repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/losses/__init__.py | mmocr/models/textdet/losses/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .db_loss import DBLoss
from .drrg_loss import DRRGLoss
from .fce_loss import FCELoss
from .pan_loss import PANLoss
from .pse_loss import PSELoss
from .textsnake_loss import TextSnakeLoss
__all__ = [
'PANLoss', 'PSELoss', 'DBLoss', 'TextSnakeLoss', 'FCELoss', 'DR... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/losses/textsnake_loss.py | mmocr/models/textdet/losses/textsnake_loss.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn.functional as F
from mmdet.core import BitmapMasks
from torch import nn
from mmocr.models.builder import LOSSES
from mmocr.utils import check_argument
@LOSSES.register_module()
class TextSnakeLoss(nn.Module):
"""The class for implementi... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/modules/utils.py | mmocr/models/textdet/modules/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
def normalize_adjacent_matrix(A):
"""Normalize adjacent matrix for GCN. This code was partially adapted from
https://github.com/GXYM/DRRG licensed under the MIT license.
Args:
A (ndarray): The adjacent matrix.
returns:
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/modules/proposal_local_graph.py | mmocr/models/textdet/modules/proposal_local_graph.py | # Copyright (c) OpenMMLab. All rights reserved.
import cv2
import numpy as np
import torch
from lanms import merge_quadrangle_n9 as la_nms
from mmcv.ops import RoIAlignRotated
from mmocr.models.textdet.postprocess.utils import fill_hole
from .utils import (euclidean_distance_matrix, feature_embedding,
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/modules/__init__.py | mmocr/models/textdet/modules/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .gcn import GCN
from .local_graph import LocalGraphs
from .proposal_local_graph import ProposalLocalGraphs
__all__ = ['LocalGraphs', 'ProposalLocalGraphs', 'GCN']
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/modules/gcn.py | mmocr/models/textdet/modules/gcn.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import init
class MeanAggregator(nn.Module):
def forward(self, features, A):
x = torch.bmm(A, features)
return x
class GraphConv(nn.Module):
def __init__(self, i... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/modules/local_graph.py | mmocr/models/textdet/modules/local_graph.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmcv.ops import RoIAlignRotated
from .utils import (euclidean_distance_matrix, feature_embedding,
normalize_adjacent_matrix)
class LocalGraphs:
"""Generate local graphs for GCN to classify the neighbors of a ... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/dbnet.py | mmocr/models/textdet/detectors/dbnet.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmocr.models.builder import DETECTORS
from .single_stage_text_detector import SingleStageTextDetector
from .text_detector_mixin import TextDetectorMixin
@DETECTORS.register_module()
class DBNet(TextDetectorMixin, SingleStageTextDetector):
"""The class for imple... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/fcenet.py | mmocr/models/textdet/detectors/fcenet.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmocr.models.builder import DETECTORS
from .single_stage_text_detector import SingleStageTextDetector
from .text_detector_mixin import TextDetectorMixin
@DETECTORS.register_module()
class FCENet(TextDetectorMixin, SingleStageTextDetector):
"""The class for impl... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/single_stage_text_detector.py | mmocr/models/textdet/detectors/single_stage_text_detector.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmocr.models.builder import DETECTORS
from mmocr.models.common.detectors import SingleStageDetector
@DETECTORS.register_module()
class SingleStageTextDetector(SingleStageDetector):
"""The class for implementing single stage text detector."""
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/psenet.py | mmocr/models/textdet/detectors/psenet.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmocr.models.builder import DETECTORS
from .single_stage_text_detector import SingleStageTextDetector
from .text_detector_mixin import TextDetectorMixin
@DETECTORS.register_module()
class PSENet(TextDetectorMixin, SingleStageTextDetector):
"""The class for impl... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/textsnake.py | mmocr/models/textdet/detectors/textsnake.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmocr.models.builder import DETECTORS
from .single_stage_text_detector import SingleStageTextDetector
from .text_detector_mixin import TextDetectorMixin
@DETECTORS.register_module()
class TextSnake(TextDetectorMixin, SingleStageTextDetector):
"""The class for i... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/drrg.py | mmocr/models/textdet/detectors/drrg.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmocr.models.builder import DETECTORS
from .single_stage_text_detector import SingleStageTextDetector
from .text_detector_mixin import TextDetectorMixin
@DETECTORS.register_module()
class DRRG(TextDetectorMixin, SingleStageTextDetector):
"""The class for implem... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/ocr_mask_rcnn.py | mmocr/models/textdet/detectors/ocr_mask_rcnn.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmdet.models.detectors import MaskRCNN
from mmocr.core import seg2boundary
from mmocr.models.builder import DETECTORS
from .text_detector_mixin import TextDetectorMixin
@DETECTORS.register_module()
class OCRMaskRCNN(TextDetectorMixin, MaskRCNN):
"""Mask RCNN t... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/__init__.py | mmocr/models/textdet/detectors/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .dbnet import DBNet
from .drrg import DRRG
from .fcenet import FCENet
from .ocr_mask_rcnn import OCRMaskRCNN
from .panet import PANet
from .psenet import PSENet
from .single_stage_text_detector import SingleStageTextDetector
from .text_detector_mixin import TextDetec... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/panet.py | mmocr/models/textdet/detectors/panet.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmocr.models.builder import DETECTORS
from .single_stage_text_detector import SingleStageTextDetector
from .text_detector_mixin import TextDetectorMixin
@DETECTORS.register_module()
class PANet(TextDetectorMixin, SingleStageTextDetector):
"""The class for imple... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/detectors/text_detector_mixin.py | mmocr/models/textdet/detectors/text_detector_mixin.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import mmcv
from mmocr.core import imshow_pred_boundary
class TextDetectorMixin:
"""Base class for text detector, only to show results.
Args:
show_score (bool): Whether to show text instance score.
"""
def __init__(self, show_... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/necks/fpnf.py | mmocr/models/textdet/necks/fpnf.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule, ModuleList, auto_fp16
from mmocr.models.builder import NECKS
@NECKS.register_module()
class FPNF(BaseModule):
"""FPN-like fusion module in Shape Robust ... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/necks/fpem_ffm.py | mmocr/models/textdet/necks/fpem_ffm.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn.functional as F
from mmcv.runner import BaseModule, ModuleList
from torch import nn
from mmocr.models.builder import NECKS
class FPEM(BaseModule):
"""FPN-like feature fusion module in PANet.
Args:
in_channels (int): Number of input chan... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/necks/fpn_cat.py | mmocr/models/textdet/necks/fpn_cat.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import BaseModule, ModuleList, Sequential, auto_fp16
from mmocr.models.builder import NECKS
@NECKS.register_module()
class FPNC(BaseModule):
"""FPN-l... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/necks/__init__.py | mmocr/models/textdet/necks/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .fpem_ffm import FPEM_FFM
from .fpn_cat import FPNC
from .fpn_unet import FPN_UNet
from .fpnf import FPNF
__all__ = ['FPEM_FFM', 'FPNF', 'FPNC', 'FPN_UNet']
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/models/textdet/necks/fpn_unet.py | mmocr/models/textdet/necks/fpn_unet.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn.functional as F
from mmcv.runner import BaseModule
from torch import nn
from mmocr.models.builder import NECKS
class UpBlock(BaseModule):
"""Upsample block for DRRG and TextSnake."""
def __init__(self, in_channels, out_channels, in... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/img_util.py | mmocr/utils/img_util.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import mmcv
def drop_orientation(img_file):
"""Check if the image has orientation information. If yes, ignore it by
converting the image format to png, and return new filename, otherwise
return the original filename.
Args:
img_file(st... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/fileio.py | mmocr/utils/fileio.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import mmcv
def list_to_file(filename, lines):
"""Write a list of strings to a text file.
Args:
filename (str): The output filename. It will be created/overwritten.
lines (list(str)): Data to be written.
"""
mmcv.mkdir_or_exis... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/data_convert_util.py | mmocr/utils/data_convert_util.py | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
def convert_annotations(image_infos, out_json_name):
"""Convert the annotation into coco style.
Args:
image_infos(list): The list of image information dicts
out_json_name(str): The output json filename
Returns:
out_json(... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/model.py | mmocr/utils/model.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
class _BatchNormXd(torch.nn.modules.batchnorm._BatchNorm):
"""A general BatchNorm layer without input dimension check.
Reproduced from @kapily's work:
(https://github.com/pytorch/pytorch/issues/41081#issuecomment-783961547)
The only differe... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/logger.py | mmocr/utils/logger.py | # Copyright (c) OpenMMLab. All rights reserved.
import logging
from mmcv.utils import get_logger
def get_root_logger(log_file=None, log_level=logging.INFO):
"""Use `get_logger` method in mmcv to get the root logger.
The logger will be initialized if it has not been initialized. By default a
StreamHandle... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/setup_env.py | mmocr/utils/setup_env.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import platform
import warnings
import cv2
import torch.multiprocessing as mp
def setup_multi_processes(cfg):
"""Setup multi-processing environment variables."""
# set multi-process start method as `fork` to speed up the training
if platform.syste... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/ocr.py | mmocr/utils/ocr.py | #!/usr/bin/env python
# Copyright (c) OpenMMLab. All rights reserved.
import copy
import os
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
import mmcv
import numpy as np
import torch
from mmcv.image.misc import tensor2imgs
from mmcv.runner import load_checkpoint
from mmcv.utils... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | true |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/string_util.py | mmocr/utils/string_util.py | # Copyright (c) OpenMMLab. All rights reserved.
class StringStrip:
"""Removing the leading and/or the trailing characters based on the string
argument passed.
Args:
strip (bool): Whether remove characters from both left and right of
the string. Default: True.
strip_pos (str): Wh... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/collect_env.py | mmocr/utils/collect_env.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.utils import collect_env as collect_base_env
from mmcv.utils import get_git_hash
import mmocr
def collect_env():
"""Collect the information of the running environments."""
env_info = collect_base_env()
env_info['MMOCR'] = mmocr.__version__ + '+' +... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/lmdb_util.py | mmocr/utils/lmdb_util.py | # Copyright (c) OpenMMLab. All rights reserved.
import json
import os
import os.path as osp
import cv2
import lmdb
import numpy as np
from mmocr.utils import list_from_file
def check_image_is_valid(imageBin):
if imageBin is None:
return False
imageBuf = np.frombuffer(imageBin, dtype=np.uint8)
im... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/__init__.py | mmocr/utils/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.utils import Registry, build_from_cfg
from .box_util import (bezier_to_polygon, is_on_same_line, sort_points,
stitch_boxes_into_lines)
from .check_argument import (equal_len, is_2dlist, is_3dlist, is_none_or_type,
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/check_argument.py | mmocr/utils/check_argument.py | # Copyright (c) OpenMMLab. All rights reserved.
def is_3dlist(x):
"""check x is 3d-list([[[1], []]]) or 2d empty list([[], []]) or 1d empty
list([]).
Notice:
The reason that it contains 1d or 2d empty list is because
some arguments from gt annotation file or model prediction
may b... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/utils/box_util.py | mmocr/utils/box_util.py | # Copyright (c) OpenMMLab. All rights reserved.
import functools
import numpy as np
from mmocr.utils.check_argument import is_2dlist, is_type_list
def is_on_same_line(box_a, box_b, min_y_overlap_ratio=0.8):
"""Check if two boxes are on the same line by their y-axis coordinates.
Two boxes are on the same li... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/visualize.py | mmocr/core/visualize.py | # Copyright (c) OpenMMLab. All rights reserved.
import math
import os
import shutil
import urllib
import warnings
import cv2
import mmcv
import numpy as np
import torch
from matplotlib import pyplot as plt
from PIL import Image, ImageDraw, ImageFont
import mmocr.utils as utils
def overlay_mask_img(img, mask):
"... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/mask.py | mmocr/core/mask.py | # Copyright (c) OpenMMLab. All rights reserved.
import cv2
import numpy as np
import mmocr.utils as utils
def points2boundary(points, text_repr_type, text_score=None, min_width=-1):
"""Convert a text mask represented by point coordinates sequence into a
text boundary.
Args:
points (ndarray): Mas... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/__init__.py | mmocr/core/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from . import evaluation
from .evaluation import * # NOQA
from .mask import extract_boundary, points2boundary, seg2boundary
from .visualize import (det_recog_show_result, imshow_edge, imshow_node,
imshow_pred_boundary, imshow_text_char_boundary,
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/deployment/__init__.py | mmocr/core/deployment/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .deploy_utils import (ONNXRuntimeDetector, ONNXRuntimeRecognizer,
TensorRTDetector, TensorRTRecognizer)
__all__ = [
'ONNXRuntimeRecognizer', 'ONNXRuntimeDetector', 'TensorRTDetector',
'TensorRTRecognizer'
]
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/deployment/deploy_utils.py | mmocr/core/deployment/deploy_utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import warnings
from typing import Any, Iterable
import numpy as np
import torch
from mmdet.models.builder import DETECTORS
from mmocr.models.textdet.detectors.single_stage_text_detector import \
SingleStageTextDetector
from mmocr.models.textde... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/evaluation/hmean.py | mmocr/core/evaluation/hmean.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
from operator import itemgetter
import mmcv
import numpy as np
from mmcv.utils import print_log
import mmocr.utils as utils
from mmocr.core.evaluation import hmean_ic13, hmean_iou
from mmocr.core.evaluation.utils import (filter_2dlist_result,
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/evaluation/ner_metric.py | mmocr/core/evaluation/ner_metric.py | # Copyright (c) OpenMMLab. All rights reserved.
from collections import Counter
def gt_label2entity(gt_infos):
"""Get all entities from ground truth infos.
Args:
gt_infos (list[dict]): Ground-truth information contains text and
label.
Returns:
gt_entities (list[list]): Original... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/evaluation/hmean_iou.py | mmocr/core/evaluation/hmean_iou.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import mmocr.utils as utils
from . import utils as eval_utils
def eval_hmean_iou(pred_boxes,
gt_boxes,
gt_ignored_boxes,
iou_thr=0.5,
precision_thr=0.5):
"""Evaluate hmea... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/evaluation/ocr_metric.py | mmocr/core/evaluation/ocr_metric.py | # Copyright (c) OpenMMLab. All rights reserved.
import re
from difflib import SequenceMatcher
from rapidfuzz.distance import Levenshtein
from mmocr.utils import is_type_list
def cal_true_positive_char(pred, gt):
"""Calculate correct character number in prediction.
Args:
pred (str): Prediction text.... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/evaluation/utils.py | mmocr/core/evaluation/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
from shapely.geometry import Polygon as plg
import mmocr.utils as utils
def ignore_pred(pred_boxes, gt_ignored_index, gt_polys, precision_thr):
"""Ignore the predicted box if it hits any ignored ground truth.
Args:
pred_boxes (list[n... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/evaluation/__init__.py | mmocr/core/evaluation/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .hmean import eval_hmean
from .hmean_ic13 import eval_hmean_ic13
from .hmean_iou import eval_hmean_iou
from .kie_metric import compute_f1_score
from .ner_metric import eval_ner_f1
from .ocr_metric import eval_ocr_metric
__all__ = [
'eval_hmean_ic13', 'eval_hmean... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/evaluation/kie_metric.py | mmocr/core/evaluation/kie_metric.py | # Copyright (c) OpenMMLab. All rights reserved.
import torch
def compute_f1_score(preds, gts, ignores=[]):
"""Compute the F1-score of prediction.
Args:
preds (Tensor): The predicted probability NxC map
with N and C being the sample number and class
number respectively.
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/core/evaluation/hmean_ic13.py | mmocr/core/evaluation/hmean_ic13.py | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import mmocr.utils as utils
from . import utils as eval_utils
def compute_recall_precision(gt_polys, pred_polys):
"""Compute the recall and the precision matrices between gt and predicted
polygons.
Args:
gt_polys (list[Polygon]):... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/apis/train.py | mmocr/apis/train.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import mmcv
import numpy as np
import torch
import torch.distributed as dist
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import (DistSamplerSeedHook, EpochBasedRunner,
Fp16OptimizerHook, Op... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/apis/inference.py | mmocr/apis/inference.py | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import mmcv
import numpy as np
import torch
from mmcv.ops import RoIPool
from mmcv.parallel import collate, scatter
from mmcv.runner import load_checkpoint
from mmdet.core import get_classes
from mmdet.datasets import replace_ImageToTensor
from mmdet.data... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/apis/utils.py | mmocr/apis/utils.py | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import warnings
import mmcv
import numpy as np
import torch
from mmdet.datasets import replace_ImageToTensor
from mmocr.utils import is_2dlist, is_type_list
def update_pipeline(cfg, idx=None):
if idx is None:
if cfg.pipeline is not None:
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/apis/__init__.py | mmocr/apis/__init__.py | # Copyright (c) OpenMMLab. All rights reserved.
from .inference import init_detector, model_inference
from .test import single_gpu_test
from .train import init_random_seed, train_detector
from .utils import (disable_text_recog_aug_test, replace_image_to_tensor,
tensor2grayimgs)
__all__ = [
'mod... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/mmocr/apis/test.py | mmocr/apis/test.py | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import mmcv
import numpy as np
import torch
from mmcv.image import tensor2imgs
from mmcv.parallel import DataContainer
from mmdet.core import encode_mask_results
from .utils import tensor2grayimgs
def retrieve_img_tensor_and_meta(data):
"""Re... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/docs/zh_cn/conf.py | docs/zh_cn/conf.py | # Copyright (c) OpenMMLab. All rights reserved.
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup -----------------------... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/docs/zh_cn/stats.py | docs/zh_cn/stats.py | #!/usr/bin/env python
# Copyright (c) OpenMMLab. All rights reserved.
import functools as func
import glob
import re
from os.path import basename, splitext
import numpy as np
import titlecase
def title2anchor(name):
return re.sub(r'-+', '-', re.sub(r'[^a-zA-Z0-9]', '-',
name.... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/docs/en/conf.py | docs/en/conf.py | # Copyright (c) OpenMMLab. All rights reserved.
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup -----------------------... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/docs/en/stats.py | docs/en/stats.py | #!/usr/bin/env python
# Copyright (c) OpenMMLab. All rights reserved.
import functools as func
import glob
import re
from os.path import basename, splitext
import numpy as np
import titlecase
def title2anchor(name):
return re.sub(r'-+', '-', re.sub(r'[^a-zA-Z0-9]', '-',
name.... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/default_runtime.py | configs/_base_/default_runtime.py | # yapf:disable
log_config = dict(
interval=5,
hooks=[
dict(type='TextLoggerHook')
])
# yapf:enable
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = None
resume_from = None
workflow = [('train', 1)]
# disable opencv multithreading to avoid system being overloaded
opencv_num_threads ... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/det_datasets/icdar2015.py | configs/_base_/det_datasets/icdar2015.py | dataset_type = 'IcdarDataset'
data_root = 'data/icdar2015'
train = dict(
type=dataset_type,
ann_file=f'{data_root}/instances_training.json',
img_prefix=f'{data_root}/imgs',
pipeline=None)
test = dict(
type=dataset_type,
ann_file=f'{data_root}/instances_test.json',
img_prefix=f'{data_root}/... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/det_datasets/icdar2017.py | configs/_base_/det_datasets/icdar2017.py | dataset_type = 'IcdarDataset'
data_root = 'data/icdar2017'
train = dict(
type=dataset_type,
ann_file=f'{data_root}/instances_training.json',
img_prefix=f'{data_root}/imgs',
pipeline=None)
test = dict(
type=dataset_type,
ann_file=f'{data_root}/instances_val.json',
img_prefix=f'{data_root}/i... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/det_datasets/ctw1500.py | configs/_base_/det_datasets/ctw1500.py | dataset_type = 'IcdarDataset'
data_root = 'data/ctw1500'
train = dict(
type=dataset_type,
ann_file=f'{data_root}/instances_training.json',
img_prefix=f'{data_root}/imgs',
pipeline=None)
test = dict(
type=dataset_type,
ann_file=f'{data_root}/instances_test.json',
img_prefix=f'{data_root}/im... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/det_datasets/toy_data.py | configs/_base_/det_datasets/toy_data.py | root = 'tests/data/toy_dataset'
# dataset with type='TextDetDataset'
train1 = dict(
type='TextDetDataset',
img_prefix=f'{root}/imgs',
ann_file=f'{root}/instances_test.txt',
loader=dict(
type='AnnFileLoader',
repeat=4,
file_format='txt',
parser=dict(
type='Lin... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/det_datasets/synthtext.py | configs/_base_/det_datasets/synthtext.py | dataset_type = 'TextDetDataset'
data_root = 'data/synthtext'
train = dict(
type=dataset_type,
ann_file=f'{data_root}/instances_training.lmdb',
loader=dict(
type='AnnFileLoader',
repeat=1,
file_format='lmdb',
parser=dict(
type='LineJsonParser',
keys=['... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_sgd_600e.py | configs/_base_/schedules/schedule_sgd_600e.py | # optimizer
optimizer = dict(type='SGD', lr=1e-3, momentum=0.99, weight_decay=5e-4)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy='step', step=[200, 400])
# running settings
runner = dict(type='EpochBasedRunner', max_epochs=600)
checkpoint_config = dict(interval=100)
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_sgd_100k_iters.py | configs/_base_/schedules/schedule_sgd_100k_iters.py | # optimizer
optimizer = dict(type='SGD', lr=0.007, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy='poly', power=0.9, min_lr=1e-7, by_epoch=False)
# running settings
runner = dict(type='IterBasedRunner', max_iters=100000)
checkpoint_config = dict(inte... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_adam_step_20e.py | configs/_base_/schedules/schedule_adam_step_20e.py | # optimizer
optimizer = dict(type='Adam', lr=1e-4)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(
policy='step',
step=[16, 18],
warmup='linear',
warmup_iters=1,
warmup_ratio=0.001,
warmup_by_epoch=True)
# running settings
runner = dict(type='EpochBasedRunner', max_ep... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_adam_600e.py | configs/_base_/schedules/schedule_adam_600e.py | # optimizer
optimizer = dict(type='Adam', lr=1e-3)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy='poly', power=0.9)
# running settings
runner = dict(type='EpochBasedRunner', max_epochs=600)
checkpoint_config = dict(interval=100)
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_adam_step_6e.py | configs/_base_/schedules/schedule_adam_step_6e.py | # optimizer
optimizer = dict(type='Adam', lr=1e-3)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy='step', step=[3, 4])
# running settings
runner = dict(type='EpochBasedRunner', max_epochs=6)
checkpoint_config = dict(interval=1)
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_sgd_160e.py | configs/_base_/schedules/schedule_sgd_160e.py | # optimizer
optimizer = dict(type='SGD', lr=0.08, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=500,
warmup_ratio=0.001,
step=[80, 128])
# running settings
runner = dict(type='EpochBasedRunn... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_sgd_1500e.py | configs/_base_/schedules/schedule_sgd_1500e.py | # optimizer
optimizer = dict(type='SGD', lr=1e-3, momentum=0.90, weight_decay=5e-4)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy='poly', power=0.9, min_lr=1e-7, by_epoch=True)
# running settings
runner = dict(type='EpochBasedRunner', max_epochs=1500)
checkpoint_config = dict(interva... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_adam_step_600e.py | configs/_base_/schedules/schedule_adam_step_600e.py | # optimizer
optimizer = dict(type='Adam', lr=1e-4)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy='step', step=[200, 400])
# running settings
runner = dict(type='EpochBasedRunner', max_epochs=600)
checkpoint_config = dict(interval=100)
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_adam_step_12e.py | configs/_base_/schedules/schedule_adam_step_12e.py | # optimizer
optimizer = dict(type='Adam', lr=4e-4)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(
policy='step',
warmup='linear',
warmup_iters=100,
warmup_ratio=1.0 / 3,
step=[11])
runner = dict(type='EpochBasedRunner', max_epochs=12)
checkpoint_config = dict(interval=1)... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_sgd_1200e.py | configs/_base_/schedules/schedule_sgd_1200e.py | # optimizer
optimizer = dict(type='SGD', lr=0.007, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy='poly', power=0.9, min_lr=1e-7, by_epoch=True)
# running settings
runner = dict(type='EpochBasedRunner', max_epochs=1200)
checkpoint_config = dict(inter... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_adadelta_5e.py | configs/_base_/schedules/schedule_adadelta_5e.py | # optimizer
optimizer = dict(type='Adadelta', lr=1.0)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy='step', step=[])
# running settings
runner = dict(type='EpochBasedRunner', max_epochs=5)
checkpoint_config = dict(interval=1)
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_adadelta_18e.py | configs/_base_/schedules/schedule_adadelta_18e.py | # optimizer
optimizer = dict(type='Adadelta', lr=0.5)
optimizer_config = dict(grad_clip=dict(max_norm=0.5))
# learning policy
lr_config = dict(policy='step', step=[8, 14, 16])
# running settings
runner = dict(type='EpochBasedRunner', max_epochs=18)
checkpoint_config = dict(interval=1)
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/schedules/schedule_adam_step_5e.py | configs/_base_/schedules/schedule_adam_step_5e.py | # optimizer
optimizer = dict(type='Adam', lr=1e-3)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config = dict(policy='step', step=[3, 4])
# running settings
runner = dict(type='EpochBasedRunner', max_epochs=5)
checkpoint_config = dict(interval=1)
| python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_models/abinet.py | configs/_base_/recog_models/abinet.py | # num_chars depends on the configuration of label_convertor. The actual
# dictionary size is 36 + 1 (<BOS/EOS>).
# TODO: Automatically update num_chars based on the configuration of
# label_convertor
num_chars = 37
max_seq_len = 26
label_convertor = dict(
type='ABIConvertor',
dict_type='DICT36',
with_unkno... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_models/master.py | configs/_base_/recog_models/master.py | label_convertor = dict(
type='AttnConvertor', dict_type='DICT90', with_unknown=True)
model = dict(
type='MASTER',
backbone=dict(
type='ResNet',
in_channels=3,
stem_channels=[64, 128],
block_cfgs=dict(
type='BasicBlock',
plugins=dict(
c... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_models/robust_scanner.py | configs/_base_/recog_models/robust_scanner.py | label_convertor = dict(
type='AttnConvertor', dict_type='DICT90', with_unknown=True)
hybrid_decoder = dict(type='SequenceAttentionDecoder')
position_decoder = dict(type='PositionAttentionDecoder')
model = dict(
type='RobustScanner',
backbone=dict(type='ResNet31OCR'),
encoder=dict(
type='Chann... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_models/crnn_tps.py | configs/_base_/recog_models/crnn_tps.py | # model
label_convertor = dict(
type='CTCConvertor', dict_type='DICT36', with_unknown=False, lower=True)
model = dict(
type='CRNNNet',
preprocessor=dict(
type='TPSPreprocessor',
num_fiducial=20,
img_size=(32, 100),
rectified_img_size=(32, 100),
num_img_channel=1),
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_models/nrtr_modality_transform.py | configs/_base_/recog_models/nrtr_modality_transform.py | label_convertor = dict(
type='AttnConvertor', dict_type='DICT36', with_unknown=True, lower=True)
model = dict(
type='NRTR',
backbone=dict(type='NRTRModalityTransform'),
encoder=dict(type='NRTREncoder', n_layers=12),
decoder=dict(type='NRTRDecoder'),
loss=dict(type='TFLoss'),
label_convertor... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_models/crnn.py | configs/_base_/recog_models/crnn.py | label_convertor = dict(
type='CTCConvertor', dict_type='DICT36', with_unknown=False, lower=True)
model = dict(
type='CRNNNet',
preprocessor=None,
backbone=dict(type='VeryDeepVgg', leaky_relu=False, input_channels=1),
encoder=None,
decoder=dict(type='CRNNDecoder', in_channels=512, rnn_flag=True)... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_models/seg.py | configs/_base_/recog_models/seg.py | label_convertor = dict(
type='SegConvertor', dict_type='DICT36', with_unknown=True, lower=True)
model = dict(
type='SegRecognizer',
backbone=dict(
type='ResNet31OCR',
layers=[1, 2, 5, 3],
channels=[32, 64, 128, 256, 512, 512],
out_indices=[0, 1, 2, 3],
stage4_pool_cf... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_models/sar.py | configs/_base_/recog_models/sar.py | label_convertor = dict(
type='AttnConvertor', dict_type='DICT90', with_unknown=True)
model = dict(
type='SARNet',
backbone=dict(type='ResNet31OCR'),
encoder=dict(
type='SAREncoder',
enc_bi_rnn=False,
enc_do_rnn=0.1,
enc_gru=False,
),
decoder=dict(
type='P... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_models/satrn.py | configs/_base_/recog_models/satrn.py | label_convertor = dict(
type='AttnConvertor', dict_type='DICT36', with_unknown=True, lower=True)
model = dict(
type='SATRN',
backbone=dict(type='ShallowCNN'),
encoder=dict(type='SatrnEncoder'),
decoder=dict(type='TFDecoder'),
loss=dict(type='TFLoss'),
label_convertor=label_convertor,
ma... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_datasets/MJ_train.py | configs/_base_/recog_datasets/MJ_train.py | # Text Recognition Training set, including:
# Synthetic Datasets: Syn90k
train_root = 'data/mixture/Syn90k'
train_img_prefix = f'{train_root}/mnt/ramdisk/max/90kDICT32px'
train_ann_file = f'{train_root}/label.lmdb'
train = dict(
type='OCRDataset',
img_prefix=train_img_prefix,
ann_file=train_ann_file,
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_datasets/seg_toy_data.py | configs/_base_/recog_datasets/seg_toy_data.py | prefix = 'tests/data/ocr_char_ann_toy_dataset/'
train = dict(
type='OCRSegDataset',
img_prefix=f'{prefix}/imgs',
ann_file=f'{prefix}/instances_train.txt',
loader=dict(
type='AnnFileLoader',
repeat=100,
file_format='txt',
parser=dict(
type='LineJsonParser', ke... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_datasets/ST_SA_MJ_real_train.py | configs/_base_/recog_datasets/ST_SA_MJ_real_train.py | # Text Recognition Training set, including:
# Synthetic Datasets: SynthText, SynthAdd, Syn90k
# Real Dataset: IC11, IC13, IC15, COCO-Test, IIIT5k
train_prefix = 'data/mixture'
train_img_prefix1 = f'{train_prefix}/icdar_2011'
train_img_prefix2 = f'{train_prefix}/icdar_2013'
train_img_prefix3 = f'{train_prefix}/icdar_2... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_datasets/toy_data.py | configs/_base_/recog_datasets/toy_data.py | dataset_type = 'OCRDataset'
root = 'tests/data/ocr_toy_dataset'
img_prefix = f'{root}/imgs'
train_anno_file1 = f'{root}/label.txt'
train1 = dict(
type=dataset_type,
img_prefix=img_prefix,
ann_file=train_anno_file1,
loader=dict(
type='AnnFileLoader',
repeat=100,
file_format='txt... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_datasets/ST_charbox_train.py | configs/_base_/recog_datasets/ST_charbox_train.py | # Text Recognition Training set, including:
# Synthetic Datasets: SynthText (with character level boxes)
train_img_root = 'data/mixture'
train_img_prefix = f'{train_img_root}/SynthText'
train_ann_file = f'{train_img_root}/SynthText/instances_train.txt'
train = dict(
type='OCRSegDataset',
img_prefix=train_im... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_datasets/ST_MJ_alphanumeric_train.py | configs/_base_/recog_datasets/ST_MJ_alphanumeric_train.py | # Text Recognition Training set, including:
# Synthetic Datasets: SynthText, Syn90k
# Both annotations are filtered so that
# only alphanumeric terms are left
train_root = 'data/mixture'
train_img_prefix1 = f'{train_root}/Syn90k/mnt/ramdisk/max/90kDICT32px'
train_ann_file1 = f'{train_root}/Syn90k/label.lmdb'
train1 ... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_datasets/ST_SA_MJ_train.py | configs/_base_/recog_datasets/ST_SA_MJ_train.py | # Text Recognition Training set, including:
# Synthetic Datasets: SynthText, Syn90k
train_root = 'data/mixture'
train_img_prefix1 = f'{train_root}/Syn90k/mnt/ramdisk/max/90kDICT32px'
train_ann_file1 = f'{train_root}/Syn90k/label.lmdb'
train1 = dict(
type='OCRDataset',
img_prefix=train_img_prefix1,
ann_fi... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_datasets/academic_test.py | configs/_base_/recog_datasets/academic_test.py | # Text Recognition Testing set, including:
# Regular Datasets: IIIT5K, SVT, IC13
# Irregular Datasets: IC15, SVTP, CT80
test_root = 'data/mixture'
test_img_prefix1 = f'{test_root}/IIIT5K/'
test_img_prefix2 = f'{test_root}/svt/'
test_img_prefix3 = f'{test_root}/icdar_2013/'
test_img_prefix4 = f'{test_root}/icdar_2015/... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_datasets/ST_MJ_train.py | configs/_base_/recog_datasets/ST_MJ_train.py | # Text Recognition Training set, including:
# Synthetic Datasets: SynthText, Syn90k
train_root = 'data/mixture'
train_img_prefix1 = f'{train_root}/Syn90k/mnt/ramdisk/max/90kDICT32px'
train_ann_file1 = f'{train_root}/Syn90k/label.lmdb'
train1 = dict(
type='OCRDataset',
img_prefix=train_img_prefix1,
ann_fi... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_pipelines/nrtr_pipeline.py | configs/_base_/recog_pipelines/nrtr_pipeline.py | img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='ResizeOCR',
height=32,
min_width=32,
max_width=160,
keep_aspect_ratio=True,
width_downsample_ratio=0.25),
dict(type='ToTen... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_pipelines/crnn_tps_pipeline.py | configs/_base_/recog_pipelines/crnn_tps_pipeline.py | img_norm_cfg = dict(mean=[0.5], std=[0.5])
train_pipeline = [
dict(type='LoadImageFromFile', color_type='grayscale'),
dict(
type='ResizeOCR',
height=32,
min_width=100,
max_width=100,
keep_aspect_ratio=False),
dict(type='ToTensorOCR'),
dict(type='NormalizeOCR', **... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_pipelines/abinet_pipeline.py | configs/_base_/recog_pipelines/abinet_pipeline.py | img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='ResizeOCR',
height=32,
min_width=128,
max_width=128,
keep_aspect_ratio=False,
width_downsample_ratio=0.25),
dict(
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_pipelines/sar_pipeline.py | configs/_base_/recog_pipelines/sar_pipeline.py | img_norm_cfg = dict(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='ResizeOCR',
height=48,
min_width=48,
max_width=160,
keep_aspect_ratio=True,
width_downsample_ratio=0.25),
dict(type='ToTensorOCR'),
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_pipelines/master_pipeline.py | configs/_base_/recog_pipelines/master_pipeline.py | img_norm_cfg = dict(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='ResizeOCR',
height=48,
min_width=48,
max_width=160,
keep_aspect_ratio=True),
dict(type='ToTensorOCR'),
dict(type='NormalizeOCR', **img_nor... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
xdxie/WordArt | https://github.com/xdxie/WordArt/blob/89bf8a218881b250d0ead7a0287526c69586c92a/configs/_base_/recog_pipelines/cornertransformer_pipeline.py | configs/_base_/recog_pipelines/cornertransformer_pipeline.py | img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='ResizeOCR',
height=32,
min_width=128,
max_width=128,
keep_aspect_ratio=False,
width_downsample_ratio=0.25),
dict(
... | python | Apache-2.0 | 89bf8a218881b250d0ead7a0287526c69586c92a | 2026-01-05T07:11:30.009719Z | false |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.