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v2_batch.py
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#Script for running evaluation mode
#import pylab
from PyQt4 import QtGui, QtCore, Qt, QtWebKit
try:
from PyQt4.QtCore import QString as QString
except:
QString=str
import time
#import vigra
#import scipy
#from scipy.ndimage import filters
from scipy.sparse.csgraph import _validation
#from sklearn.ensemble import ExtraTreesRegressor
#import thread
#import random
import csv
import cPickle as pickle
import datetime
#import errno
import os
import numpy as np
import copy
import datetime
#import functools
#from scipy.special import _ufuncs_cxx
#import sklearn.utils.lgamma
#from gnu import return_license
#from matplotlib.path import Path
import pdb
from common_navigation import navigation_setup,create_channel_objects,btn_fn
from parameter_object import ParameterClass
from File_handler import Intermediate_handler
from user_ROI import ROI
import functools
from multiprocessing.dummy import Pool as ThreadPool
#Apparently matplotlib slows the loading drammatically due to a font cache issue. This resolves it.
try:
#mac location.
os.remove(os.path.expanduser('~')+'/.matplotlib/fontList.cache')
print 'removing matplotlib cache'
except:
pass
try:
#Alternate location.
os.remove(os.path.expanduser('~')+'/.cache/matplotlib')
print 'removing matplotlib cache'
except:
pass
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
import v2_batch_functions as v2
"""QBrain 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.
"""
class Eval_load_im_win(QtGui.QWidget):
def __init__(self,par_obj):
super(Eval_load_im_win, self).__init__()
"""Setups the load image interface"""
#Stops reinitalise of text which can produce buggy text.
#if par_obj.evalLoadImWin_loaded !=True:
vbox0 = QtGui.QVBoxLayout()
self.setLayout(vbox0)
#Load images button
self.loadImages_button_panel = QtGui.QHBoxLayout()
self.loadImages_button = QtGui.QPushButton("Add Images")
self.loadImages_button.move(20, 20)
self.loadImages_button_panel.addWidget(self.loadImages_button)
self.loadImages_button_panel.addStretch()
about_btn = QtGui.QPushButton('About')
about_btn.clicked.connect(lambda: on_about(self))
self.loadImages_button_panel.addWidget(about_btn)
#Table widget which displays
self.modelTabIm_panel = QtGui.QHBoxLayout()
self.modelTabIm = QtGui.QTableWidget()
self.modelTabIm.setRowCount(1)
self.modelTabIm.setColumnCount(4)
self.modelTabIm.setColumnWidth(0,125)
self.modelTabIm.resize(550,200)
self.modelTabIm.setHorizontalHeaderLabels(QString(",Image name, Range, Path").split(","))
self.modelTabIm.hide()
self.modelTabIm.setEditTriggers( QtGui.QTableWidget.NoEditTriggers )
self.modelTabIm_panel.addWidget(self.modelTabIm)
self.modelTabIm_panel.addStretch()
#Starts file dialog calss
self.imLoad = File_Dialog(par_obj,self,self.modelTabIm)
self.imLoad.type = 'im'
self.loadImages_button.clicked.connect(self.imLoad.showDialog)
vbox0.addLayout(self.loadImages_button_panel)
vbox0.addLayout(self.modelTabIm_panel)
vbox0.addStretch()
#Move to training button.
self.selIntButton_panel = QtGui.QHBoxLayout()
self.selIntButton = QtGui.QPushButton("Goto Model Import")
self.selIntButton.clicked.connect(self.goto_model_import)
self.selIntButton.move(20, 520)
self.selIntButton.setEnabled(False)
self.selIntButton_panel.addWidget(self.selIntButton)
self.selIntButton_panel.addStretch()
vbox0.addLayout(self.selIntButton_panel)
#Status bar to report whats going on.
self.image_status_text = QtGui.QStatusBar()
self.image_status_text.showMessage('Status: Highlight training images in folder. ')
vbox0.addWidget(self.image_status_text)
def goto_model_import(self):
win_tab.setCurrentWidget(evalLoadModelWin)
#Checks the correct things are disabled.
evalLoadModelWin.gotoEvalButton.setEnabled(False)
evalImWin.prev_im_btn.setEnabled(False)
evalImWin.next_im_btn.setEnabled(False)
evalImWin.eval_im_btn.setEnabled(False)
par_obj.eval_load_im_win_eval = False
class Eval_load_model_win(QtGui.QWidget):
"""Interface which allows selection of model."""
def __init__(self,par_obj):
super(Eval_load_model_win,self).__init__()
#The main layout
box = QtGui.QVBoxLayout()
self.setLayout(box)
hbox0 = QtGui.QHBoxLayout()
box.addLayout(hbox0)
#The two principle columns
vbox0 = QtGui.QVBoxLayout()
vbox1 = QtGui.QVBoxLayout()
hbox0.addLayout(vbox0)
hbox0.addLayout(vbox1)
self.modelTabFor = QtGui.QTableWidget()
self.modelTabFor.setRowCount(1)
self.modelTabFor.setColumnCount(3)
self.modelTabFor.setColumnWidth(2,200)
self.modelTabFor.resize(600,500)
self.modelTabFor.setHorizontalHeaderLabels(QString(",model name, date and time saved").split(","))
self.modelTabFor.setEditTriggers( QtGui.QTableWidget.NoEditTriggers )
vbox0.addWidget(self.modelTabFor)
#Button for going to model evaluation.
self.gotoEvalButton = QtGui.QPushButton("Goto Image Evaluation")
self.gotoEvalButton.setEnabled(False)
self.gotoEvalButton.clicked.connect(self.gotoEvalButton_fn)
vbox0.addWidget(self.gotoEvalButton)
#Status text.
self.image_status_text = QtGui.QStatusBar()
self.image_status_text.resize(300,20)
self.image_status_text.setStyleSheet("QLabel { color : green }")
self.image_status_text.showMessage('Status: Please click a model from above and then click \'Load Model\'. ')
#The second column.
self.modelIm_panel = QtGui.QHBoxLayout()
self.figure1 = Figure(figsize=(3, 3), dpi=100)
self.canvas1 = FigureCanvas(self.figure1)
self.figure1.patch.set_facecolor('grey')
self.plt1 = self.figure1.add_subplot(1, 1, 1)
im_RGB = np.zeros((300, 300))
#Makes sure it spans the whole figure.
self.figure1.subplots_adjust(left=0.001, right=0.999, top=0.999, bottom=0.001)
self.plt1.imshow(im_RGB)
#Removes the tick labels
self.plt1.set_xticklabels([])
self.plt1.set_yticklabels([])
vbox1.addWidget(self.canvas1)
self.modelImTxt1_panel = QtGui.QHBoxLayout()
self.modelImTxt2_panel = QtGui.QHBoxLayout()
self.modelImTxt3_panel = QtGui.QHBoxLayout()
self.modelImTxt4_panel = QtGui.QHBoxLayout()
self.modelImTxt5_panel = QtGui.QHBoxLayout()
self.modelImTxt6_panel = QtGui.QHBoxLayout()
self.modelImTxt1 = QtGui.QLabel()
self.modelImTxt2 = QtGui.QLabel()
self.modelImTxt3 = QtGui.QLabel()
self.modelImTxt4 = QtGui.QLabel()
self.modelImTxt5 = QtGui.QLabel()
self.modelImTxt6 = QtGui.QLabel()
self.modelImTxt1.setText('Name: ')
self.modelImTxt1.resize(400,25)
self.modelImTxt1_panel.addWidget(self.modelImTxt1)
self.modelImTxt1_panel.addStretch()
self.modelImTxt2.setText('Description: ')
self.modelImTxt2.resize(400,25)
self.modelImTxt2_panel.addWidget(self.modelImTxt2)
self.modelImTxt2_panel.addStretch()
self.modelImTxt3.setText('Sigma Data: ')
self.modelImTxt3.resize(400,25)
self.modelImTxt3_panel.addWidget(self.modelImTxt3)
self.modelImTxt3_panel.addStretch()
self.modelImTxt4.setText('Feature Scale: ')
self.modelImTxt4.resize(400,25)
self.modelImTxt4_panel.addWidget(self.modelImTxt4)
self.modelImTxt4_panel.addStretch()
self.modelImTxt5.setText('Feature Type: ')
self.modelImTxt5.resize(400,25)
self.modelImTxt5_panel.addWidget(self.modelImTxt5)
self.modelImTxt5_panel.addStretch()
self.modelImTxt6.setText('Channels: ')
self.modelImTxt6.resize(400,25)
self.modelImTxt6_panel.addWidget(self.modelImTxt6)
self.modelImTxt6_panel.addStretch()
vbox1.addLayout(self.modelImTxt1_panel)
vbox1.addLayout(self.modelImTxt2_panel)
vbox1.addLayout(self.modelImTxt3_panel)
vbox1.addLayout(self.modelImTxt4_panel)
vbox1.addLayout(self.modelImTxt5_panel)
vbox1.addLayout(self.modelImTxt6_panel)
vbox1.addStretch()
self.makeTable()
box.addWidget(self.image_status_text)
def makeTable(self):
#Display available models.
#Find all files in folder with serielize prefix.
files = os.listdir(par_obj.forPath)
filesRF =[]
for b in range(0,files.__len__()):
if(os.path.splitext(files[b])[1] == '.pkl'):
filesRF.append(os.path.splitext(files[b])[0] )
if(os.path.splitext(files[b])[1] == '.mdla'):
filesRF.append(os.path.splitext(files[b])[0] )
filesLen = filesRF.__len__()
c =0
for i in range(filesLen):
strFn = filesRF[i].split('_')
if(str(strFn[0]) == 'pv1.3'):
self.modelTabFor.setRowCount(c+1)
btn = loadModelBtn(par_obj,self,self.modelTabFor,i,filesRF[i])
btn.setText('Click to View')
self.modelTabFor.setCellWidget(c, 0, btn)
text1 = QtGui.QLabel(self.modelTabFor)
text1.setText(str(' '+strFn[1]))
self.modelTabFor.setCellWidget(c,1,text1)
text2 = QtGui.QLabel(self.modelTabFor)
text2.setText(str(' '+strFn[2]))
self.modelTabFor.setCellWidget(c,2,text2)
c= c+1
if str(strFn[0]) == 'pv20':
self.modelTabFor.setRowCount(c+1)
btn = loadModelBtn(par_obj,self,self.modelTabFor,i,filesRF[i])
btn.setText('Click to View')
self.modelTabFor.setCellWidget(c, 0, btn)
text1 = QtGui.QLabel(self.modelTabFor)
text1.setText(str(' '+strFn[2]))
self.modelTabFor.setCellWidget(c,1,text1)
text2 = QtGui.QLabel(self.modelTabFor)
text2.setText(str(' '+datetime.datetime.fromtimestamp(float(strFn[1])).strftime('%Y-%m-%d %H:%M:%S')))
self.modelTabFor.setCellWidget(c,2,text2)
c= c+1
def loadModelFn(self,par_obj, fileName):
"""Shows details of the model when loaded"""
par_obj.selectedModel = par_obj.forPath+fileName
par_obj.evaluated = False
self.image_status_text.showMessage('Status: Loading previously trained model. ')
app.processEvents()
ver = par_obj.selectedModel.split('/')[-1][0:5]
if(ver =='pv20_'):
save_file = pickle.load(open(par_obj.selectedModel+str('.mdla'), "rb"))
print(par_obj.selectedModel+str('.mdla'))
par_obj.modelName = save_file["name"]
par_obj.modelDescription = save_file["description"]
par_obj.RF = save_file["model"]
local_time = save_file["date"]
par_obj.M = save_file["M"]
par_obj.c = save_file["c"]
par_obj.feature_type = save_file["feature_type"]
par_obj.feature_scale = save_file["feature_scale"]
par_obj.sigma_data = save_file["sigma_data"]
par_obj.ch_active = save_file["ch_active"]
par_obj.limit_ratio_size = save_file["limit_ratio_size"]
par_obj.max_depth = save_file["max_depth"]
par_obj.min_samples_split = save_file["min_samples"]
par_obj.min_samples_leaf = save_file["min_samples_leaf"]
par_obj.max_features = save_file["max_features"]
par_obj.num_of_tree = save_file["num_of_tree"]
par_obj.resize_factor = save_file["resize_factor"]
par_obj.min_distance = save_file["min_distance"]
par_obj.abs_thr = save_file["abs_thr"]
par_obj.rel_thr = save_file["rel_thr"]
#par_obj.gt_vec = save_file["gt_vec"]
#par_obj.error_vec = save_file["error_vec"]
save_im = save_file["imFile"]
self.image_status_text.showMessage('Status: Model loaded. ')
success = True
#Some basic image checking.
if par_obj.filehandlers[0].numCH!=par_obj.numCH <par_obj.ch_active.__len__():
success = False
self.image_status_text.showMessage('Status: Model is incompatible. There were more channels in the original images on which the training was performed than in the loaded images. ')
if(ver =='pv1.3'):
#Load in parameters from file.
par_obj.file_ext,par_obj.RF,par_obj.sigma_data,par_obj.feature_scale,par_obj.feature_type,par_obj.ch_active,par_obj.modelName,par_obj.modelDescription = pickle.load(open(par_obj.selectedModel+str('.pkl'), "rb"))
#save_im =cv2.imread(par_obj.selectedModel+"im.png")
self.image_status_text.showMessage('Status: Model loaded. ')
#Display details about model.
success, statusText = v2.import_data_fn(par_obj,par_obj.file_array)
if success == True:
self.modelImTxt1.setText('Name: '+str(par_obj.modelName))
self.modelImTxt2.setText('Description: '+str(par_obj.modelDescription ))
self.modelImTxt3.setText('Sigma Data: '+str(par_obj.sigma_data))
self.modelImTxt4.setText('Feature Scale: '+str(par_obj.feature_scale))
self.modelImTxt5.setText('Feature Type: '+str(par_obj.feature_type))
self.modelImTxt6.setText('Channels: '+str(par_obj.ch_active))
self.plt1.imshow(save_im/np.max(save_im))
self.canvas1.draw()
self.gotoEvalButton.setEnabled(True)
evalImWin.eval_im_btn.setEnabled(True)
par_obj.eval_load_im_win_eval = False
def gotoEvalButton_fn(self):
#for i in range(par_obj.file_array.__len__()):
# par_obj.frames_2_load = range(0,par_obj.max_z) #TODO make max_zslices a list
# if par_obj.total_time_pt==[]:
# par_obj.total_time_pt=1
par_obj.tpt_list = range(0,par_obj.max_t+1) #TODO make sure this matches up and don't have a +1 error
par_obj.user_min_z=0
v2.setup_parameters(self,par_obj)
par_obj.eval_load_im_win_eval = False
win_tab.setCurrentWidget(evalImWin)
evalImWin.prev_im_btn.setEnabled(True)
evalImWin.next_im_btn.setEnabled(True)
#Now that we have correct resize factor from the model import.
v2.import_data_fn(par_obj,par_obj.file_array)
evalImWin.loadTrainFn()
v2.load_and_initiate_plots(par_obj, evalImWin)
class Eval_disp_im_win(QtGui.QWidget):
""" Arranges widget to visualise the input images and ouput prediction. """
def __init__(self,par_obj):
super(Eval_disp_im_win, self).__init__()
#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')
toolbar = NavigationToolbar(self.canvas1,self)
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.plt1.imshow(im_RGB)
#Removes the tick labels
self.plt1.set_xticklabels([])
self.plt1.set_yticklabels([])
self.cursor = ROI(self,par_obj)
#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 #for avoiding unecessary refresh
#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 = QtGui.QLabel()
self.image_num_txt = QtGui.QLabel()
box = QtGui.QVBoxLayout()
self.setLayout(box)
#Widget containing the top panel.
top_panel = QtGui.QHBoxLayout()
#Top left and right widget panels
top_left_panel = QtGui.QGroupBox('Basic Controls')
top_middle_panel = QtGui.QGroupBox('ROI Controls')
top_right_panel = QtGui.QGroupBox('Advanced Controls')
#Grid layouts for the top and left panels.
self.top_left_grid = QtGui.QGridLayout()
self.top_right_grid = QtGui.QGridLayout()
self.top_left_grid.setSpacing(2)
self.top_right_grid.setSpacing(1)
#Widgets for the top panel.
top_panel.addWidget(top_left_panel)
top_panel.addWidget(top_middle_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)
#common navigation elements
self.Btn_fns = btn_fn(self)
navigation_setup(self,par_obj)
#Sets the current text.
self.image_num_txt.setText('The Current Image is: ' + str(par_obj.curr_z +1)+' and the time point is: '+str(par_obj.curr_t +1))
self.count_txt = QtGui.QLabel()
#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)
top_right_panel.setLayout(self.top_right_grid)
self.eval_im_btn = QtGui.QPushButton('Evaluate Images')
self.eval_im_btn.clicked.connect(self.evaluate_images)
self.count_all_btn = QtGui.QPushButton('Re-Count Maxima')
self.count_all_btn.clicked.connect(self.count_all_fn)
self.toggle_display_btn = QtGui.QPushButton('Show Probability/Maxima')
self.toggle_display_btn.clicked.connect(self.kernel_btn_fn)
self.save_output_data_btn = QtGui.QPushButton('Save Output Data')
self.save_output_data_btn.clicked.connect(self.save_output_data)
self.save_output_prediction_btn = QtGui.QPushButton('Save Prediction')
self.save_output_prediction_btn.clicked.connect(self.save_output_prediction)
self.save_output_mask_btn = QtGui.QPushButton('Save Point Mask')
self.save_output_mask_btn.clicked.connect(self.save_output_mask)
self.save_output_link = QtGui.QLabel()
self.save_output_link.setText('''<p><a href="'''+str(par_obj.csvPath)+'''">Goto output folder</a></p>
<p><span style="font-size: 17px;"><br /></span></p>''')
self.kernel_show_btn = QtGui.QPushButton('Showing Prediction')
#self.kernel_show_btn.setMinimumWidth(170)
self.top_right_grid.addWidget(self.kernel_show_btn, 1, 1)
#Populates the grid on the right with the different widgets.
self.top_right_grid.addWidget(self.eval_im_btn, 0, 0)
self.top_right_grid.addWidget(self.save_output_data_btn, 1, 0)
self.top_right_grid.addWidget(self.save_output_prediction_btn,1,1)
self.top_right_grid.addWidget(self.save_output_mask_btn,0,1)
self.top_right_grid.addWidget(self.count_all_btn, 3,1)
self.top_right_grid.addWidget(self.toggle_display_btn, 2,0)
self.top_right_grid.addWidget(self.output_count_txt,2,1,1,4)
#self.top_right_grid.addWidget(self.save_output_link, 2, 0)
self.count_maxima_btn = QtGui.QPushButton('Count Maxima')
self.count_maxima_btn.setEnabled(False)
self.top_right_grid.addWidget(self.count_maxima_btn, 2, 1)
self.count_maxima_btn.clicked.connect(self.count_maxima_btn_fn)
self.kernel_show_btn.clicked.connect(self.kernel_btn_fn)
self.count_replot_btn = QtGui.QPushButton('Replot')
self.count_replot_btn_all = QtGui.QPushButton('Replot All')
self.count_txt_1 = QtGui.QLineEdit(str(par_obj.min_distance[0]))
self.count_txt_1.setFixedWidth(20)
self.count_txt_2 = QtGui.QLineEdit(str(par_obj.min_distance[1]))
self.count_txt_2.setFixedWidth(20)
self.count_txt_3 = QtGui.QLineEdit(str(par_obj.min_distance[2]))
self.count_txt_3.setFixedWidth(20)
abs_thr_lbl = QtGui.QLabel('Abs Thr:')
self.abs_thr_txt = QtGui.QLineEdit(str(par_obj.abs_thr*100))
self.abs_thr_txt.setFixedWidth(25)
rel_thr_lbl = QtGui.QLabel('Rel Thr:')
self.rel_thr_txt = QtGui.QLineEdit(str(par_obj.rel_thr))
self.rel_thr_txt.setFixedWidth(25)
self.min_distance_panel = QtGui.QHBoxLayout()
self.min_distance_panel.addWidget(QtGui.QLabel("x:"))
self.min_distance_panel.addWidget(self.count_txt_1)
self.min_distance_panel.addWidget(QtGui.QLabel("y:"))
self.min_distance_panel.addWidget(self.count_txt_2 )
self.min_distance_panel.addWidget(QtGui.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(rel_thr_lbl)
self.min_distance_panel.addWidget(self.rel_thr_txt)
self.min_distance_panel.addStretch()
self.top_right_grid.addLayout(self.min_distance_panel,3,0)
#self.top_right_grid.addWidget(self.count_replot_btn_all,0,1)
#self.top_right_grid.addWidget(self.count_replot_btn,1,1)
self.top_right_grid.setRowStretch(3,2)
#self.top_panel = QtGui.QHBoxLayout()
self.activate_roi_btn = QtGui.QPushButton('Toggle ROI tool')
self.activate_roi_btn.clicked.connect(self.activate_roi_btn_fn)
self.compl_btn = QtGui.QPushButton('Save ROI')
self.compl_btn.clicked.connect(self.cursor.complete_roi)
self.clear_btn = QtGui.QPushButton('Clear ROI')
self.clear_btn.clicked.connect(self.cursor.clear_ROI)
self.interpolate_btn = QtGui.QPushButton('Interpolate (z)')
self.interpolate_btn.clicked.connect(self.interpolate_roi_fn)
self.interpolate_time_btn = QtGui.QPushButton('Interpolate (t)')
self.interpolate_time_btn.clicked.connect(self.interpolate_roi_in_time_fn)
roi_panel = QtGui.QVBoxLayout()
roi_panel.addWidget(self.activate_roi_btn)
roi_panel.addWidget(self.compl_btn)
roi_panel.addWidget(self.clear_btn)
roi_panel.addWidget(self.interpolate_btn)
roi_panel.addWidget(self.interpolate_time_btn)
roi_panel.addStretch()
top_middle_panel.setLayout(roi_panel)
#Sets up the image panel splitter.
image_panel = QtGui.QSplitter(QtCore.Qt.Horizontal)
image_panel.addWidget(self.canvas1)
image_panel.addWidget(self.canvas2)
#Splitter which separates the controls at the top and the images below.
splitter = QtGui.QSplitter(QtCore.Qt.Vertical)
hbox1 = QtGui.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 = QtGui.QStatusBar()
box.addWidget(toolbar)
box.addWidget(self.image_status_text)
self.image_status_text.showMessage('Status: Please Select a Region and Click \'Save ROI\'. ')
self.modelLoadedText = QtGui.QLabel(self)
self.imageNumText = QtGui.QLabel(self)
self.evalStatusText = QtGui.QLabel(self)
self.canvas1.mpl_connect('motion_notify_event', self.cursor.motion_notify_callback)
self.canvas1.mpl_connect('button_press_event', self.cursor.button_press_callback)
self.canvas1.mpl_connect('button_release_event', self.cursor.button_release_callback)
self.canvas1.mpl_connect('key_press_event', self.on_key)
self.setFocusPolicy(QtCore.Qt.StrongFocus)
def on_key(self,event):
if event.key==' ':
pass
elif event.key == '.':
self.Btn_fns.next_file(par_obj)
elif event.key == ',':
self.Btn_fns.prev_file(par_obj)
elif event.key == "up":
self.Btn_fns.next_im(par_obj)
elif event.key == "down":
self.Btn_fns.prev_im(par_obj)
elif event.key == "left":
self.Btn_fns.prev_time(par_obj)
elif event.key == "right":
self.Btn_fns.next_time(par_obj)
def keyPressEvent(self, ev):
"""When the . and , keys are pressed"""
if ev.key() == QtCore.Qt.Key_Period:
self.Btn_fns.next_file(par_obj)
elif ev.key() == QtCore.Qt.Key_Comma:
self.Btn_fns.prev_file(par_obj)
elif ev.key() == QtCore.Qt.Key_Up:
self.Btn_fns.next_im(par_obj)
elif ev.key() == QtCore.Qt.Key_Down:
self.Btn_fns.prev_im(par_obj)
elif ev.key() == QtCore.Qt.Key_Left:
self.Btn_fns.prev_time(par_obj)
elif ev.key() == QtCore.Qt.Key_Right:
self.Btn_fns.next_time(par_obj)
def activate_roi_btn_fn(self):
self.cursor.roi_active = not self.cursor.roi_active
def interpolate_roi_fn(self):
self.cursor.interpolate_ROI()
self.goto_img_fn()
def interpolate_roi_in_time_fn(self):
self.cursor.interpolate_ROI_in_time()
self.goto_img_fn()
def count_all_fn(self):
#iterates over t and files to count maxima
#TODO: make threaded
par_obj.data.hessians = []
for fileno in range(par_obj.max_file):
imfile=par_obj.filehandlers[fileno]
par_obj.data.hessians.append(Intermediate_handler(imfile.full_name+'Hessians.tif'))
for tpt in range(imfile.max_t+1):
self.report_progress('Calculating Maxima for File:'+str(fileno+1)+ ' Timepoint: '+str(tpt+1) +' All Z')
v2.count_maxima(par_obj,tpt,fileno)
par_obj.show_pts = 1
self.kernel_btn_fn()
self.report_progress('Maxima calculated. Save output data or change maxima parameters.')
def kernel_btn_fn(self):
"""Shows the kernels on the image."""
par_obj.show_pts = par_obj.show_pts+ 1
if par_obj.show_pts ==3:
par_obj.show_pts = 1
if par_obj.show_pts == 1:
self.kernel_show_btn.setText('Showing Probability')
#self.goto_img_fn(par_obj.curr_z,par_obj)
self.goto_img_fn()
#v2.goto_img_fn(par_obj, int_obj,par_obj.curr_z,par_obj.time_pt)
#v2.eval_goto_img_fn(par_obj.curr_z,par_obj,self) ###needs correcting??###
elif par_obj.show_pts == 2:
self.kernel_show_btn.setText('Showing Counts')
#self.goto_img_fn(par_obj.curr_z,par_obj)
self.goto_img_fn()
#v2.goto_img_fn(par_obj, int_obj,par_obj.curr_z,par_obj.time_pt)
#v2.eval_goto_img_fn(par_obj.curr_z,par_obj,self)
def count_maxima_btn_fn(self):
par_obj.min_distance[0]= float(self.count_txt_1.text())
par_obj.min_distance[1]= float(self.count_txt_2.text())
par_obj.min_distance[2]= float(self.count_txt_3.text())
par_obj.abs_thr =float(self.abs_thr_txt.text())/100
par_obj.rel_thr =float(self.rel_thr_txt.text())
par_obj.data.hessians = []
par_obj.data.hessians.append(Intermediate_handler(par_obj.filehandlers[par_obj.curr_file].full_name+'Hessians.tif'))
v2.count_maxima(par_obj,par_obj.curr_t,par_obj.curr_file)
par_obj.show_pts= 1
self.kernel_btn_fn()
#v2.eval_pred_show_fn(par_obj.curr_z, par_obj,self)
#self.goto_img_fn(par_obj.curr_z,par_obj)
#self.goto_img_fn(par_obj.curr_z,par_obj.time_pt)
return
def evaluate_images(self):
par_obj.data.predictions = []
par_obj.data.hessians = []
par_obj.maxPred = 0 #resets scaling for display between models
par_obj.minPred = 100
for fileno,imfile in par_obj.filehandlers.iteritems():
par_obj.data.predictions.append(Intermediate_handler(imfile.full_name+'Predictions.tif'))
with par_obj.data.predictions[fileno].writer() as predwriter:
for tpt in range(imfile.max_t+1):
#pool = ThreadPool(8)
#pool.map(functools.partial(v2.calculate_feat_and_predict,par_obj, tpt, fileno, 0, predwriter,), range(imfile.max_z+1))
for z in range(imfile.max_z+1):
v2.calculate_feat_and_predict(par_obj, tpt, fileno, 0, predwriter,z)
app.processEvents()
time.sleep(0.001)
#pool.close()
#pool.join()
par_obj.data.hessians.append(Intermediate_handler(imfile.full_name+'Hessians.tif'))
for tpt in range(imfile.max_t+1):
v2.count_maxima(par_obj,tpt,fileno)
app.processEvents()
time.sleep(0.001)
self.show_pts = 2
self.count_maxima_btn.setEnabled(True)
self.count_all_btn.setEnabled(True)
self.save_output_data_btn.setEnabled(True)
self.save_output_prediction_btn.setEnabled(True)
self.save_output_mask_btn.setEnabled(True)
self.image_status_text.showMessage('Status: evaluation finished.')
def evaluate_images_old(self):
#par_obj.double_feat_arr = {}
#par_obj.feat_arr = {}
#par_obj.pred_arr = {}
par_obj.sum_pred = {}
'''
for fileno in range(par_obj.max_file):
for tpt in par_obj.tpt_list:
count = -1
frames =par_obj.frames_2_load
#try to make it threadable
#v2.im_pred_inline_fn_eval(par_obj, self,outer_loop=b,inner_loop=frames,threaded=True)
v2.im_pred_inline_fn_new(par_obj, self,frames,[tpt],[fileno],True)
for i in frames:
#v2.im_pred_inline_fn(par_obj, self,inline=True,outer_loop=b,inner_loop=frames,count=count)
#v2.evaluate_forest(par_obj,self, False, 0,inline=True,outer_loop=b,inner_loop=i,count=count)
v2.evaluate_forest_new(par_obj,self,False,0,[i],[tpt],[fileno],False)
count = count+1
par_obj.data_store['feat_arr'][fileno][tpt] = {}
v2.count_maxima(par_obj,tpt,fileno)
time.sleep(0.001)
'''
par_obj.data.predictions = []
par_obj.data.hessians = []
for fileno,imfile in par_obj.filehandlers.iteritems():
par_obj.data.predictions.append(Intermediate_handler(imfile.full_name+'Predictions.tif'))
par_obj.data.hessians.append(Intermediate_handler(imfile.full_name+'Hessians.tif'))
for tpt in range(imfile.max_t+1):
frames = range(imfile.max_z+1)
#try to make it threadable
#v2.im_pred_inline_fn_eval(par_obj, self,outer_loop=b,inner_loop=frames,threaded=True)
#TODO rework to put threading on outside
v2.im_pred_inline_fn_new(par_obj, self,frames,[tpt],[fileno],True)
for i in frames:
v2.evaluate_forest_new(par_obj,self,False,0,[i],[tpt],[fileno])
if par_obj.double_train==True:
v2.im_pred_inline_fn_new(par_obj, self,frames,[tpt],[fileno],threaded='auto')
par_obj.data_store['feat_arr'][fileno][tpt] = {}
for i in frames:
v2.evaluate_forest_new(par_obj,self,False,1,[i],[tpt],[fileno],False,arr='double_feat_arr')
par_obj.data_store['double_feat_arr'][fileno][tpt] = {}
else:
par_obj.data_store['feat_arr'][fileno][tpt] = {}
for tpt in range(imfile.max_t+1):
frames = range(imfile.max_z+1)
v2.count_maxima(par_obj,tpt,fileno)
time.sleep(0.001)
#set count maxima parameters from model
self.count_txt_1.setText(str(par_obj.min_distance[0]))
self.count_txt_2.setText(str(par_obj.min_distance[1]))
self.count_txt_3.setText(str(par_obj.min_distance[2]))
self.abs_thr_txt.setText(str(par_obj.abs_thr))
self.rel_thr_txt.setText(str(par_obj.rel_thr))
self.count_maxima_btn.setEnabled(True)
self.count_all_btn.setEnabled(True)
self.save_output_data_btn.setEnabled(True)
self.save_output_prediction_btn.setEnabled(True)
self.save_output_mask_btn.setEnabled(True)
self.image_status_text.showMessage('Status: evaluation finished.')
par_obj.eval_load_im_win_eval = True
par_obj.curr_t= 0
#TODO check why this is not using the local version of goto_img
par_obj.show_pts=1
#v2.goto_img_fn_new(par_obj, self)
self.goto_img_fn()
#v2.eval_pred_show_fn(par_obj,self,par_obj.curr_z,par_obj.time_pt)
def save_output_data(self):
v2.save_output_data_fn(par_obj,self)
def save_output_prediction(self):
v2.save_output_prediction_fn(par_obj,self)
def save_output_mask(self):
v2.save_output_mask_fn(par_obj,self)
def report_progress(self,message):
self.image_status_text.showMessage('Status: ' + message)
app.processEvents()
def draw_saved_dots_and_roi(self):
pass
def loadTrainFn(self):
#Win_fn()
try:
del self.channel_wid
except:
pass
channel_wid = QtGui.QWidget()
channel_lay = QtGui.QHBoxLayout()
ChannelGroup = create_channel_objects(self,par_obj,par_obj.numCH)
for chbx, contrast, brightness in ChannelGroup:
channel_lay.addWidget(chbx)
channel_lay.addWidget(contrast)
channel_lay.addWidget(brightness)
contrast.show()
chbx.show()
chbx.setChecked(True)
channel_lay.addStretch()
channel_wid.setLayout(channel_lay)
self.channel_wid = channel_wid
self.top_left_grid.setMargin(0)
self.top_left_grid.addWidget(channel_wid,1,0,1,3)
def goto_img_fn(self,zslice=None,tpt=None,imno=None):
if zslice!=None:
par_obj.curr_z=zslice
if tpt!=None:
par_obj.curr_t =tpt
if imno!=None:
par_obj.curr_file=imno
self.cursor.ppt_x = []
self.cursor.ppt_y = []
self.cursor.line = [None]
#self.cursor.draw_ROI()
#self.canvas1.draw()
self.cursor.complete = False
self.cursor.flag = False
try: #TODO not really sure what went wrong here, fix later
for bt in par_obj.data_store['roi_stk_x'][imno][tpt]:
if bt == zslice:
self.cursor.complete = True
self.cursor.ppt_x = copy.deepcopy(par_obj.data_store['roi_stk_x'][imno][tpt][bt])
self.cursor.ppt_y = copy.deepcopy(par_obj.data_store['roi_stk_y'][imno][tpt][bt])
break;
except KeyError:
pass
#v2.eval_goto_img_fn(im_num,par_obj,self)
v2.goto_img_fn_new(par_obj, self)
class checkBoxCH(QtGui.QCheckBox):
def __init__(self):
QtGui.QCheckBox.__init__(self)
self.stateChanged.connect(self.stateChange)
self.type = None;
def stateChange(self):
if self.type == 'visual_ch':
#v2.eval_goto_img_fn(par_obj.curr_z,par_obj,evalImWin)
Eval_disp_im_win.goto_img_fn(evalImWin)
class File_Dialog(QtGui.QMainWindow):
def __init__(self,par_obj,int_obj,modelTabObj):
super(File_Dialog, self).__init__()
self.int_obj = int_obj
self.par_obj = par_obj
self.type = 'im'
self.modelTabObj = modelTabObj
self.initUI()
def initUI(self):
self.textEdit = QtGui.QTextEdit()
self.setCentralWidget(self.textEdit)
self.statusBar()
openFile = QtGui.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')
self.par_obj.config ={}
try:
self.par_obj.config = pickle.load(open(os.path.expanduser('~')+'/.densitycount/config.p', "rb" ));
self.par_obj.filepath = self.par_obj.config['evalpath']
except:
self.par_obj.filepath = os.path.expanduser('~')+'/'
#self.show()
def showDialog(self):
self.int_obj.selIntButton.setEnabled(False)
#filepath = QtGui.QFileDialog.getOpenFileName(self, 'Open file', '/home')
par_obj.file_array =[]
for path in QtGui.QFileDialog.getOpenFileNames(self, 'Open file', self.par_obj.filepath,'Images(*.tif *.tiff);;'):
par_obj.file_array.append(path)
if len(par_obj.file_array)>0:
self.par_obj.config['evalpath'] = str(QtCore.QFileInfo(path).absolutePath())+'/'
pickle.dump(self.par_obj.config, open(str(os.path.expanduser('~')+'/.densitycount/config.p'), "w" ))
self.par_obj.csvPath = self.par_obj.config['evalpath']
v2.import_data_fn(par_obj,par_obj.file_array)
self.int_obj.image_status_text.showMessage('Status: Loading Images. ')
if self.type == 'im':
if(self.par_obj.file_array.__len__()>0):
self.int_obj.selIntButton.setEnabled(True)
self.refreshTable()
def refreshTable(self):
self.int_obj.image_status_text.showMessage(str(self.par_obj.file_array.__len__())+' Files Selected.')
filesLen =self.par_obj.file_array.__len__()
self.modelTabObj.show()
c = 0
for i in range(0,self.par_obj.file_array.__len__()):
self.modelTabObj.setRowCount(c+1)
btn = removeImBtn(self.int_obj,self.par_obj,self,i)
btn.setText('Click to Remove')
self.modelTabObj.setCellWidget(c, 0, btn)
text1 = QtGui.QLabel(self.modelTabObj)
text1.setText(str(self.par_obj.file_array[i]).split('/')[-1])
self.modelTabObj.setCellWidget(c,1,text1)
self.par_obj.input_range = QtGui.QLineEdit(self.modelTabObj)
self.par_obj.input_range.setText('1-'+str(self.par_obj.max_t+1))
self.modelTabObj.setCellWidget(c,2,self.par_obj.input_range)
text3 = QtGui.QLabel(self.modelTabObj)