Commit 4c4cad8b authored by Leif's avatar Leif
Browse files

Add PPOCRLabel

parent 569deedc
# ex: set ts=8 noet:
all: qt5 test
test: testpy3
testpy2:
python -m unittest discover tests
testpy3:
python3 -m unittest discover tests
qt4: qt4py2
qt5: qt5py3
qt4py2:
pyrcc4 -py2 -o libs/resources.py resources.qrc
qt4py3:
pyrcc4 -py3 -o libs/resources.py resources.qrc
qt5py3:
pyrcc5 -o libs/resources.py resources.qrc
clean:
rm -rf ~/.labelImgSettings.pkl *.pyc dist labelImg.egg-info __pycache__ build
pip_upload:
python3 setup.py upload
long_description:
restview --long-description
.PHONY: all
This diff is collapsed.
# PPOCRLabel
PPOCRLabel是一款适用于OCR领域的半自动化图形标注工具,使用python3和pyqt5编写,支持矩形框标注和四点标注模式,导出格式可直接用于PPOCR检测和识别模型的训练。
<img src="./data/gif/steps.gif" width="100%"/>
## 安装
### 1. 安装PaddleOCR
参考[PaddleOCR安装文档](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/installation.md)准备好PaddleOCR
### 2. 安装PPOCRLabel
#### Windows + Anaconda
下载安装[Anaconda](https://www.anaconda.com/download/#download) (Python 3+)
```
conda install pyqt=5
cd ./PPOCRLabel # 将目录切换到PPOCRLabel文件夹下
pyrcc5 -o libs/resources.py resources.qrc
python PPOCRLabel.py
```
#### Ubuntu Linux
```
pip3 install pyqt5
pip3 install trash-cli
cd ./PPOCRLabel # 将目录切换到PPOCRLabel文件夹下
python3 PPOCRLabel.py
```
#### macOS
```
pip3 install pyqt5
pip3 uninstall opencv-python # 由于mac版本的opencv与pyqt有冲突,需先手动卸载opencv
pip3 install opencv-contrib-python-headless # 安装headless版本的open-cv
cd ./PPOCRLabel # 将目录切换到PPOCRLabel文件夹下
python3 PPOCRLabel.py
```
## 使用
### 操作步骤
1. 安装与运行:使用上述命令安装与运行程序。
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<sup>[1]</sup>.
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<sup>[2]</sup>为 “X” 的图片进行自动标注。
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。
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。
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<sup>[3]</sup>
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。
8. 确认结果:点击 “确认”,图片状态切换为 “√”,跳转至下一张。
9. 删除:点击 “删除图像”,图片将会被删除至回收站。
10. 保存标注结果:关闭应用程序或切换文件路径后,手动确认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*<sup>[4]</sup>
### 注意
[1] PPOCRLabel以文件夹为基本标记单位,打开待标记的图片文件夹后,不会在窗口栏中显示图片,而是在点击 "选择文件夹" 之后直接将文件夹下的图片导入到程序中。
[2] 图片状态表示本张图片用户是否手动保存过,未手动保存过即为 “X”,手动保存过为 “√”。点击 “自动标注”按钮后,PPOCRLabel不会对状态为 “√” 的图片重新标注。
[3] 点击“重新识别”后,模型会对图片中的识别结果进行覆盖。因此如果在此之前手动更改过识别结果,有可能在重新识别后产生变动。
[4] PPOCRLabel产生的文件均在标记图片的文件夹中,包括一下几种,请勿手动更改其中内容,否则会引起程序出现异常。
| 文件名 | 说明 |
| :-----------: | :----------------------------------------------------------: |
| Label.txt | 检测标签,可直接用于PPOCR检测模型训练。用户每保存10张检测结果后,程序会进行自动写入。当用户关闭应用程序或切换文件路径后同样会进行写入。 |
| fileState.txt | 图片状态标记文件,保存当前文件夹下已经被用户手动确认过的图片名称。 |
| Cache.cach | 缓存文件,保存模型自动识别的结果。 |
| rec_gt.txt | 识别标签。可直接用于PPOCR识别模型训练。需用户手动点击菜单栏“PaddleOCR” - "保存识别结果"后产生。 |
| crop_img | 识别数据。按照检测框切割后的图片。与rec_gt.txt同时产生。 |
## 说明
### 内置模型
- 默认模型:PPOCRLabel默认使用PaddleOCR中的中英文超轻量OCR模型,支持中英文与数字识别,多种语言检测。
- 模型语言切换:用户可通过菜单栏中 "PaddleOCR" - "选择模型" 切换内置模型语言,目前支持的语言包括法文、德文、韩文、日文。具体模型下载链接可参考[PaddleOCR模型列表](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/models_list.md).
- 自定义模型:用户可根据[自定义模型代码使用](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/whl.md#%E8%87%AA%E5%AE%9A%E4%B9%89%E6%A8%A1%E5%9E%8B),通过修改PPOCRLabel.py中针对[PaddleOCR类的实例化](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/PPOCRLabel/PPOCRLabel.py#L110)替换成自己训练的模型。
### 导出部分识别结果
针对部分难以识别的数据,通过在识别结果的复选框中**取消勾选**相应的标记,其识别结果不会被导出。
*注意:识别结果中的复选框状态仍需用户手动点击保存后才能保留*
### 错误提示
- 如果同时使用whl包安装了paddleocr,其优先级大于通过paddleocr.py调用PaddleOCR类,whl包未更新时会导致程序异常。
- PPOCRLabel**不支持对中文文件名**的图片进行自动标注。
- 如果您在打开软件过程中出现**objc[XXXXX]**开头的错误,证明您的opencv版本太高,建议安装4.2版本:
```
pip install opencv-python==4.2.0.32
```
### 参考资料
1.[Tzutalin. LabelImg. Git code (2015)](https://github.com/tzutalin/labelImg)
# PPOCRLabel
PPOCRLabel is a semi-automatic graphic annotation tool suitable for OCR field. It is written in python3 and pyqt5, supporting rectangular box annotation and four-point annotation modes. Annotations can be directly used for the training of PPOCR detection and recognition models.
<img src="./data/gif/steps.gif" width="100%"/>
## Installation
### 1. Install PaddleOCR
Refer to [PaddleOCR installation document](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_ch/installation.md) to prepare PaddleOCR
### 2. Install PPOCRLabel
#### Windows + Anaconda
Download and install [Anaconda](https://www.anaconda.com/download/#download) (Python 3+)
```
conda install pyqt=5
cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder
pyrcc5 -o libs/resources.py resources.qrc
python PPOCRLabel.py --lang en
```
#### Ubuntu Linux
```
pip3 install pyqt5
pip3 install trash-cli
cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder
python3 PPOCRLabel.py --lang en
```
#### macOS
```
pip3 install pyqt5
pip3 uninstall opencv-python # Uninstall opencv manually as it conflicts with pyqt
pip3 install opencv-contrib-python-headless # Install the headless version of opencv
cd ./PPOCRLabel # Change the directory to the PPOCRLabel folder
python3 PPOCRLabel.py --lang en
```
## Usage
### Steps
1. Build and launch using the instructions above.
2. Click 'Open Dir' in Menu/File to select the folder of the picture.<sup>[1]</sup>
3. Click 'Auto recognition', use PPOCR model to automatically annotate images which marked with 'X' <sup>[2]</sup>before the file name.
4. Create Box:
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.
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.
5. After the marking frame is drawn, the user clicks "OK", and the detection frame will be pre-assigned a "TEMPORARY" label.
6. Click 're-Recognition', model will rewrite ALL recognition results in ALL detection box<sup>[3]</sup>.
7. Double click the result in 'recognition result' list to manually change inaccurate recognition results.
8. Click "Save", the image status will switch to "√",then the program automatically jump to the next.
9. Click "Delete Image" and the image will be deleted to the recycle bin.
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.
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*<sup>[4]</sup>.
### Note
[1] PPOCRLabel uses the opened folder as the project. After opening the image folder, the picture will not be displayed in the dialog. Instead, the pictures under the folder will be directly imported into the program after clicking "Open Dir".
[2] The image status indicates whether the user has saved the image manually. If it has not been saved manually it is "X", otherwise it is "√", PPOCRLabel will not relabel pictures with a status of "√".
[3] After clicking "Re-recognize", the model will overwrite ALL recognition results in the picture.
Therefore, if the recognition result has been manually changed before, it may change after re-recognition.
[4] The files produced by PPOCRLabel include the following, please do not manually change the contents, otherwise it will cause the program to be abnormal.
| File name | Description |
| :-----------: | :----------------------------------------------------------: |
| Label.txt | The detection label file can be directly used for PPOCR detection model training. After the user saves 10 label results, the file will be automatically saved. It will also be written when the user closes the application or changes the file folder. |
| fileState.txt | The picture status file save the image in the current folder that has been manually confirmed by the user. |
| Cache.cach | Cache files to save the results of model recognition. |
| rec_gt.txt | The recognition label file, which can be directly used for PPOCR identification model training, is generated after the user clicks on the menu bar "PaddleOCR"-"Save recognition result". |
| crop_img | The recognition data, generated at the same time with *rec_gt.txt* |
## Explanation
### Built-in Model
- Default model: PPOCRLabel uses the Chinese and English ultra-lightweight OCR model in PaddleOCR by default, supports Chinese, English and number recognition, and multiple language detection.
- Model language switching: Changing the built-in model language is supportable by clicking "PaddleOCR"-"Choose OCR Model" in the menu bar. Currently supported languages​include French, German, Korean, and Japanese.
For specific model download links, please refer to [PaddleOCR Model List](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_en/models_list_en.md#multilingual-recognition-modelupdating)
- Custom model: The model trained by users can be replaced by modifying PPOCRLabel.py in [PaddleOCR class instantiation](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/PPOCRLabel/PPOCRLabel.py#L110) referring [Custom Model Code](https://github.com/PaddlePaddle/PaddleOCR/blob/develop/doc/doc_en/whl_en.md#use-custom-model)
### Export partial recognition results
For some data that are difficult to recognize, the recognition results will not be exported by **unchecking** the corresponding tags in the recognition results checkbox.
*Note: The status of the checkboxes in the recognition results still needs to be saved manually by clicking Save Button.*
### Error message
- If paddleocr is installed with whl, it has a higher priority than calling PaddleOCR class with paddleocr.py, which may cause an exception if whl package is not updated.
- If you get an error starting with **objc[XXXXX]** when opening the software, it proves that your opencv version is too high. It is recommended to install version 4.2:
```
pip install opencv-python==4.2.0.32
```
### Related
1.[Tzutalin. LabelImg. Git code (2015)](https://github.com/tzutalin/labelImg)
# 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 sys
try:
from PyQt5.QtWidgets import QWidget, QHBoxLayout, QComboBox
except ImportError:
# needed for py3+qt4
# Ref:
# http://pyqt.sourceforge.net/Docs/PyQt4/incompatible_apis.html
# http://stackoverflow.com/questions/21217399/pyqt4-qtcore-qvariant-object-instead-of-a-string
if sys.version_info.major >= 3:
import sip
sip.setapi('QVariant', 2)
from PyQt4.QtGui import QWidget, QHBoxLayout, QComboBox
class ComboBox(QWidget):
def __init__(self, parent=None, items=[]):
super(ComboBox, self).__init__(parent)
layout = QHBoxLayout()
self.cb = QComboBox()
self.items = items
self.cb.addItems(self.items)
self.cb.currentIndexChanged.connect(parent.comboSelectionChanged)
layout.addWidget(self.cb)
self.setLayout(layout)
def update_items(self, items):
self.items = items
self.cb.clear()
self.cb.addItems(self.items)
__version_info__ = ('1', '0', '0')
__version__ = '.'.join(__version_info__)
try:
from PyQt5.QtGui import *
from PyQt5.QtCore import *
from PyQt5.QtWidgets import *
except ImportError:
from PyQt4.QtGui import *
from PyQt4.QtCore import *
import json
from libs.utils import newIcon
BB = QDialogButtonBox
class Worker(QThread):
progressBarValue = pyqtSignal(int)
listValue = pyqtSignal(str)
endsignal = pyqtSignal(int, str)
handle = 0
def __init__(self, ocr, mImgList, mainThread, model):
super(Worker, self).__init__()
self.ocr = ocr
self.mImgList = mImgList
self.mainThread = mainThread
self.model = model
self.setStackSize(1024*1024)
def run(self):
try:
findex = 0
for Imgpath in self.mImgList:
if self.handle == 0:
self.listValue.emit(Imgpath)
if self.model == 'paddle':
self.result_dic = self.ocr.ocr(Imgpath, cls=True, det=True)
# 结果保存
if self.result_dic is None or len(self.result_dic) == 0:
print('Can not recognise file is : ', Imgpath)
pass
else:
for res in self.result_dic:
chars = res[1][0]
cond = res[1][1]
posi = res[0]
self.listValue.emit("文字:" + chars + " 置信度:" + str(cond) + " 坐标:" + json.dumps(posi))
self.mainThread.result_dic = self.result_dic
self.mainThread.filePath = Imgpath
# 保存
self.mainThread.saveFile(mode='Auto')
findex += 1
self.progressBarValue.emit(findex)
else:
break
self.endsignal.emit(0, "readAll")
self.exec()
except Exception as e:
print(e)
raise
class AutoDialog(QDialog):
def __init__(self, text="Enter object label", parent=None, ocr=None, mImgList=None, lenbar=0):
super(AutoDialog, self).__init__(parent)
self.setFixedWidth(1000)
self.parent = parent
self.ocr = ocr
self.mImgList = mImgList
self.pb = QProgressBar()
self.pb.setRange(0, lenbar)
self.pb.setValue(0)
layout = QVBoxLayout()
layout.addWidget(self.pb)
self.model = 'paddle'
self.listWidget = QListWidget(self)
layout.addWidget(self.listWidget)
self.buttonBox = bb = BB(BB.Ok | BB.Cancel, Qt.Horizontal, self)
bb.button(BB.Ok).setIcon(newIcon('done'))
bb.button(BB.Cancel).setIcon(newIcon('undo'))
bb.accepted.connect(self.validate)
bb.rejected.connect(self.reject)
layout.addWidget(bb)
bb.button(BB.Ok).setEnabled(False)
self.setLayout(layout)
self.setWindowTitle("自动标注中")
self.setWindowModality(Qt.ApplicationModal)
# self.setWindowFlags(Qt.WindowCloseButtonHint)
self.thread_1 = Worker(self.ocr, self.mImgList, self.parent, 'paddle')
self.thread_1.progressBarValue.connect(self.handleProgressBarSingal)
self.thread_1.listValue.connect(self.handleListWidgetSingal)
self.thread_1.endsignal.connect(self.handleEndsignalSignal)
def handleProgressBarSingal(self, i):
self.pb.setValue(i)
def handleListWidgetSingal(self, i):
self.listWidget.addItem(i)
titem = self.listWidget.item(self.listWidget.count() - 1)
self.listWidget.scrollToItem(titem)
def handleEndsignalSignal(self, i, str):
if i == 0 and str == "readAll":
self.buttonBox.button(BB.Ok).setEnabled(True)
self.buttonBox.button(BB.Cancel).setEnabled(False)
def reject(self):
print("reject")
self.thread_1.handle = -1
self.thread_1.quit()
# del self.thread_1
# if self.thread_1.isRunning():
# self.thread_1.terminate()
# self.thread_1.quit()
# super(AutoDialog,self).reject()
while not self.thread_1.isFinished():
pass
self.accept()
def validate(self):
self.accept()
def postProcess(self):
try:
self.edit.setText(self.edit.text().trimmed())
# print(self.edit.text())
except AttributeError:
# PyQt5: AttributeError: 'str' object has no attribute 'trimmed'
self.edit.setText(self.edit.text())
print(self.edit.text())
def popUp(self):
self.thread_1.start()
return 1 if self.exec_() else None
def closeEvent(self, event):
print("???")
# if self.thread_1.isRunning():
# self.thread_1.quit()
#
# # self._thread.terminate()
# # del self.thread_1
# super(AutoDialog, self).closeEvent(event)
self.reject()
This diff is collapsed.
# 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.
try:
from PyQt5.QtGui import *
from PyQt5.QtCore import *
from PyQt5.QtWidgets import QColorDialog, QDialogButtonBox
except ImportError:
from PyQt4.QtGui import *
from PyQt4.QtCore import *
BB = QDialogButtonBox
class ColorDialog(QColorDialog):
def __init__(self, parent=None):
super(ColorDialog, self).__init__(parent)
self.setOption(QColorDialog.ShowAlphaChannel)
# The Mac native dialog does not support our restore button.
self.setOption(QColorDialog.DontUseNativeDialog)
# Add a restore defaults button.
# The default is set at invocation time, so that it
# works across dialogs for different elements.
self.default = None
self.bb = self.layout().itemAt(1).widget()
self.bb.addButton(BB.RestoreDefaults)
self.bb.clicked.connect(self.checkRestore)
def getColor(self, value=None, title=None, default=None):
self.default = default
if title:
self.setWindowTitle(title)
if value:
self.setCurrentColor(value)
return self.currentColor() if self.exec_() else None
def checkRestore(self, button):
if self.bb.buttonRole(button) & BB.ResetRole and self.default:
self.setCurrentColor(self.default)
# 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.
SETTING_FILENAME = 'filename'
SETTING_RECENT_FILES = 'recentFiles'
SETTING_WIN_SIZE = 'window/size'
SETTING_WIN_POSE = 'window/position'
SETTING_WIN_GEOMETRY = 'window/geometry'
SETTING_LINE_COLOR = 'line/color'
SETTING_FILL_COLOR = 'fill/color'
SETTING_ADVANCE_MODE = 'advanced'
SETTING_WIN_STATE = 'window/state'
SETTING_SAVE_DIR = 'savedir'
SETTING_PAINT_LABEL = 'paintlabel'
SETTING_LAST_OPEN_DIR = 'lastOpenDir'
SETTING_AUTO_SAVE = 'autosave'
SETTING_SINGLE_CLASS = 'singleclass'
FORMAT_PASCALVOC='PascalVOC'
FORMAT_YOLO='YOLO'
SETTING_DRAW_SQUARE = 'draw/square'
SETTING_LABEL_FILE_FORMAT= 'labelFileFormat'
DEFAULT_ENCODING = 'utf-8'
# 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.
#!/usr/bin/env python
# -*- coding: utf8 -*-
import json
from pathlib import Path
from libs.constants import DEFAULT_ENCODING
import os
JSON_EXT = '.json'
ENCODE_METHOD = DEFAULT_ENCODING
class CreateMLWriter:
def __init__(self, foldername, filename, imgsize, shapes, outputfile, databasesrc='Unknown', localimgpath=None):
self.foldername = foldername
self.filename = filename
self.databasesrc = databasesrc
self.imgsize = imgsize
self.boxlist = []
self.localimgpath = localimgpath
self.verified = False
self.shapes = shapes
self.outputfile = outputfile
def write(self):
if os.path.isfile(self.outputfile):
with open(self.outputfile, "r") as file:
input_data = file.read()
outputdict = json.loads(input_data)
else:
outputdict = []
outputimagedict = {
"image": self.filename,
"annotations": []
}
for shape in self.shapes:
points = shape["points"]
x1 = points[0][0]
y1 = points[0][1]
x2 = points[1][0]
y2 = points[2][1]
height, width, x, y = self.calculate_coordinates(x1, x2, y1, y2)
shapedict = {
"label": shape["label"],
"coordinates": {
"x": x,
"y": y,
"width": width,
"height": height
}
}
outputimagedict["annotations"].append(shapedict)
# check if image already in output
exists = False
for i in range(0, len(outputdict)):
if outputdict[i]["image"] == outputimagedict["image"]:
exists = True
outputdict[i] = outputimagedict
break
if not exists:
outputdict.append(outputimagedict)
Path(self.outputfile).write_text(json.dumps(outputdict), ENCODE_METHOD)
def calculate_coordinates(self, x1, x2, y1, y2):
if x1 < x2:
xmin = x1
xmax = x2
else:
xmin = x2
xmax = x1
if y1 < y2:
ymin = y1
ymax = y2
else:
ymin = y2
ymax = y1
width = xmax - xmin
if width < 0:
width = width * -1
height = ymax - ymin
# x and y from center of rect
x = xmin + width / 2
y = ymin + height / 2
return height, width, x, y
class CreateMLReader:
def __init__(self, jsonpath, filepath):
self.jsonpath = jsonpath
self.shapes = []
self.verified = False
self.filename = filepath.split("/")[-1:][0]
try:
self.parse_json()
except ValueError:
print("JSON decoding failed")
def parse_json(self):
with open(self.jsonpath, "r") as file:
inputdata = file.read()
outputdict = json.loads(inputdata)
self.verified = True
if len(self.shapes) > 0:
self.shapes = []
for image in outputdict:
if image["image"] == self.filename:
for shape in image["annotations"]:
self.add_shape(shape["label"], shape["coordinates"])
def add_shape(self, label, bndbox):
xmin = bndbox["x"] - (bndbox["width"] / 2)
ymin = bndbox["y"] - (bndbox["height"] / 2)
xmax = bndbox["x"] + (bndbox["width"] / 2)
ymax = bndbox["y"] + (bndbox["height"] / 2)
points = [(xmin, ymin), (xmax, ymin), (xmax, ymax), (xmin, ymax)]
self.shapes.append((label, points, None, None, True))
def get_shapes(self):
return self.shapes
# 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.
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
try:
from PyQt5.QtGui import *
from PyQt5.QtCore import *
from PyQt5.QtWidgets import *
except ImportError:
# needed for py3+qt4
# Ref:
# http://pyqt.sourceforge.net/Docs/PyQt4/incompatible_apis.html
# http://stackoverflow.com/questions/21217399/pyqt4-qtcore-qvariant-object-instead-of-a-string
if sys.version_info.major >= 3:
import sip
sip.setapi('QVariant', 2)
from PyQt4.QtGui import *
from PyQt4.QtCore import *
# PyQt5: TypeError: unhashable type: 'QListWidgetItem'
class HashableQListWidgetItem(QListWidgetItem):
def __init__(self, *args):
super(HashableQListWidgetItem, self).__init__(*args)
def __hash__(self):
return hash(id(self))
# 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.
try:
from PyQt5.QtGui import *
from PyQt5.QtCore import *
from PyQt5.QtWidgets import *
except ImportError:
from PyQt4.QtGui import *
from PyQt4.QtCore import *
from libs.utils import newIcon, labelValidator
BB = QDialogButtonBox
class LabelDialog(QDialog):
def __init__(self, text="Enter object label", parent=None, listItem=None):
super(LabelDialog, self).__init__(parent)
self.edit = QLineEdit() # OLD
# self.edit = QTextEdit()
self.edit.setText(text)
# self.edit.setValidator(labelValidator()) # 验证有效性
self.edit.editingFinished.connect(self.postProcess)
model = QStringListModel()
model.setStringList(listItem)
completer = QCompleter()
completer.setModel(model)
self.edit.setCompleter(completer)
layout = QVBoxLayout()
layout.addWidget(self.edit)
self.buttonBox = bb = BB(BB.Ok | BB.Cancel, Qt.Horizontal, self)
bb.button(BB.Ok).setIcon(newIcon('done'))
bb.button(BB.Cancel).setIcon(newIcon('undo'))
bb.accepted.connect(self.validate)
bb.rejected.connect(self.reject)
layout.addWidget(bb)
# if listItem is not None and len(listItem) > 0:
# self.listWidget = QListWidget(self)
# for item in listItem:
# self.listWidget.addItem(item)
# self.listWidget.itemClicked.connect(self.listItemClick)
# self.listWidget.itemDoubleClicked.connect(self.listItemDoubleClick)
# layout.addWidget(self.listWidget)
self.setLayout(layout)
def validate(self):
try:
if self.edit.text().trimmed():
self.accept()
except AttributeError:
# PyQt5: AttributeError: 'str' object has no attribute 'trimmed'
if self.edit.text().strip():
self.accept()
def postProcess(self):
try:
self.edit.setText(self.edit.text().trimmed())
# print(self.edit.text())
except AttributeError:
# PyQt5: AttributeError: 'str' object has no attribute 'trimmed'
self.edit.setText(self.edit.text())
print(self.edit.text())
def popUp(self, text='', move=True):
self.edit.setText(text)
self.edit.setSelection(0, len(text))
self.edit.setFocus(Qt.PopupFocusReason)
if move:
cursor_pos = QCursor.pos()
parent_bottomRight = self.parentWidget().geometry()
max_x = parent_bottomRight.x() + parent_bottomRight.width() - self.sizeHint().width()
max_y = parent_bottomRight.y() + parent_bottomRight.height() - self.sizeHint().height()
max_global = self.parentWidget().mapToGlobal(QPoint(max_x, max_y))
if cursor_pos.x() > max_global.x():
cursor_pos.setX(max_global.x())
if cursor_pos.y() > max_global.y():
cursor_pos.setY(max_global.y())
self.move(cursor_pos)
return self.edit.text() if self.exec_() else None
def listItemClick(self, tQListWidgetItem):
try:
text = tQListWidgetItem.text().trimmed()
except AttributeError:
# PyQt5: AttributeError: 'str' object has no attribute 'trimmed'
text = tQListWidgetItem.text().strip()
self.edit.setText(text)
def listItemDoubleClick(self, tQListWidgetItem):
self.listItemClick(tQListWidgetItem)
self.validate()
# Copyright (c) 2016 Tzutalin
# Create by TzuTaLin <tzu.ta.lin@gmail.com>
try:
from PyQt5.QtGui import QImage
except ImportError:
from PyQt4.QtGui import QImage
from base64 import b64encode, b64decode
from libs.pascal_voc_io import PascalVocWriter
from libs.yolo_io import YOLOWriter
from libs.pascal_voc_io import XML_EXT
from enum import Enum
import os.path
import sys
class LabelFileFormat(Enum):
PASCAL_VOC= 1
YOLO = 2
class LabelFileError(Exception):
pass
class LabelFile(object):
# It might be changed as window creates. By default, using XML ext
# suffix = '.lif'
suffix = XML_EXT
def __init__(self, filename=None):
self.shapes = ()
self.imagePath = None
self.imageData = None
self.verified = False
def savePascalVocFormat(self, filename, shapes, imagePath, imageData,
lineColor=None, fillColor=None, databaseSrc=None):
imgFolderPath = os.path.dirname(imagePath)
imgFolderName = os.path.split(imgFolderPath)[-1]
imgFileName = os.path.basename(imagePath)
#imgFileNameWithoutExt = os.path.splitext(imgFileName)[0]
# Read from file path because self.imageData might be empty if saving to
# Pascal format
image = QImage()
image.load(imagePath)
imageShape = [image.height(), image.width(),
1 if image.isGrayscale() else 3]
writer = PascalVocWriter(imgFolderName, imgFileName,
imageShape, localImgPath=imagePath)
writer.verified = self.verified
for shape in shapes:
points = shape['points']
label = shape['label']
# Add Chris
difficult = int(shape['difficult'])
bndbox = LabelFile.convertPoints2BndBox(points)
writer.addBndBox(bndbox[0], bndbox[1], bndbox[2], bndbox[3], label, difficult)
writer.save(targetFile=filename)
return
def saveYoloFormat(self, filename, shapes, imagePath, imageData, classList,
lineColor=None, fillColor=None, databaseSrc=None):
imgFolderPath = os.path.dirname(imagePath)
imgFolderName = os.path.split(imgFolderPath)[-1]
imgFileName = os.path.basename(imagePath)
#imgFileNameWithoutExt = os.path.splitext(imgFileName)[0]
# Read from file path because self.imageData might be empty if saving to
# Pascal format
image = QImage()
image.load(imagePath)
imageShape = [image.height(), image.width(),
1 if image.isGrayscale() else 3]
writer = YOLOWriter(imgFolderName, imgFileName,
imageShape, localImgPath=imagePath)
writer.verified = self.verified
for shape in shapes:
points = shape['points']
label = shape['label']
# Add Chris
difficult = int(shape['difficult'])
bndbox = LabelFile.convertPoints2BndBox(points)
writer.addBndBox(bndbox[0], bndbox[1], bndbox[2], bndbox[3], label, difficult)
writer.save(targetFile=filename, classList=classList)
return
def toggleVerify(self):
self.verified = not self.verified
''' ttf is disable
def load(self, filename):
import json
with open(filename, 'rb') as f:
data = json.load(f)
imagePath = data['imagePath']
imageData = b64decode(data['imageData'])
lineColor = data['lineColor']
fillColor = data['fillColor']
shapes = ((s['label'], s['points'], s['line_color'], s['fill_color'])\
for s in data['shapes'])
# Only replace data after everything is loaded.
self.shapes = shapes
self.imagePath = imagePath
self.imageData = imageData
self.lineColor = lineColor
self.fillColor = fillColor
def save(self, filename, shapes, imagePath, imageData, lineColor=None, fillColor=None):
import json
with open(filename, 'wb') as f:
json.dump(dict(
shapes=shapes,
lineColor=lineColor, fillColor=fillColor,
imagePath=imagePath,
imageData=b64encode(imageData)),
f, ensure_ascii=True, indent=2)
'''
@staticmethod
def isLabelFile(filename):
fileSuffix = os.path.splitext(filename)[1].lower()
return fileSuffix == LabelFile.suffix
@staticmethod
def convertPoints2BndBox(points):
xmin = float('inf')
ymin = float('inf')
xmax = float('-inf')
ymax = float('-inf')
for p in points:
x = p[0]
y = p[1]
xmin = min(x, xmin)
ymin = min(y, ymin)
xmax = max(x, xmax)
ymax = max(y, ymax)
# Martin Kersner, 2015/11/12
# 0-valued coordinates of BB caused an error while
# training faster-rcnn object detector.
if xmin < 1:
xmin = 1
if ymin < 1:
ymin = 1
return (int(xmin), int(ymin), int(xmax), int(ymax))
# 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.
#!/usr/bin/env python
# -*- coding: utf8 -*-
import sys
from xml.etree import ElementTree
from xml.etree.ElementTree import Element, SubElement
from lxml import etree
import codecs
from libs.constants import DEFAULT_ENCODING
from libs.ustr import ustr
XML_EXT = '.xml'
ENCODE_METHOD = DEFAULT_ENCODING
class PascalVocWriter:
def __init__(self, foldername, filename, imgSize,databaseSrc='Unknown', localImgPath=None):
self.foldername = foldername
self.filename = filename
self.databaseSrc = databaseSrc
self.imgSize = imgSize
self.boxlist = []
self.localImgPath = localImgPath
self.verified = False
def prettify(self, elem):
"""
Return a pretty-printed XML string for the Element.
"""
rough_string = ElementTree.tostring(elem, 'utf8')
root = etree.fromstring(rough_string)
return etree.tostring(root, pretty_print=True, encoding=ENCODE_METHOD).replace(" ".encode(), "\t".encode())
# minidom does not support UTF-8
'''reparsed = minidom.parseString(rough_string)
return reparsed.toprettyxml(indent="\t", encoding=ENCODE_METHOD)'''
def genXML(self):
"""
Return XML root
"""
# Check conditions
if self.filename is None or \
self.foldername is None or \
self.imgSize is None:
return None
top = Element('annotation')
if self.verified:
top.set('verified', 'yes')
folder = SubElement(top, 'folder')
folder.text = self.foldername
filename = SubElement(top, 'filename')
filename.text = self.filename
if self.localImgPath is not None:
localImgPath = SubElement(top, 'path')
localImgPath.text = self.localImgPath
source = SubElement(top, 'source')
database = SubElement(source, 'database')
database.text = self.databaseSrc
size_part = SubElement(top, 'size')
width = SubElement(size_part, 'width')
height = SubElement(size_part, 'height')
depth = SubElement(size_part, 'depth')
width.text = str(self.imgSize[1])
height.text = str(self.imgSize[0])
if len(self.imgSize) == 3:
depth.text = str(self.imgSize[2])
else:
depth.text = '1'
segmented = SubElement(top, 'segmented')
segmented.text = '0'
return top
def addBndBox(self, xmin, ymin, xmax, ymax, name, difficult):
bndbox = {'xmin': xmin, 'ymin': ymin, 'xmax': xmax, 'ymax': ymax}
bndbox['name'] = name
bndbox['difficult'] = difficult
self.boxlist.append(bndbox)
def appendObjects(self, top):
for each_object in self.boxlist:
object_item = SubElement(top, 'object')
name = SubElement(object_item, 'name')
name.text = ustr(each_object['name'])
pose = SubElement(object_item, 'pose')
pose.text = "Unspecified"
truncated = SubElement(object_item, 'truncated')
if int(float(each_object['ymax'])) == int(float(self.imgSize[0])) or (int(float(each_object['ymin']))== 1):
truncated.text = "1" # max == height or min
elif (int(float(each_object['xmax']))==int(float(self.imgSize[1]))) or (int(float(each_object['xmin']))== 1):
truncated.text = "1" # max == width or min
else:
truncated.text = "0"
difficult = SubElement(object_item, 'difficult')
difficult.text = str( bool(each_object['difficult']) & 1 )
bndbox = SubElement(object_item, 'bndbox')
xmin = SubElement(bndbox, 'xmin')
xmin.text = str(each_object['xmin'])
ymin = SubElement(bndbox, 'ymin')
ymin.text = str(each_object['ymin'])
xmax = SubElement(bndbox, 'xmax')
xmax.text = str(each_object['xmax'])
ymax = SubElement(bndbox, 'ymax')
ymax.text = str(each_object['ymax'])
def save(self, targetFile=None):
root = self.genXML()
self.appendObjects(root)
out_file = None
if targetFile is None:
out_file = codecs.open(
self.filename + XML_EXT, 'w', encoding=ENCODE_METHOD)
else:
out_file = codecs.open(targetFile, 'w', encoding=ENCODE_METHOD)
prettifyResult = self.prettify(root)
out_file.write(prettifyResult.decode('utf8'))
out_file.close()
class PascalVocReader:
def __init__(self, filepath):
# shapes type:
# [labbel, [(x1,y1), (x2,y2), (x3,y3), (x4,y4)], color, color, difficult]
self.shapes = []
self.filepath = filepath
self.verified = False
try:
self.parseXML()
except:
pass
def getShapes(self):
return self.shapes
def addShape(self, label, bndbox, difficult):
xmin = int(float(bndbox.find('xmin').text))
ymin = int(float(bndbox.find('ymin').text))
xmax = int(float(bndbox.find('xmax').text))
ymax = int(float(bndbox.find('ymax').text))
points = [(xmin, ymin), (xmax, ymin), (xmax, ymax), (xmin, ymax)]
self.shapes.append((label, points, None, None, difficult))
def parseXML(self):
assert self.filepath.endswith(XML_EXT), "Unsupport file format"
parser = etree.XMLParser(encoding=ENCODE_METHOD)
xmltree = ElementTree.parse(self.filepath, parser=parser).getroot()
filename = xmltree.find('filename').text
try:
verified = xmltree.attrib['verified']
if verified == 'yes':
self.verified = True
except KeyError:
self.verified = False
for object_iter in xmltree.findall('object'):
bndbox = object_iter.find("bndbox")
label = object_iter.find('name').text
# Add chris
difficult = False
if object_iter.find('difficult') is not None:
difficult = bool(int(object_iter.find('difficult').text))
self.addShape(label, bndbox, difficult)
return True
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