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- # Copyright (c) <2015-Present> Tzutalin
- # Copyright (C) 2013 MIT, Computer Science and Artificial Intelligence Laboratory. Bryan Russell, Antonio Torralba,
- # William T. Freeman. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and
- # associated documentation files (the "Software"), to deal in the Software without restriction, including without
- # limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the
- # Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
- # The above copyright notice and this permission notice shall be included in all copies or substantial portions of
- # the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT
- # NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
- # SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
- # CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
- # THE SOFTWARE.
- import hashlib
- import os
- import re
- import sys
- from math import sqrt
- import cv2
- import numpy as np
- from PyQt5.QtCore import QRegExp, QT_VERSION_STR
- from PyQt5.QtGui import QIcon, QRegExpValidator, QColor
- from PyQt5.QtWidgets import QPushButton, QAction, QMenu
- from libs.ustr import ustr
- __dir__ = os.path.dirname(os.path.abspath(__file__)) # 获取本程序文件路径
- __iconpath__ = os.path.abspath(os.path.join(__dir__, '../resources/icons'))
- def newIcon(icon, iconSize=None):
- if iconSize is not None:
- return QIcon(QIcon(__iconpath__ + "/" + icon + ".png").pixmap(iconSize, iconSize))
- else:
- return QIcon(__iconpath__ + "/" + icon + ".png")
- def newButton(text, icon=None, slot=None):
- b = QPushButton(text)
- if icon is not None:
- b.setIcon(newIcon(icon))
- if slot is not None:
- b.clicked.connect(slot)
- return b
- def newAction(parent, text, slot=None, shortcut=None, icon=None,
- tip=None, checkable=False, enabled=True, iconSize=None):
- """Create a new action and assign callbacks, shortcuts, etc."""
- a = QAction(text, parent)
- if icon is not None:
- if iconSize is not None:
- a.setIcon(newIcon(icon, iconSize))
- else:
- a.setIcon(newIcon(icon))
- if shortcut is not None:
- if isinstance(shortcut, (list, tuple)):
- a.setShortcuts(shortcut)
- else:
- a.setShortcut(shortcut)
- if tip is not None:
- a.setToolTip(tip)
- a.setStatusTip(tip)
- if slot is not None:
- a.triggered.connect(slot)
- if checkable:
- a.setCheckable(True)
- a.setEnabled(enabled)
- return a
- def addActions(widget, actions):
- for action in actions:
- if action is None:
- widget.addSeparator()
- elif isinstance(action, QMenu):
- widget.addMenu(action)
- else:
- widget.addAction(action)
- def labelValidator():
- return QRegExpValidator(QRegExp(r'^[^ \t].+'), None)
- class struct(object):
- def __init__(self, **kwargs):
- self.__dict__.update(kwargs)
- def distance(p):
- return sqrt(p.x() * p.x() + p.y() * p.y())
- def fmtShortcut(text):
- mod, key = text.split('+', 1)
- return '<b>%s</b>+<b>%s</b>' % (mod, key)
- def generateColorByText(text):
- s = ustr(text)
- hashCode = int(hashlib.sha256(s.encode('utf-8')).hexdigest(), 16)
- r = int((hashCode / 255) % 255)
- g = int((hashCode / 65025) % 255)
- b = int((hashCode / 16581375) % 255)
- return QColor(r, g, b, 100)
- def have_qstring():
- '''p3/qt5 get rid of QString wrapper as py3 has native unicode str type'''
- return not (sys.version_info.major >= 3 or QT_VERSION_STR.startswith('5.'))
- def natural_sort(list, key=lambda s: s):
- """
- Sort the list into natural alphanumeric order.
- """
- def get_alphanum_key_func(key):
- convert = lambda text: int(text) if text.isdigit() else text
- return lambda s: [convert(c) for c in re.split('([0-9]+)', key(s))]
- sort_key = get_alphanum_key_func(key)
- list.sort(key=sort_key)
- def get_rotate_crop_image(img, points):
- # Use Green's theory to judge clockwise or counterclockwise
- # author: biyanhua
- d = 0.0
- for index in range(-1, 3):
- d += -0.5 * (points[index + 1][1] + points[index][1]) * (
- points[index + 1][0] - points[index][0])
- if d < 0: # counterclockwise
- tmp = np.array(points)
- points[1], points[3] = tmp[3], tmp[1]
- try:
- img_crop_width = int(
- max(
- np.linalg.norm(points[0] - points[1]),
- np.linalg.norm(points[2] - points[3])))
- img_crop_height = int(
- max(
- np.linalg.norm(points[0] - points[3]),
- np.linalg.norm(points[1] - points[2])))
- pts_std = np.float32([[0, 0], [img_crop_width, 0],
- [img_crop_width, img_crop_height],
- [0, img_crop_height]])
- M = cv2.getPerspectiveTransform(points, pts_std)
- dst_img = cv2.warpPerspective(
- img,
- M, (img_crop_width, img_crop_height),
- borderMode=cv2.BORDER_REPLICATE,
- flags=cv2.INTER_CUBIC)
- dst_img_height, dst_img_width = dst_img.shape[0:2]
- if dst_img_height * 1.0 / dst_img_width >= 1.5:
- dst_img = np.rot90(dst_img)
- return dst_img
- except Exception as e:
- print(e)
- def boxPad(box, imgShape, pad : int) -> np.array:
- """
- Pad a box with [pad] pixels on each side.
- """
- box = np.array(box, dtype=np.int32)
- box[0][0], box[0][1] = box[0][0] - pad, box[0][1] - pad
- box[1][0], box[1][1] = box[1][0] + pad, box[1][1] - pad
- box[2][0], box[2][1] = box[2][0] + pad, box[2][1] + pad
- box[3][0], box[3][1] = box[3][0] - pad, box[3][1] + pad
- h, w, _ = imgShape
- box[:,0] = np.clip(box[:,0], 0, w)
- box[:,1] = np.clip(box[:,1], 0, h)
- return box
- def expand_list(merged, html_list):
- '''
- Fill blanks according to merged cells
- '''
- sr, er, sc, ec = merged
- for i in range(sr, er):
- for j in range(sc, ec):
- html_list[i][j] = None
- html_list[sr][sc] = ''
- if ec - sc > 1:
- html_list[sr][sc] += " colspan={}".format(ec - sc)
- if er - sr > 1:
- html_list[sr][sc] += " rowspan={}".format(er - sr)
- return html_list
- def convert_token(html_list):
- '''
- Convert raw html to label format
- '''
- token_list = ["<tbody>"]
- # final html list:
- for row in html_list:
- token_list.append("<tr>")
- for col in row:
- if col == None:
- continue
- elif col == 'td':
- token_list.extend(["<td>", "</td>"])
- else:
- token_list.append("<td")
- if 'colspan' in col:
- _, n = col.split('colspan=')
- token_list.append(" colspan=\"{}\"".format(n[0]))
- if 'rowspan' in col:
- _, n = col.split('rowspan=')
- token_list.append(" rowspan=\"{}\"".format(n[0]))
- token_list.extend([">", "</td>"])
- token_list.append("</tr>")
- token_list.append("</tbody>")
- return token_list
- def rebuild_html_from_ppstructure_label(label_info):
- from html import escape
- html_code = label_info['html']['structure']['tokens'].copy()
- to_insert = [
- i for i, tag in enumerate(html_code) if tag in ('<td>', '>')
- ]
- for i, cell in zip(to_insert[::-1], label_info['html']['cells'][::-1]):
- if cell['tokens']:
- cell = [
- escape(token) if len(token) == 1 else token
- for token in cell['tokens']
- ]
- cell = ''.join(cell)
- html_code.insert(i + 1, cell)
- html_code = ''.join(html_code)
- html_code = '<html><body><table>{}</table></body></html>'.format(
- html_code)
- return html_code
- def stepsInfo(lang='en'):
- if lang == 'ch':
- msg = "1. 安装与运行:使用上述命令安装与运行程序。\n" \
- "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" \
- "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" \
- "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" \
- "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" \
- "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" \
- "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" \
- "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" \
- "8. 保存:点击 “保存”,图片状态切换为 “√”,跳转至下一张。\n" \
- "9. 删除:点击 “删除图像”,图片将会被删除至回收站。\n" \
- "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" \
- "*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," \
- "识别标签保存在*rec_gt.txt*中。\n"
- else:
- msg = "1. Build and launch using the instructions above.\n" \
- "2. Click 'Open Dir' in Menu/File to select the folder of the picture.\n" \
- "3. Click 'Auto recognition', use PPOCR model to automatically annotate images which marked with 'X' before the file name." \
- "4. Create Box:\n" \
- "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" \
- "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" \
- "5. After the marking frame is drawn, the user clicks 'OK', and the detection frame will be pre-assigned a TEMPORARY label.\n" \
- "6. Click re-Recognition, model will rewrite ALL recognition results in ALL detection box.\n" \
- "7. Double click the result in 'recognition result' list to manually change inaccurate recognition results.\n" \
- "8. Click 'Save', the image status will switch to '√',then the program automatically jump to the next.\n" \
- "9. Click 'Delete Image' and the image will be deleted to the recycle bin.\n" \
- "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" \
- " 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"
- return msg
- def keysInfo(lang='en'):
- if lang == 'ch':
- msg = "快捷键\t\t\t说明\n" \
- "———————————————————————\n" \
- "Ctrl + shift + R\t\t对当前图片的所有标记重新识别\n" \
- "W\t\t\t新建矩形框\n" \
- "Q\t\t\t新建四点框\n" \
- "Ctrl + E\t\t编辑所选框标签\n" \
- "Ctrl + R\t\t重新识别所选标记\n" \
- "Ctrl + C\t\t复制并粘贴选中的标记框\n" \
- "Ctrl + 鼠标左键\t\t多选标记框\n" \
- "Backspace\t\t删除所选框\n" \
- "Ctrl + V\t\t确认本张图片标记\n" \
- "Ctrl + Shift + d\t删除本张图片\n" \
- "D\t\t\t下一张图片\n" \
- "A\t\t\t上一张图片\n" \
- "Ctrl++\t\t\t缩小\n" \
- "Ctrl--\t\t\t放大\n" \
- "↑→↓←\t\t\t移动标记框\n" \
- "———————————————————————\n" \
- "注:Mac用户Command键替换上述Ctrl键"
- else:
- msg = "Shortcut Keys\t\tDescription\n" \
- "———————————————————————\n" \
- "Ctrl + shift + R\t\tRe-recognize all the labels\n" \
- "\t\t\tof the current image\n" \
- "\n" \
- "W\t\t\tCreate a rect box\n" \
- "Q\t\t\tCreate a four-points box\n" \
- "Ctrl + E\t\tEdit label of the selected box\n" \
- "Ctrl + R\t\tRe-recognize the selected box\n" \
- "Ctrl + C\t\tCopy and paste the selected\n" \
- "\t\t\tbox\n" \
- "\n" \
- "Ctrl + Left Mouse\tMulti select the label\n" \
- "Button\t\t\tbox\n" \
- "\n" \
- "Backspace\t\tDelete the selected box\n" \
- "Ctrl + V\t\tCheck image\n" \
- "Ctrl + Shift + d\tDelete image\n" \
- "D\t\t\tNext image\n" \
- "A\t\t\tPrevious image\n" \
- "Ctrl++\t\t\tZoom in\n" \
- "Ctrl--\t\t\tZoom out\n" \
- "↑→↓←\t\t\tMove selected box" \
- "———————————————————————\n" \
- "Notice:For Mac users, use the 'Command' key instead of the 'Ctrl' key"
- return msg
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