mirror of
https://github.com/PaddlePaddle/PaddleOCR.git
synced 2025-10-31 09:49:30 +00:00
319 lines
14 KiB
Python
319 lines
14 KiB
Python
# Copyright (c) <2015-Present> Tzutalin
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# Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba,
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# William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and
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# associated documentation files (the "Software"), to deal in the Software without restriction, including without
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# limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the
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# Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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# The above copyright notice and this permission notice shall be included in all copies or substantial portions of
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# the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT
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# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
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# SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
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# CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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# THE SOFTWARE.
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import hashlib
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import os
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import re
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import sys
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from math import sqrt
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import cv2
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import numpy as np
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from PyQt5.QtCore import QRegExp, QT_VERSION_STR
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from PyQt5.QtGui import QIcon, QRegExpValidator, QColor
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from PyQt5.QtWidgets import QPushButton, QAction, QMenu
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from libs.ustr import ustr
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__dir__ = os.path.dirname(os.path.abspath(__file__)) # 获取本程序文件路径
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__iconpath__ = os.path.abspath(os.path.join(__dir__, '../resources/icons'))
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def newIcon(icon, iconSize=None):
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if iconSize is not None:
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return QIcon(QIcon(__iconpath__ + "/" + icon + ".png").pixmap(iconSize, iconSize))
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else:
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return QIcon(__iconpath__ + "/" + icon + ".png")
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def newButton(text, icon=None, slot=None):
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b = QPushButton(text)
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if icon is not None:
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b.setIcon(newIcon(icon))
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if slot is not None:
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b.clicked.connect(slot)
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return b
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def newAction(parent, text, slot=None, shortcut=None, icon=None,
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tip=None, checkable=False, enabled=True, iconSize=None):
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"""Create a new action and assign callbacks, shortcuts, etc."""
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a = QAction(text, parent)
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if icon is not None:
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if iconSize is not None:
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a.setIcon(newIcon(icon, iconSize))
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else:
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a.setIcon(newIcon(icon))
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if shortcut is not None:
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if isinstance(shortcut, (list, tuple)):
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a.setShortcuts(shortcut)
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else:
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a.setShortcut(shortcut)
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if tip is not None:
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a.setToolTip(tip)
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a.setStatusTip(tip)
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if slot is not None:
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a.triggered.connect(slot)
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if checkable:
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a.setCheckable(True)
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a.setEnabled(enabled)
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return a
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def addActions(widget, actions):
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for action in actions:
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if action is None:
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widget.addSeparator()
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elif isinstance(action, QMenu):
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widget.addMenu(action)
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else:
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widget.addAction(action)
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def labelValidator():
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return QRegExpValidator(QRegExp(r'^[^ \t].+'), None)
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class struct(object):
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def __init__(self, **kwargs):
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self.__dict__.update(kwargs)
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def distance(p):
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return sqrt(p.x() * p.x() + p.y() * p.y())
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def fmtShortcut(text):
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mod, key = text.split('+', 1)
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return '<b>%s</b>+<b>%s</b>' % (mod, key)
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def generateColorByText(text):
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s = ustr(text)
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hashCode = int(hashlib.sha256(s.encode('utf-8')).hexdigest(), 16)
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r = int((hashCode / 255) % 255)
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g = int((hashCode / 65025) % 255)
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b = int((hashCode / 16581375) % 255)
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return QColor(r, g, b, 100)
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def have_qstring():
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'''p3/qt5 get rid of QString wrapper as py3 has native unicode str type'''
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return not (sys.version_info.major >= 3 or QT_VERSION_STR.startswith('5.'))
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def natural_sort(list, key=lambda s: s):
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"""
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Sort the list into natural alphanumeric order.
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"""
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def get_alphanum_key_func(key):
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convert = lambda text: int(text) if text.isdigit() else text
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return lambda s: [convert(c) for c in re.split('([0-9]+)', key(s))]
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sort_key = get_alphanum_key_func(key)
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list.sort(key=sort_key)
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def get_rotate_crop_image(img, points):
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# Use Green's theory to judge clockwise or counterclockwise
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# author: biyanhua
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d = 0.0
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for index in range(-1, 3):
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d += -0.5 * (points[index + 1][1] + points[index][1]) * (
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points[index + 1][0] - points[index][0])
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if d < 0: # counterclockwise
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tmp = np.array(points)
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points[1], points[3] = tmp[3], tmp[1]
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try:
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img_crop_width = int(
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max(
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np.linalg.norm(points[0] - points[1]),
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np.linalg.norm(points[2] - points[3])))
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img_crop_height = int(
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max(
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np.linalg.norm(points[0] - points[3]),
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np.linalg.norm(points[1] - points[2])))
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pts_std = np.float32([[0, 0], [img_crop_width, 0],
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[img_crop_width, img_crop_height],
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[0, img_crop_height]])
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M = cv2.getPerspectiveTransform(points, pts_std)
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dst_img = cv2.warpPerspective(
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img,
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M, (img_crop_width, img_crop_height),
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borderMode=cv2.BORDER_REPLICATE,
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flags=cv2.INTER_CUBIC)
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dst_img_height, dst_img_width = dst_img.shape[0:2]
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if dst_img_height * 1.0 / dst_img_width >= 1.5:
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dst_img = np.rot90(dst_img)
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return dst_img
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except Exception as e:
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print(e)
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def boxPad(box, imgShape, pad : int) -> np.array:
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"""
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Pad a box with [pad] pixels on each side.
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"""
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box = np.array(box, dtype=np.int32)
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box[0][0], box[0][1] = box[0][0] - pad, box[0][1] - pad
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box[1][0], box[1][1] = box[1][0] + pad, box[1][1] - pad
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box[2][0], box[2][1] = box[2][0] + pad, box[2][1] + pad
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box[3][0], box[3][1] = box[3][0] - pad, box[3][1] + pad
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h, w, _ = imgShape
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box[:,0] = np.clip(box[:,0], 0, w)
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box[:,1] = np.clip(box[:,1], 0, h)
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return box
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def OBB2HBB(obb) -> np.array:
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"""
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Convert Oriented Bounding Box to Horizontal Bounding Box.
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"""
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hbb = np.zeros(4, dtype=np.int32)
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hbb[0] = min(obb[:, 0])
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hbb[1] = min(obb[:, 1])
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hbb[2] = max(obb[:, 0])
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hbb[3] = max(obb[:, 1])
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return hbb
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def expand_list(merged, html_list):
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'''
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Fill blanks according to merged cells
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'''
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sr, er, sc, ec = merged
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for i in range(sr, er):
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for j in range(sc, ec):
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html_list[i][j] = None
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html_list[sr][sc] = ''
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if ec - sc > 1:
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html_list[sr][sc] += " colspan={}".format(ec - sc)
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if er - sr > 1:
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html_list[sr][sc] += " rowspan={}".format(er - sr)
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return html_list
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def convert_token(html_list):
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'''
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Convert raw html to label format
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'''
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token_list = ["<tbody>"]
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# final html list:
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for row in html_list:
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token_list.append("<tr>")
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for col in row:
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if col == None:
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continue
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elif col == 'td':
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token_list.extend(["<td>", "</td>"])
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else:
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token_list.append("<td")
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if 'colspan' in col:
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_, n = col.split('colspan=')
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token_list.append(" colspan=\"{}\"".format(n))
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if 'rowspan' in col:
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_, n = col.split('rowspan=')
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token_list.append(" rowspan=\"{}\"".format(n))
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token_list.extend([">", "</td>"])
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token_list.append("</tr>")
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token_list.append("</tbody>")
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return token_list
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def stepsInfo(lang='en'):
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if lang == 'ch':
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msg = "1. 安装与运行：使用上述命令安装与运行程序。\n" \
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"2. 打开文件夹：在菜单栏点击 “文件” - 打开目录 选择待标记图片的文件夹.\n" \
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"3. 自动标注：点击 ”自动标注“，使用PPOCR超轻量模型对图片文件名前图片状态为 “X” 的图片进行自动标注。\n" \
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"4. 手动标注：点击 “矩形标注”（推荐直接在英文模式下点击键盘中的 “W”)，用户可对当前图片中模型未检出的部分进行手动" \
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"绘制标记框。点击键盘P，则使用四点标注模式（或点击“编辑” - “四点标注”），用户依次点击4个点后，双击左键表示标注完成。\n" \
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"5. 标记框绘制完成后，用户点击 “确认”，检测框会先被预分配一个 “待识别” 标签。\n" \
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"6. 重新识别：将图片中的所有检测画绘制/调整完成后，点击 “重新识别”，PPOCR模型会对当前图片中的**所有检测框**重新识别。\n" \
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"7. 内容更改：双击识别结果，对不准确的识别结果进行手动更改。\n" \
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"8. 保存：点击 “保存”，图片状态切换为 “√”，跳转至下一张。\n" \
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"9. 删除：点击 “删除图像”，图片将会被删除至回收站。\n" \
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"10. 标注结果：关闭应用程序或切换文件路径后，手动保存过的标签将会被存放在所打开图片文件夹下的" \
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"*Label.txt*中。在菜单栏点击 “PaddleOCR” - 保存识别结果后，会将此类图片的识别训练数据保存在*crop_img*文件夹下，" \
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"识别标签保存在*rec_gt.txt*中。\n"
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else:
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msg = "1. Build and launch using the instructions above.\n" \
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"2. Click 'Open Dir' in Menu/File to select the folder of the picture.\n" \
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"3. Click 'Auto recognition', use PPOCR model to automatically annotate images which marked with 'X' before the file name." \
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"4. Create Box:\n" \
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"4.1 Click 'Create RectBox' or press 'W' in English keyboard mode to draw a new rectangle detection box. Click and release left mouse to select a region to annotate the text area.\n" \
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"4.2 Press 'P' to enter four-point labeling mode which enables you to create any four-point shape by clicking four points with the left mouse button in succession and DOUBLE CLICK the left mouse as the signal of labeling completion.\n" \
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"5. After the marking frame is drawn, the user clicks 'OK', and the detection frame will be pre-assigned a TEMPORARY label.\n" \
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"6. Click re-Recognition, model will rewrite ALL recognition results in ALL detection box.\n" \
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"7. Double click the result in 'recognition result' list to manually change inaccurate recognition results.\n" \
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"8. Click 'Save', the image status will switch to '√',then the program automatically jump to the next.\n" \
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"9. Click 'Delete Image' and the image will be deleted to the recycle bin.\n" \
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"10. Labeling result: After closing the application or switching the file path, the manually saved label will be stored in *Label.txt* under the opened picture folder.\n" \
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" Click PaddleOCR-Save Recognition Results in the menu bar, the recognition training data of such pictures will be saved in the *crop_img* folder, and the recognition label will be saved in *rec_gt.txt*.\n"
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return msg
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def keysInfo(lang='en'):
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if lang == 'ch':
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msg = "快捷键\t\t\t说明\n" \
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"———————————————————————\n" \
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"Ctrl + shift + R\t\t对当前图片的所有标记重新识别\n" \
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"W\t\t\t新建矩形框\n" \
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"Q\t\t\t新建四点框\n" \
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"Ctrl + E\t\t编辑所选框标签\n" \
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"Ctrl + R\t\t重新识别所选标记\n" \
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"Ctrl + C\t\t复制并粘贴选中的标记框\n" \
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"Ctrl + 鼠标左键\t\t多选标记框\n" \
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"Backspace\t\t删除所选框\n" \
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"Ctrl + V\t\t确认本张图片标记\n" \
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"Ctrl + Shift + d\t删除本张图片\n" \
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"D\t\t\t下一张图片\n" \
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"A\t\t\t上一张图片\n" \
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"Ctrl++\t\t\t缩小\n" \
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"Ctrl--\t\t\t放大\n" \
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"↑→↓←\t\t\t移动标记框\n" \
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"———————————————————————\n" \
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"注：Mac用户Command键替换上述Ctrl键"
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else:
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msg = "Shortcut Keys\t\tDescription\n" \
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"———————————————————————\n" \
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"Ctrl + shift + R\t\tRe-recognize all the labels\n" \
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"\t\t\tof the current image\n" \
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"\n" \
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"W\t\t\tCreate a rect box\n" \
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"Q\t\t\tCreate a four-points box\n" \
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"Ctrl + E\t\tEdit label of the selected box\n" \
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"Ctrl + R\t\tRe-recognize the selected box\n" \
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"Ctrl + C\t\tCopy and paste the selected\n" \
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"\t\t\tbox\n" \
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"\n" \
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"Ctrl + Left Mouse\tMulti select the label\n" \
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"Button\t\t\tbox\n" \
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"\n" \
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"Backspace\t\tDelete the selected box\n" \
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"Ctrl + V\t\tCheck image\n" \
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"Ctrl + Shift + d\tDelete image\n" \
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"D\t\t\tNext image\n" \
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"A\t\t\tPrevious image\n" \
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"Ctrl++\t\t\tZoom in\n" \
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"Ctrl--\t\t\tZoom out\n" \
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"↑→↓←\t\t\tMove selected box" \
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"———————————————————————\n" \
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"Notice:For Mac users, use the 'Command' key instead of the 'Ctrl' key"
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return msg
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