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v2_release.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Main script for running QuantiFly training.
"""CytoCensus Software v0.1
Copyright (C) 2017 Dominic Waithe Martin Hailstone
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
"""
import time
import errno
import os
import os.path
import re
import pickle
import sys
from multiprocessing import freeze_support
freeze_support()
from PyQt5 import QtGui, QtCore, QtWidgets # ,QtWebKit
import numpy as np
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar
from matplotlib.figure import Figure
#import numdifftools as ndt
from common.common_navigation import navigation_setup, create_channel_objects, btn_fn, on_about
from parameters.parameter_object import ParameterClass
from ROI.user_ROI import ROI
#from functions import v2_functions
from features import local_features
from fileio import file_handler
from common import common_navigation
from functions.maxima import count_maxima
from functions import v2_functions as v2
class fileDialog(QtWidgets.QMainWindow):
"""The dialog for loading images"""
def __init__(self, parent):
super(fileDialog, self).__init__()
self.parent = parent
self.initUI()
self.parent.config = {}
try:
with open(os.path.expanduser('~')+'/.densitycount/config.p', "rb") as pfile:
self.parent.config = pickle.load(pfile)
self.parent.filepath = self.parent.config['filepath']
except Exception: #catch all because pickle can throw loads of Exceptions
self.parent.filepath = os.path.expanduser('~')+'/'
try:
os.makedirs(os.path.expanduser('~')+'/.densitycount/')
except OSError as exc:
if exc.errno != errno.EACCES:
print ('Write permission to '+self.parent.filepath+' denied')
else:
print ('unable to make directory: ', os.path.expanduser(
'~') + '/.densitycount/')
def initUI(self):
self.text_edit = QtWidgets.QTextEdit()
self.setCentralWidget(self.text_edit)
self.statusBar()
openFile = QtWidgets.QAction(QtGui.QIcon('open.png'), 'Open', self)
openFile.setShortcut('Ctrl+O')
openFile.setStatusTip('Open new File')
openFile.triggered.connect(self.showDialog)
menubar = self.menuBar()
fileMenu = menubar.addMenu('&File')
fileMenu.addAction(openFile)
self.setGeometry(300, 300, 350, 500)
self.setWindowTitle('File dialog')
def showDialog(self):
self.parent.selIntButton.setEnabled(False)
par_obj.file_array = []
path = None
for path in QtWidgets.QFileDialog.getOpenFileNames(self, 'Open file', self.parent.filepath, 'Images(*.tif *.tiff *.mrc *.dv);;'):
if path != '' and path !='Images(*.tif *.tiff *.mrc *.dv)':
if type(path) is not list:
par_obj.file_array.append(path)
else:
par_obj.file_array=par_obj.file_array+path
if par_obj.file_array is []:
return
self.parent.config['filepath'] = str(
QtCore.QFileInfo(path).absolutePath())+'/'
pickle.dump(self.parent.config, open(
str(os.path.expanduser('~')+'/.densitycount/config.p'), "wb"))
self.parent.image_status_text.showMessage('Status: Loading Images. ')
success, updateText = v2.import_data_fn(par_obj, par_obj.file_array)
self.parent.image_status_text.showMessage(updateText)
if success is True:
self.parent.updateAfterImport()
#self.parent.resize_factor_text.hide()
#self.parent.resize_factor_input.hide()
else:
self.parent.image_status_text.showMessage(
'Image import unsuccesful. Use TIF files')
return
class Load_win_fn(QtWidgets.QWidget):
"""The class for loading and processing images"""
def __init__(self): # ,par_obj,win):
super(Load_win_fn, self).__init__()
# Load images button
load_im_lo = QtWidgets.QHBoxLayout()
self.loadImages_button = QtWidgets.QPushButton("Load Images", self)
load_im_lo.addWidget(self.loadImages_button)
load_im_lo.addStretch()
self.ex = fileDialog(self)
self.loadImages_button.clicked.connect(self.ex.showDialog)
# about button
about = QtWidgets.QPushButton('About', self)
load_im_lo.addWidget(about)
about.clicked.connect(lambda: on_about(self))
# SigmaData input field.
resize_lo = QtWidgets.QHBoxLayout()
sampling_lo = QtWidgets.QHBoxLayout()
max_features_lo = QtWidgets.QHBoxLayout()
self.samplingText = QtWidgets.QLabel('Sampling :')
self.samplingText.setToolTip(
'5 is a good default, try setting this lower for rare and small objects')
self.samplingText.resize(40, 20)
self.samplingText.hide()
self.sampling_input = QtWidgets.QLineEdit(
str(par_obj.limit_ratio_size))
self.sampling_input.setToolTip(
'5 is a good default, try setting this lower for rare and small objects')
self.sampling_input.resize(10, 10)
self.sampling_input.textChanged[str].connect(self.sampling_change)
self.sampling_input.hide()
sampling_lo.addWidget(self.samplingText)
sampling_lo.addWidget(self.sampling_input)
sampling_lo.addStretch()
#self.featuresText = QtWidgets.QLabel('Max size Random Feature subset')
#self.featuresText.resize(40, 20)
# self.featuresText.hide()
#self.features_input = QtWidgets.QLineEdit(str(par_obj.max_features))
# self.features_input.resize(10,10)
# self.features_input.textChanged[str].connect(self.features_change)
# self.features_input.hide()
# max_features_lo.addWidget(self.featuresText)
# max_features_lo.addWidget(self.features_input)
self.resize_factor_text = QtWidgets.QLabel('Resize Factor:')
self.resize_factor_text.resize(40, 20)
self.resize_factor_text.setToolTip(
'Subsample image for speed of calculation')
self.resize_factor_input = QtWidgets.QLineEdit(
str(par_obj.resize_factor))
self.resize_factor_input.setToolTip(
'Subsample image for speed of calculation')
self.resize_factor_input.resize(10, 10)
self.resize_factor_input.textChanged[str].connect(
self.resize_factor_change)
resize_lo.addWidget(self.resize_factor_text)
resize_lo.addWidget(self.resize_factor_input)
resize_lo.addStretch()
# Channel dialog generation.
Channel_Select_lo = QtWidgets.QVBoxLayout()
Channel_button_lo = QtWidgets.QHBoxLayout()
self.Text_CHopt = QtWidgets.QLabel(
'Please select which channels you want to include in the feature calculation')
Channel_Select_lo.addWidget(self.Text_CHopt)
self.Text_CHopt.resize(500, 40)
self.Text_CHopt.hide()
# Object factory for channel selection.
ButtonGroup = create_channel_objects(self, par_obj, 10, True)
for cbx in ButtonGroup:
cbx[0].hide()
Channel_button_lo.addWidget(cbx[0])
Channel_Select_lo.addLayout(Channel_button_lo)
Channel_button_lo.addStretch()
Channel_Select_lo.addStretch()
# setup preview plot
self.figure1 = Figure(figsize=(2, 2))
self.canvas1 = FigureCanvas(self.figure1)
self.plt1 = self.figure1.add_subplot(1, 1, 1)
self.resize(100, 100)
self.figure1.subplots_adjust(
left=0.001, right=0.999, top=0.999, bottom=0.001)
self.plt1.set_xticklabels([])
self.plt1.set_yticklabels([])
self.canvas1.hide()
par_obj.rect_h = 0
par_obj.rect_w = 0
canvas_lo = QtWidgets.QHBoxLayout()
canvas_lo.addWidget(self.canvas1)
canvas_lo.addStretch()
# Image range selection
Im_Range_lo = QtWidgets.QVBoxLayout()
# Image Details
self.Text_FrmOpt2 = QtWidgets.QLabel()
Im_Range_lo.addWidget(self.Text_FrmOpt2)
self.Text_FrmOpt2.hide()
self.Text_FrmOpt4 = QtWidgets.QLabel()
Im_Range_lo.addWidget(self.Text_FrmOpt4)
self.Text_FrmOpt4.hide()
# Image frames dialog.
Text_FrmOpt1_panel = QtWidgets.QHBoxLayout()
self.Text_FrmOpt1 = QtWidgets.QLabel(
'Please choose the z-slices you wish to use for training. Use \'-\' to indicate a range:')
self.Text_FrmOpt1.hide()
Im_Range_lo.addLayout(Text_FrmOpt1_panel)
# Image frames input.
linEdit_Frm_panel = QtWidgets.QHBoxLayout()
self.linEdit_Frm = QtWidgets.QLineEdit()
self.linEdit_Frm.hide()
linEdit_Frm_panel.addWidget(self.linEdit_Frm)
linEdit_Frm_panel.addStretch()
Im_Range_lo.addLayout(linEdit_Frm_panel)
Text_FrmOpt3_panel = QtWidgets.QHBoxLayout()
self.Text_FrmOpt3 = QtWidgets.QLabel()
self.Text_FrmOpt3.setText(
'Please choose the time-points you wish to use for training. Use either \',\' to separate individual frames or a \'-\' to indicate a range:')
self.Text_FrmOpt3.hide()
Text_FrmOpt1_panel.addWidget(self.Text_FrmOpt1)
Text_FrmOpt3_panel.addWidget(self.Text_FrmOpt3)
Im_Range_lo.addLayout(Text_FrmOpt3_panel)
linEdit_Frm_panel2 = QtWidgets.QHBoxLayout()
self.linEdit_Frm2 = QtWidgets.QLineEdit()
self.linEdit_Frm2.hide()
linEdit_Frm_panel2.addWidget(self.linEdit_Frm2)
linEdit_Frm_panel2.addStretch()
Im_Range_lo.addLayout(linEdit_Frm_panel2)
# Feature calculation type to perform:
self.Text_Radio = QtWidgets.QLabel(
'Feature select which kind of feature detection you would like to use:')
self.Text_Radio.resize(500, 40)
self.Text_Radio.hide()
self.radio_group = QtWidgets.QButtonGroup(self) # Number
self.radio0 = QtWidgets.QRadioButton("Basic", self)
self.radio0.setToolTip(
'13 features/channel (Set Feature size) - Fast, less accurate')
self.radio1 = QtWidgets.QRadioButton("Detailed", self)
self.radio1.setToolTip(
'21 features/channel (Set Feature size) - Slower, more accurate')
self.radio2 = QtWidgets.QRadioButton("Pyramid (Default)", self)
self.radio2.setToolTip(
'26 features/channel, calculated more efficiently. No need to set feature size')
self.radio3 = QtWidgets.QRadioButton("Histogram equalised", self)
self.radio3.setToolTip(
'Pyramid features but equalised for image variation. Try if your imaging conditions vary a lot - Slowest')
self.radio4 = QtWidgets.QRadioButton("Radial", self)
self.radio4.setToolTip(
'Radial features - Try if your objects are circular but vary in size')
self.radio5 = QtWidgets.QRadioButton("2-layer", self)
self.radio5.setToolTip(
'Calculate features of the probability map, similar to autocontext. Slower, and risks over-training')
self.radio2.setChecked(True)
self.radio_group.addButton(self.radio0)
self.radio_group.addButton(self.radio1)
self.radio_group.addButton(self.radio2)
self.radio_group.addButton(self.radio3)
self.radio_group.addButton(self.radio4)
self.radio_group.addButton(self.radio5)
self.radio0.hide()
self.radio1.hide()
self.radio2.hide()
self.radio3.hide()
self.radio4.hide()
self.radio5.hide()
Radio_Layout = QtWidgets.QVBoxLayout()
Radio_Layout.addWidget(self.Text_Radio)
Radio_Layout.addWidget(self.radio0)
Radio_Layout.addWidget(self.radio1)
Radio_Layout.addWidget(self.radio2)
Radio_Layout.addWidget(self.radio3)
Radio_Layout.addWidget(self.radio4)
Radio_Layout.addWidget(self.radio5)
Radio_Layout.addStretch()
# Feature sigma, if basic or detailed features chosen
sigma_lo = QtWidgets.QHBoxLayout()
self.feature_scaleText = QtWidgets.QLabel('Feature size (sigma):')
self.feature_scaleText.resize(40, 20)
self.feature_scaleText.hide()
self.feature_scale_input = QtWidgets.QLineEdit(
str(par_obj.feature_scale))
self.feature_scale_input.resize(10, 10)
self.feature_scale_input.textChanged[str].connect(
self.feature_scale_change)
self.feature_scale_input.hide()
sigma_lo.addWidget(self.feature_scaleText)
sigma_lo.addWidget(self.feature_scale_input)
sigma_lo.addStretch()
# Load images button
Confirm_im_lo = QtWidgets.QHBoxLayout()
self.confirmImages_btn = QtWidgets.QPushButton("Confirm Images")
self.confirmImages_btn.clicked.connect(self.confirmImages_btn_fn)
self.confirmImages_btn.setEnabled(False)
# Move to training button.
self.selIntButton = QtWidgets.QPushButton("Goto Training")
self.selIntButton.clicked.connect(win.loadTrainFn)
self.selIntButton.setEnabled(False)
Confirm_im_lo.addWidget(self.confirmImages_btn)
Confirm_im_lo.addWidget(self.selIntButton)
Confirm_im_lo.addStretch()
self.image_status_text = QtWidgets.QStatusBar()
self.image_status_text.setStyleSheet("QLabel { color : green }")
self.image_status_text.showMessage(
'Status: Highlight training images in folder. ')
# Set up Vertical layout
vbox = QtWidgets.QVBoxLayout()
self.setLayout(vbox)
vbox.addLayout(load_im_lo)
vbox.addLayout(resize_lo)
vbox.addLayout(sampling_lo)
vbox.addLayout(max_features_lo)
vbox.addLayout(Channel_Select_lo)
vbox.addLayout(canvas_lo)
vbox.addLayout(Im_Range_lo)
vbox.addLayout(Radio_Layout)
vbox.addLayout(sigma_lo)
vbox.addStretch()
vbox.addLayout(Confirm_im_lo)
vbox.addWidget(self.image_status_text)
# File browsing functions
#layout = QtWidgets.QVBoxLayout()
def resize_factor_change(self, text):
"""Updates on change of image resize parameter"""
if text != "":
par_obj.resize_factor = int(text)
def sampling_change(self, text):
"""Updates on change of sampling"""
if text != "":
par_obj.limit_ratio_size = float(text)
def features_change(self, text):
"""Updates on change of feature number"""
if text != "":
par_obj.max_features = int(text)
def feature_scale_change(self, text):
"""Updates on change of feature scale"""
if text != "":
par_obj.feature_scale = float(text)
for fileno in range(0, par_obj.max_file):
for tp in range(0, par_obj.max_t):
par_obj.data_store['feat_arr'][fileno][tp] = {}
def updateAfterImport(self):
"""Specific to ui updates"""
if par_obj.max_z > 1:
# self.linEdit_Frm.setText('1-'+str(par_obj.max_z))
self.Text_FrmOpt2.setText('There are '+str(par_obj.max_z)+' z-slices in total. The image has dimensions x: '
+ str(par_obj.ori_width)+' and y: '+str(par_obj.ori_height))
if par_obj.max_t > 1:
# self.linEdit_Frm2.setText('1-'+str(par_obj.max_t))
self.Text_FrmOpt4.setText(
'There are '+str(par_obj.max_t)+' timepoints in total.')
self.linEdit_Frm2.show()
self.Text_FrmOpt4.show()
self.Text_FrmOpt3.show()
self.Text_FrmOpt1.show()
self.Text_FrmOpt2.show()
self.linEdit_Frm.show()
self.confirmImages_btn.setEnabled(True)
self.plt1.cla()
if par_obj.ex_img.max() != 0:
self.plt1.imshow(par_obj.ex_img[:,:,:3]/par_obj.ex_img.max())
else:
self.plt1.imshow(par_obj.ex_img[:,:,:3])
self.plt1.set_xticklabels([])
self.plt1.set_yticklabels([])
self.canvas1.show()
self.canvas1.draw()
par_obj.ch_active = []
if par_obj.numCH > 0:
self.Text_CHopt.show()
for i in range(0, par_obj.numCH):
self.CH_cbx[i].show()
par_obj.ch_active.append(i)
else:
par_obj.ch_active.append(0)
# self.CH_cbx1.stateChange()
self.feature_scale_input.show()
self.feature_scaleText.show()
# self.features_input.show()
# self.featuresText.show()
self.radio0.show()
self.radio1.show()
self.radio2.show()
self.radio3.show()
self.radio4.show()
self.sampling_input.show()
self.samplingText.show()
self.Text_Radio.show()
def hyphen_range(self, s):
""" yield each integer from a complex range string like "1-9,12, 15-20,23"
>>> list(hyphen_range('1-9,12, 15-20,23'))
[1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 15, 16, 17, 18, 19, 20, 23]
>>> list(hyphen_range('1-9,12, 15-20,2-3-4'))
Traceback (most recent call last):
...
ValueError: format error in 2-3-4
"""
s_list = []
if s != '':
for x in s.split(','):
elem = x.split('-')
if len(elem) == 1: # a number
s_list.append(int(elem[0])-1)
elif len(elem) == 2: # a range inclusive
start, end = map(int, elem)
for i in xrange(start, end+1):
s_list.append(i-1)
else: # more than one hyphen
raise ValueError('format error in %s' % x)
return s_list
def confirmImages_btn_fn(self):
if par_obj.max_t > 1:
tmStr = self.linEdit_Frm2.text()
if tmStr != '':
par_obj.tpt_list = self.hyphen_range(tmStr)
else:
par_obj.tpt_list = range(par_obj.max_t)
else:
par_obj.tpt_list = [0]
if par_obj.max_z > 0: #if current file has multiple z
#this fails if first file has single z
fmStr = self.linEdit_Frm.text()
if fmStr != '': # catch empty limit
par_obj.user_max_z = max(self.hyphen_range(fmStr))
par_obj.user_min_z = min(self.hyphen_range(fmStr))
else: #excessively large default max_z for training
par_obj.user_max_z = 1000
par_obj.user_min_z = 0
else:
par_obj.user_max_z = 0
par_obj.user_min_z = 0
self.image_status_text.showMessage(
'Status: Images loaded. Click \'Goto Training\'')
self.selIntButton.setEnabled(True)
v2.setup_parameters(self, par_obj)
if self.radio0.isChecked():
par_obj.feature_type = 'basic'
if self.radio1.isChecked():
par_obj.feature_type = 'fine'
if self.radio2.isChecked():
par_obj.feature_type = 'pyramid'
if self.radio3.isChecked():
par_obj.feature_type = 'histeq'
if self.radio4.isChecked():
par_obj.feature_type = 'radial'
print (par_obj.feature_type)
def report_progress(self, message):
self.image_status_text.showMessage('Status: ' + message)
app.processEvents()
class Win_fn(QtWidgets.QWidget):
"""Class which houses main training functionality"""
def __init__(self, par_obj):
super(Win_fn, self).__init__()
self.threadpool = QtCore.QThreadPool()
self.threadpool.setMaxThreadCount = 1
# Sets up the figures for displaying images.
self.figure1 = Figure(figsize=(8, 8), dpi=100)
self.canvas1 = FigureCanvas(self.figure1)
self.figure1.patch.set_facecolor('grey')
self.cursor = ROI(self, par_obj)
self.plt1 = self.figure1.add_subplot(1, 1, 1)
im_RGB = np.zeros((512, 512))
# Makes sure it spans the whole figure.
self.figure1.subplots_adjust(
left=0.001, right=0.999, top=0.999, bottom=0.001)
self.toolbar = NavigationToolbar(self.canvas1, self)
self.toolbar.actionTriggered.connect(self.on_resize)
self.toolbar.actionTriggered.connect(self.on_resize)
self.plt1.imshow(im_RGB)
# Removes the tick labels
self.plt1.set_xticklabels([])
self.plt1.set_yticklabels([])
# Initialises the second figure.
self.figure2 = Figure(figsize=(8, 8), dpi=100)
self.canvas2 = FigureCanvas(self.figure2)
self.figure2.patch.set_facecolor('grey')
self.plt2 = self.figure2.add_subplot(1, 1, 1)
self.plt2_is_clear = False
# Makes sure it spans the whole figure.
self.figure2.subplots_adjust(
left=0.001, right=0.999, top=0.999, bottom=0.001)
self.plt2.imshow(im_RGB)
self.plt2.set_xticklabels([])
self.plt2.set_yticklabels([])
# The ui for training
self.count_txt = QtWidgets.QLabel()
self.image_num_txt = QtWidgets.QLabel()
box = QtWidgets.QVBoxLayout()
self.setLayout(box)
# Widget containing the top panel.
top_panel = QtWidgets.QHBoxLayout()
# Top left and right widget panels
top_left_panel = QtWidgets.QGroupBox('Navigation and Annotation')
top_right_panel = QtWidgets.QGroupBox('Detection and Model')
# Grid layouts for the top and left panels.
self.top_left_grid = QtWidgets.QGridLayout()
self.top_right_grid = QtWidgets.QGridLayout()
self.top_left_grid.setSpacing(2)
self.top_right_grid.setSpacing(2)
# Widgets for the top panel.
top_panel.addWidget(top_left_panel)
top_panel.addWidget(top_right_panel)
top_panel.addStretch()
# Set the layout of the panels to be the grids.
top_left_panel.setLayout(self.top_left_grid)
top_right_panel.setLayout(self.top_right_grid)
# Sets the current text.
self.image_num_txt.setText(' Image is: ' + str(par_obj.curr_z + 1))
self.count_txt = QtWidgets.QLabel()
# Sets up the button which saves the ROI.
self.save_ROI_btn = QtWidgets.QPushButton('1. Save ROI')
self.save_ROI_btn.setToolTip(
'Right-click or Ctrl-click and drag to make ROI. Then Save ROI (Space)')
self.save_ROI_btn.setEnabled(True)
# Sets up the button which saves the ROI.
self.save_dots_btn = QtWidgets.QPushButton('2. Save Dots')
self.save_dots_btn.setToolTip(
'Click within ROI to add annotations. Then Save Dots')
self.save_dots_btn.setEnabled(False)
# Button for training model
self.train_model_btn = QtWidgets.QPushButton('3. Train Model')
self.train_model_btn.setToolTip(
'When annotations are added, train the model')
self.train_model_btn.setEnabled(False)
# Selects and reactivates an existing ROI.
self.delete_ROI_btn = QtWidgets.QPushButton('Delete ROI')
self.delete_ROI_btn.setToolTip(
'Delete selected ROI')
self.delete_ROI_btn.setEnabled(False)
# Selects and reactivates an existing ROI.
self.sel_ROI_btn = QtWidgets.QPushButton('Edit ROI')
self.sel_ROI_btn.setToolTip(
'Click on ROI to select- Select ROI highlighted in yellow')
self.sel_ROI_btn.setEnabled(True)
self.select_ROI = False
# Allows deletion of dots.
self.remove_dots_btn = QtWidgets.QPushButton('Remove Dots')
self.remove_dots_btn.setToolTip(
'Select ROI, then click Remove dots, and choose dots to remove')
self.remove_dots_btn.setEnabled(False)
self.remove_dots = False
# Load in ROI file.
self.load_gt_btn = QtWidgets.QPushButton('Import ROI/Dots')
self.load_gt_btn.setToolTip('Load previously saved annotation file')
self.load_gt_btn.setEnabled(True)
self.load_gt = False
# Save in ROI file.
self.save_gt_btn = QtWidgets.QPushButton('Export ROI/Dots')
self.save_gt_btn.setToolTip(
'Save ROIs and dots to annotation file (.quantiROI)')
self.save_gt_btn.setEnabled(True)
self.save_gt = False
# common navigation elements
self.Btn_fns = btn_fn(self)
navigation_setup(self, par_obj)
# Populates the grid with the different widgets.
self.top_left_grid.addLayout(self.panel_buttons, 0, 0, 1, 3)
self.top_left_grid.addWidget(self.image_num_txt, 2, 0, 2, 3)
self.top_left_grid.addWidget(self.save_ROI_btn, 4, 0)
self.top_left_grid.addWidget(self.save_dots_btn, 4, 1)
self.top_left_grid.addWidget(self.train_model_btn, 4, 2)
self.top_left_grid.addWidget(self.sel_ROI_btn, 5, 0)
self.top_left_grid.addWidget(self.remove_dots_btn, 5, 1)
self.top_left_grid.addWidget(self.load_gt_btn, 6, 2, 1, 1)
self.top_left_grid.addWidget(self.save_gt_btn, 6, 1, 1, 1)
self.top_left_grid.addWidget(self.delete_ROI_btn, 6, 0, 1, 1 )
# SigmaData input Label.
self.sigma_data_text = QtWidgets.QLabel(self)
self.sigma_data_text.setText('Object size (pixels):')
self.sigma_data_text.setToolTip(
'Set this smaller than the object size.\n Map on right hand side should show similar size objects to those in your image.\n If your object size is >10 you should resize your images')
self.top_right_grid.addWidget(self.sigma_data_text, 0, 0)
# SigmaData input field.
self.sigma_data_input = QtWidgets.QLineEdit(str(par_obj.sigma_data))
self.sigma_data_input.onChanged = self.sigmaOnChange
self.sigma_data_input.setFixedWidth(40)
self.sigma_data_input.textChanged[str].connect(self.sigmaOnChange)
self.top_right_grid.addWidget(self.sigma_data_input, 0, 1)
# Feature scale input Label.
#self.sigma_data_text = QtWidgets.QLabel()
#self.sigma_data_text.setText('Scale of Feature Descriptor:')
#self.top_right_grid.addWidget(self.sigma_data_text, 1, 0)
# Feature scale input field
#self.feature_scale_input = QtWidgets.QLineEdit(str(par_obj.feature_scale))
#self.feature_scale_input.onChanged = self.feature_scale_change
#self.feature_scale_input.resize(40, 20)
# self.feature_scale_input.textChanged[str].connect(self.feature_scale_change)
# self.feature_scale_input.setFixedWidth(40)
#self.top_right_grid.addWidget(self.feature_scale_input, 1, 1)
# Feature scale input btn.
#self.feat_scale_change_btn = QtWidgets.QPushButton('Recalculate Features')
# self.feat_scale_change_btn.setEnabled(True)
#self.top_right_grid.addWidget(self.feat_scale_change_btn, 1, 2)
# Saves the model
self.save_model_btn = QtWidgets.QPushButton('Save Training Model')
self.save_model_btn.setToolTip(
'When happy with your training, save the model for batch processing')
self.save_model_btn.setEnabled(False)
self.top_right_grid.addWidget(self.save_model_btn, 1, 0)
# Saves the extremel random decision tree model
self.save_model_name_txt = QtWidgets.QLineEdit('Insert Model Name')
self.top_right_grid.addWidget(self.save_model_name_txt, 1, 1)
self.output_count_txt = QtWidgets.QLabel()
self.top_right_grid.addWidget(self.output_count_txt, 3, 1, 1, 4)
# Saves the extremely random decision tree model.
self.save_model_desc_txt = QtWidgets.QLineEdit(
'Insert Model Description')
self.save_model_desc_txt.setFixedWidth(200)
self.top_right_grid.addWidget(self.save_model_desc_txt, 2, 0, 1, 4)
self.clear_dots_btn = QtWidgets.QPushButton('Clear All ROI')
self.top_right_grid.addWidget(self.clear_dots_btn, 1, 2)
# Shows the kernel label distributions
self.kernel_show_btn = QtWidgets.QPushButton('Showing Kernel')
self.kernel_show_btn.setMinimumWidth(170)
self.clear_dots_btn.setEnabled(False)
self.top_right_grid.addWidget(self.kernel_show_btn, 2, 2)
self.evaluate_btn = QtWidgets.QPushButton('Evaluate Forest')
self.evaluate_btn.setToolTip('Evaluate the model on another timepoint')
self.evaluate_btn.setEnabled(False)
self.top_right_grid.addWidget(self.evaluate_btn, 3, 0)
self.count_maxima_btn = QtWidgets.QPushButton('Find object centres')
self.count_maxima_btn.setToolTip(
'Use the probability map to estimate cell centres')
self.count_maxima_btn.setEnabled(False)
self.top_right_grid.addWidget(self.count_maxima_btn, 4, 0)
# Button for overlay
self.overlay_prediction_btn = QtWidgets.QPushButton(
'Overlay Prediction')
self.overlay_prediction_btn.setToolTip(
'Switch between displaying Prediction, Training, and Cell centres')
self.overlay_prediction_btn.setEnabled(True)
self.top_right_grid.addWidget(self.overlay_prediction_btn, 0, 2)
# common navigation buttons
self.count_replot_btn = QtWidgets.QPushButton('Replot')
self.count_maxima_plot_on = QtWidgets.QCheckBox()
self.count_maxima_plot_on.setChecked = False
self.count_txt_1 = QtWidgets.QLineEdit(str(par_obj.min_distance[0]))
self.count_txt_1.setFixedWidth(20)
self.count_txt_2 = QtWidgets.QLineEdit(str(par_obj.min_distance[1]))
self.count_txt_2.setFixedWidth(20)
self.count_txt_3 = QtWidgets.QLineEdit(str(par_obj.min_distance[2]))
self.count_txt_3.setFixedWidth(20)
abs_thr_lbl = QtWidgets.QLabel('Abs Thr:')
self.abs_thr_txt = QtWidgets.QLineEdit(str(par_obj.abs_thr))
self.abs_thr_txt.setFixedWidth(35)
z_cal_lbl = QtWidgets.QLabel('Z Cal.:')
self.z_cal_txt = QtWidgets.QLabel(str(par_obj.z_cal))
self.z_cal_txt.setFixedWidth(50)
self.strictness_btn = QtWidgets.QCheckBox()
self.strictness_btn.setChecked(True)
strictness_btn_lbl = QtWidgets.QLabel('Strict')
self.strictness_btn.setToolTip('Set whether to enforce size strictness')
self.min_distance_panel = QtWidgets.QHBoxLayout()
self.min_distance_panel.addStretch()
self.min_distance_panel.addWidget(QtWidgets.QLabel("x:"))
self.min_distance_panel.addWidget(self.count_txt_1)
self.min_distance_panel.addWidget(QtWidgets.QLabel("y:"))
self.min_distance_panel.addWidget(self.count_txt_2)
self.min_distance_panel.addWidget(QtWidgets.QLabel("z:"))
self.min_distance_panel.addWidget(self.count_txt_3)
self.min_distance_panel.addWidget(abs_thr_lbl)
self.min_distance_panel.addWidget(self.abs_thr_txt)
self.min_distance_panel.addWidget(z_cal_lbl)
self.min_distance_panel.addWidget(self.z_cal_txt)
self.min_distance_panel.addWidget(strictness_btn_lbl)
self.min_distance_panel.addWidget(self.strictness_btn)
self.top_right_grid.addLayout(self.min_distance_panel, 4, 1, 1, 2)
# self.top_right_grid.addWidget(self.count_maxima_plot_on,4,2)
self.top_right_grid.setRowStretch(4, 2)
# Sets up the image panel splitter.
image_panel = QtWidgets.QSplitter(QtCore.Qt.Horizontal)
image_panel.addWidget(self.canvas1)
image_panel.addWidget(self.canvas2)
# Sets up mouse settings on the image
self.canvas1.mpl_connect('axes_enter_event', self.on_enter)
self.canvas1.mpl_connect('axes_leave_event', self.on_leave)
self.bpe = self.canvas1.mpl_connect(
'button_press_event', self.on_click)
self.bre = self.canvas1.mpl_connect(
'button_release_event', self.on_unclick)
self.ome = self.canvas1.mpl_connect(
'motion_notify_event', self.on_motion)
self.l1 = None
self.l2 = None
self.l3 = None
self.l4 = None
self.okp = self.canvas1.mpl_connect('key_press_event', self.on_key)
# Splitter which separates the controls at the top and the images below.
splitter = QtWidgets.QSplitter(QtCore.Qt.Vertical)
hbox1 = QtWidgets.QWidget()
hbox1.setLayout(top_panel)
splitter.addWidget(hbox1)
splitter.addWidget(image_panel)
box.addWidget(splitter)
# Status bar which is located beneath images.
self.image_status_text = QtWidgets.QStatusBar()
box.addWidget(self.toolbar)
box.addWidget(self.image_status_text)
self.image_status_text.showMessage(
'Status: Please Select a Region and Click \'Save ROI\'. ')
# Connects the buttons.
self.save_ROI_btn.clicked.connect(self.save_roi_fn)
self.save_dots_btn.clicked.connect(self.save_dots_fn)
self.sel_ROI_btn.clicked.connect(self.sel_ROI_btn_fn)
self.delete_ROI_btn.clicked.connect(self.delete_roi_fn)
self.remove_dots_btn.clicked.connect(self.remove_dots_btn_fn)
self.train_model_btn.clicked.connect(self.train_model_btn_fn)
self.count_maxima_btn.clicked.connect(self.count_maxima_btn_fn)
self.load_gt_btn.clicked.connect(self.load_gt_fn)
self.save_gt_btn.clicked.connect(self.save_gt_fn)
self.overlay_prediction_btn.clicked.connect(
self.overlay_prediction_btn_fn)
self.strictness_btn.clicked.connect(self.strictness_btn_fn)
# self.feat_scale_change_btn.clicked.connect(self.feat_scale_change_btn_fn)
self.kernel_show_btn.clicked.connect(self.kernel_btn_fn)
self.clear_dots_btn.clicked.connect(self.clear_dots_fn)
self.save_model_btn.clicked.connect(self.saveForestFn)
self.evaluate_btn.clicked.connect(self.evaluate_forest_fn)
# Initialises the variables for the beginning of the counting.
par_obj.first_time = True
par_obj.dots = []
par_obj.rects = None
par_obj.var = []
par_obj.saved_dots = []
par_obj.saved_ROI = []
#par_obj.subdivide_ROI = []
self.m_Cursor = self.makeCursor()
self.setFocusPolicy(QtCore.Qt.StrongFocus)
def evaluate_forest_fn(self):
# Don't want to train for all the images so we select them.
v2.im_pred_inline_fn_new(par_obj, self, range(
par_obj.max_z+1), [par_obj.curr_t], [par_obj.curr_file], threaded=True)
v2.evaluate_forest_new(par_obj, self, False, 0, range(
par_obj.max_z+1), [par_obj.curr_t], [par_obj.curr_file])
par_obj.show_pts = 0
self.kernel_btn_fn()
print ('evaluating')
self.image_status_text.showMessage('Evaluation complete')
def save_gt_v2(self):
model_name = self.save_model_name_txt.text()
# funky ordering TZCYX
for fileno, imfile in par_obj.filehandlers.iteritems():
rects = [par_obj.saved_ROI[x]
for x, y in enumerate(par_obj.saved_ROI) if y[6] == fileno]
dots = [par_obj.saved_dots[x]
for x, y in enumerate(par_obj.saved_ROI) if y[6] == fileno]
file_to_save = {'dots': dots, 'rect': rects}
fileName = imfile.path+'/'+imfile.name+'_'+model_name+'.quantiROI'
pickle.dump(file_to_save, open(fileName, "wb"))
def save_gt_fn(self):
file_to_save = {'dots': par_obj.saved_dots, 'rect': par_obj.saved_ROI}
fileName = QtWidgets.QFileDialog.getSaveFileName(
self, "Save dots and regions", "~/Documents", ".quantiROI")
print ('the filename address', fileName)
if fileName[-10:] == '.quantiROI':
fileName = fileName[0:-10]
pickle.dump(file_to_save, open(fileName + ".quantiROI", "wb"))
def load_gt_fn(self):
print ('load the gt')
fileName = QtWidgets.QFileDialog.getOpenFileName(
self, "Load dots and regions", "~/Documents", "QuantiFly ROI files (*.quantiROI) ;;MTrackJ Data Format (*.mdf)")
file_ext = os.path.splitext(fileName)[1]
print ('load the file', fileName)
if file_ext == '.quantiROI':
with open(fileName, "rb") as open_file:
the_file = pickle.load(open_file)
par_obj.saved_dots = the_file['dots']
par_obj.saved_ROI = the_file['rect']
self.clear_dots_btn.setEnabled(True)
elif file_ext == '.mdf':
lines_list = list(open(fileName, 'rb').read().split('\n'))
par_obj.saved_ROI = []
par_obj.saved_dots = []
for i in lines_list:
i = i.split(' ')
if len(i) > 0:
if i[0] == 'Point':
# trim point and convert to int
i = [int(float(num)) for num in i[1:-1]]
# order ID x y t z c from mdf
# order in save_dots: txyz
# mdf is 1 indexed
rects = (i[4]-1, 0, 0, int(abs(par_obj.ori_width)),
abs(par_obj.ori_height), i[3]-1, par_obj.curr_file)
# append if dots already in roi, otherwise create roi and append
if rects in par_obj.saved_ROI:
idx = par_obj.saved_ROI.index(rects)
par_obj.saved_dots[idx].append(
(i[4]-1, i[1]-1, i[2]-1))
else:
par_obj.saved_dots.append(
[(i[4]-1, i[1]-1, i[2]-1)])
par_obj.saved_ROI.append(rects)
# check if have loaded points and update
if par_obj.saved_ROI != []:
v2.refresh_all_density(par_obj)
self.train_model_btn.setEnabled(True)
self.goto_img_fn(par_obj.curr_z, par_obj.curr_t)
def load_gt_mdf(self):
fileName = QtWidgets.QFileDialog.getOpenFileName(
self, "Load dots", "~/Documents", "MTrackJ Data Format (*.mdf)")
print ('load the file', fileName)
lines_list = list(open(fileName, 'rb').read().split('\n'))
for i in lines_list:
i = i.split(' ')
if len(i) > 0:
if i[0] == 'Point':
# trim point and convert to int
i = [int(float(num)) for num in i[1:-1]]
# order ID x y t z c from mdf
# order in save_dots: txyz
# mdf is 1 indexed
rects = (i[4]-1, 0, 0, int(abs(par_obj.ori_width)),
abs(par_obj.ori_height), i[3]-1, par_obj.curr_file)
# append if dots already in roi, otherwise create roi and append
if rects in par_obj.saved_ROI:
idx = par_obj.saved_ROI.index(rects)
par_obj.saved_dots[idx].append(
(i[4]-1, i[1]-1, i[2]-1))
else:
par_obj.saved_dots.append([(i[4]-1, i[1]-1, i[2]-1)])
par_obj.saved_ROI.append(rects)
def overlay_prediction_btn_fn(self):
par_obj.overlay = not par_obj.overlay
self.goto_img_fn(par_obj.curr_z, par_obj.curr_t)
def strictness_btn_fn(self):
par_obj.count_maxima_laplace = not par_obj.count_maxima_laplace
def count_maxima_btn_fn(self):
t0 = time.time()
par_obj.max_det = []
par_obj.min_distance = [float(self.count_txt_1.text()), float(
self.count_txt_2.text()), float(self.count_txt_3.text())]
par_obj.abs_thr = float(self.abs_thr_txt.text())/100
#par_obj.z_cal =float(self.z_cal_txt.text())
count_maxima(par_obj, par_obj.curr_t,
par_obj.curr_file, reset_max=True)
par_obj.show_pts = 1
self.kernel_btn_fn()
def report_progress(self, message):
self.image_status_text.showMessage('Status: ' + message)
app.processEvents()
def loadTrainFn(self):
# Win_fn()
channel_wid = QtWidgets.QWidget()
channel_lay = QtWidgets.QHBoxLayout()
channel_wid.setLayout(channel_lay)
win.top_left_grid.addWidget(channel_wid, 1, 0, 1, 3)
# cleanup if reloading image
if not hasattr(self, 'ChannelGroup'):
# define channel brightness controls
self.ChannelGroup = []
for itemset in self.ChannelGroup:
for item in itemset: