fix conflict

This commit is contained in:
LDOUBLEV
2021-02-01 03:19:56 +00:00
34 changed files with 1675 additions and 101 deletions
+2 -2
View File
@@ -33,7 +33,7 @@ import paddle.distributed as dist
from ppocr.data.imaug import transform, create_operators
from ppocr.data.simple_dataset import SimpleDataSet
from ppocr.data.lmdb_dataset import LMDBDateSet
from ppocr.data.lmdb_dataset import LMDBDataSet
__all__ = ['build_dataloader', 'transform', 'create_operators']
@@ -54,7 +54,7 @@ signal.signal(signal.SIGTERM, term_mp)
def build_dataloader(config, mode, device, logger, seed=None):
config = copy.deepcopy(config)
support_dict = ['SimpleDataSet', 'LMDBDateSet']
support_dict = ['SimpleDataSet', 'LMDBDataSet']
module_name = config[mode]['dataset']['name']
assert module_name in support_dict, Exception(
'DataSet only support {}'.format(support_dict))
+1 -1
View File
@@ -21,7 +21,7 @@ from .make_border_map import MakeBorderMap
from .make_shrink_map import MakeShrinkMap
from .random_crop_data import EastRandomCropData, PSERandomCrop
from .rec_img_aug import RecAug, RecResizeImg, ClsResizeImg
from .rec_img_aug import RecAug, RecResizeImg, ClsResizeImg, SRNRecResizeImg
from .randaugment import RandAugment
from .operators import *
from .label_ops import *
+48
View File
@@ -102,6 +102,8 @@ class BaseRecLabelEncode(object):
support_character_type, character_type)
self.max_text_len = max_text_length
self.beg_str = "sos"
self.end_str = "eos"
if character_type == "en":
self.character_str = "0123456789abcdefghijklmnopqrstuvwxyz"
dict_character = list(self.character_str)
@@ -231,3 +233,49 @@ class AttnLabelEncode(BaseRecLabelEncode):
assert False, "Unsupport type %s in get_beg_end_flag_idx" \
% beg_or_end
return idx
class SRNLabelEncode(BaseRecLabelEncode):
""" Convert between text-label and text-index """
def __init__(self,
max_text_length=25,
character_dict_path=None,
character_type='en',
use_space_char=False,
**kwargs):
super(SRNLabelEncode,
self).__init__(max_text_length, character_dict_path,
character_type, use_space_char)
def add_special_char(self, dict_character):
dict_character = dict_character + [self.beg_str, self.end_str]
return dict_character
def __call__(self, data):
text = data['label']
text = self.encode(text)
char_num = len(self.character_str)
if text is None:
return None
if len(text) > self.max_text_len:
return None
data['length'] = np.array(len(text))
text = text + [char_num] * (self.max_text_len - len(text))
data['label'] = np.array(text)
return data
def get_ignored_tokens(self):
beg_idx = self.get_beg_end_flag_idx("beg")
end_idx = self.get_beg_end_flag_idx("end")
return [beg_idx, end_idx]
def get_beg_end_flag_idx(self, beg_or_end):
if beg_or_end == "beg":
idx = np.array(self.dict[self.beg_str])
elif beg_or_end == "end":
idx = np.array(self.dict[self.end_str])
else:
assert False, "Unsupport type %s in get_beg_end_flag_idx" \
% beg_or_end
return idx
+75 -15
View File
@@ -12,20 +12,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import math
import cv2
import numpy as np
@@ -77,6 +63,26 @@ class RecResizeImg(object):
return data
class SRNRecResizeImg(object):
def __init__(self, image_shape, num_heads, max_text_length, **kwargs):
self.image_shape = image_shape
self.num_heads = num_heads
self.max_text_length = max_text_length
def __call__(self, data):
img = data['image']
norm_img = resize_norm_img_srn(img, self.image_shape)
data['image'] = norm_img
[encoder_word_pos, gsrm_word_pos, gsrm_slf_attn_bias1, gsrm_slf_attn_bias2] = \
srn_other_inputs(self.image_shape, self.num_heads, self.max_text_length)
data['encoder_word_pos'] = encoder_word_pos
data['gsrm_word_pos'] = gsrm_word_pos
data['gsrm_slf_attn_bias1'] = gsrm_slf_attn_bias1
data['gsrm_slf_attn_bias2'] = gsrm_slf_attn_bias2
return data
def resize_norm_img(img, image_shape):
imgC, imgH, imgW = image_shape
h = img.shape[0]
@@ -103,7 +109,7 @@ def resize_norm_img(img, image_shape):
def resize_norm_img_chinese(img, image_shape):
imgC, imgH, imgW = image_shape
# todo: change to 0 and modified image shape
max_wh_ratio = 0
max_wh_ratio = imgW * 1.0 / imgH
h, w = img.shape[0], img.shape[1]
ratio = w * 1.0 / h
max_wh_ratio = max(max_wh_ratio, ratio)
@@ -126,6 +132,60 @@ def resize_norm_img_chinese(img, image_shape):
return padding_im
def resize_norm_img_srn(img, image_shape):
imgC, imgH, imgW = image_shape
img_black = np.zeros((imgH, imgW))
im_hei = img.shape[0]
im_wid = img.shape[1]
if im_wid <= im_hei * 1:
img_new = cv2.resize(img, (imgH * 1, imgH))
elif im_wid <= im_hei * 2:
img_new = cv2.resize(img, (imgH * 2, imgH))
elif im_wid <= im_hei * 3:
img_new = cv2.resize(img, (imgH * 3, imgH))
else:
img_new = cv2.resize(img, (imgW, imgH))
img_np = np.asarray(img_new)
img_np = cv2.cvtColor(img_np, cv2.COLOR_BGR2GRAY)
img_black[:, 0:img_np.shape[1]] = img_np
img_black = img_black[:, :, np.newaxis]
row, col, c = img_black.shape
c = 1
return np.reshape(img_black, (c, row, col)).astype(np.float32)
def srn_other_inputs(image_shape, num_heads, max_text_length):
imgC, imgH, imgW = image_shape
feature_dim = int((imgH / 8) * (imgW / 8))
encoder_word_pos = np.array(range(0, feature_dim)).reshape(
(feature_dim, 1)).astype('int64')
gsrm_word_pos = np.array(range(0, max_text_length)).reshape(
(max_text_length, 1)).astype('int64')
gsrm_attn_bias_data = np.ones((1, max_text_length, max_text_length))
gsrm_slf_attn_bias1 = np.triu(gsrm_attn_bias_data, 1).reshape(
[1, max_text_length, max_text_length])
gsrm_slf_attn_bias1 = np.tile(gsrm_slf_attn_bias1,
[num_heads, 1, 1]) * [-1e9]
gsrm_slf_attn_bias2 = np.tril(gsrm_attn_bias_data, -1).reshape(
[1, max_text_length, max_text_length])
gsrm_slf_attn_bias2 = np.tile(gsrm_slf_attn_bias2,
[num_heads, 1, 1]) * [-1e9]
return [
encoder_word_pos, gsrm_word_pos, gsrm_slf_attn_bias1,
gsrm_slf_attn_bias2
]
def flag():
"""
flag
+2 -2
View File
@@ -20,9 +20,9 @@ import cv2
from .imaug import transform, create_operators
class LMDBDateSet(Dataset):
class LMDBDataSet(Dataset):
def __init__(self, config, mode, logger, seed=None):
super(LMDBDateSet, self).__init__()
super(LMDBDataSet, self).__init__()
global_config = config['Global']
dataset_config = config[mode]['dataset']