur(new_img)
if config.color:
tp = random.randint(1, 100)
if tp >= 50:
new_img = cvtColor(new_img)
if config.dou:
new_img = doudong(new_img)
if config.noise:
tp = random.randint(1, 100)
if tp >= 50:
new_img = add_gasuss_noise(new_img)
if config.reverse:
tp = random.randint(1, 100)
if tp >= 50:
new_img = 255 - new_img
return new_img
def process_image(img, def process_image(img,
image_shape, image_shape,
label=None, label=None,
...@@ -96,7 +343,10 @@ def process_image(img, ...@@ -96,7 +343,10 @@ def process_image(img,
loss_type=None, loss_type=None,
max_text_length=None, max_text_length=None,
tps=None, tps=None,
infer_mode=False): infer_mode=False,
distort=False):
if distort:
img = warp(img, 10)
if infer_mode and char_ops.character_type == "ch" and not tps: if infer_mode and char_ops.character_type == "ch" and not tps:
norm_img = resize_norm_img_chinese(img, image_shape) norm_img = resize_norm_img_chinese(img, image_shape)
else: else:
......
...@@ -6620,4 +6620,5 @@ j ...@@ -6620,4 +6620,5 @@ j
\ No newline at end of file
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