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v2_evaluate.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""QBrain Software v0.1 evaluation mode
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 os
import os.path
import sys
import copy
import pickle
import datetime
import time
from multiprocessing import freeze_support
freeze_support()
from PyQt5 import QtGui, QtCore # , Qt, QtWebKit
from PyQt5 import QtWidgets
import numpy as np
from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
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 as v2
class Eval_load_im_win(QtWidgets.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 = QtWidgets.QVBoxLayout()
self.setLayout(vbox0)
# Load images button
self.loadImages_button_panel = QtWidgets.QHBoxLayout()
self.loadImages_button = QtWidgets.QPushButton("Add Images")
self.loadImages_button.move(20, 20)
self.loadImages_button_panel.addWidget(self.loadImages_button)
self.loadImages_button_panel.addStretch()
about_btn = QtWidgets.QPushButton("About")
about_btn.clicked.connect(lambda: on_about(self))
self.loadImages_button_panel.addWidget(about_btn)
# Table widget which displays
self.modelTabIm_panel = QtWidgets.QHBoxLayout()
self.modelTabIm = QtWidgets.QTableWidget()
self.modelTabIm.setRowCount(1)
self.modelTabIm.setColumnCount(4)
self.modelTabIm.setColumnWidth(0, 125)
self.modelTabIm.resize(550, 200)
self.modelTabIm.setHorizontalHeaderLabels(str(",Image name, Range, Path").split(","))
self.modelTabIm.hide()
self.modelTabIm.setEditTriggers(QtWidgets.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 = QtWidgets.QHBoxLayout()
self.selIntButton = QtWidgets.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 = QtWidgets.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(QtWidgets.QWidget):
"""Interface which allows selection of model."""
def __init__(self, par_obj):
super(Eval_load_model_win, self).__init__()
# The main layout
box = QtWidgets.QVBoxLayout()
self.setLayout(box)
hbox0 = QtWidgets.QHBoxLayout()
box.addLayout(hbox0)
# The two principle columns
vbox0 = QtWidgets.QVBoxLayout()
vbox1 = QtWidgets.QVBoxLayout()
hbox0.addLayout(vbox0)
hbox0.addLayout(vbox1)
self.threadpool = QtCore.QThreadPool()
# Display available models.
# Find all files in folder with serielize prefix.
files = os.listdir(par_obj.forPath)
files = sorted(files, key=lambda p: os.path.getmtime(par_obj.forPath + p))
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__()
self.modelTabFor = QtWidgets.QTableWidget()
self.modelTabFor.setRowCount(1)
self.modelTabFor.setColumnCount(3)
self.modelTabFor.setColumnWidth(2, 200)
self.modelTabFor.resize(600, 500)
self.modelTabFor.setHorizontalHeaderLabels(str(",model name, date and time saved").split(","))
self.modelTabFor.setEditTriggers(QtWidgets.QTableWidget.NoEditTriggers)
vbox0.addWidget(self.modelTabFor)
# Button for going to model evaluation.
self.gotoEvalButton = QtWidgets.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 = QtWidgets.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 = QtWidgets.QHBoxLayout()
self.figure1 = Figure()
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 = QtWidgets.QHBoxLayout()
self.modelImTxt2_panel = QtWidgets.QHBoxLayout()
self.modelImTxt3_panel = QtWidgets.QHBoxLayout()
self.modelImTxt4_panel = QtWidgets.QHBoxLayout()
self.modelImTxt5_panel = QtWidgets.QHBoxLayout()
self.modelImTxt6_panel = QtWidgets.QHBoxLayout()
self.modelImTxt1 = QtWidgets.QLabel()
self.modelImTxt2 = QtWidgets.QLabel()
self.modelImTxt3 = QtWidgets.QLabel()
self.modelImTxt4 = QtWidgets.QLabel()
self.modelImTxt5 = QtWidgets.QLabel()
self.modelImTxt6 = QtWidgets.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()
c = 0
for i in range(0, filesRF.__len__()):
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 = QtWidgets.QLabel(self.modelTabFor)
text1.setText(str(" " + strFn[1]))
self.modelTabFor.setCellWidget(c, 1, text1)
text2 = QtWidgets.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 = QtWidgets.QLabel(self.modelTabFor)
text1.setText(str(" " + strFn[2]))
self.modelTabFor.setCellWidget(c, 1, text1)
text2 = QtWidgets.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
box.addWidget(self.image_status_text)
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.count_maxima_laplace = save_file["count_maxima_laplace"]
# 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):
par_obj.tpt_list = range(0, par_obj.max_t + 1)
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(QtWidgets.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.threadpool = QtCore.QThreadPool()
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 = 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")
top_middle_panel = QtWidgets.QGroupBox("ROI Controls")
top_right_panel = QtWidgets.QGroupBox("Advanced Controls")
# 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(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 = QtWidgets.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 = QtWidgets.QPushButton("Evaluate Images")
self.eval_im_btn.clicked.connect(self.evaluate_images)
self.count_all_btn = QtWidgets.QPushButton("Re-Count Maxima")
self.count_all_btn.clicked.connect(self.count_all_fn)
self.toggle_display_btn = QtWidgets.QPushButton("Show Probability/Maxima")
self.toggle_display_btn.clicked.connect(self.kernel_btn_fn)
self.save_output_data_btn = QtWidgets.QPushButton("Save Output Data")
self.save_output_data_btn.clicked.connect(self.save_output_data)
self.save_output_prediction_btn = QtWidgets.QPushButton("Save Prediction")
self.save_output_prediction_btn.clicked.connect(self.save_output_prediction)
self.save_output_mask_btn = QtWidgets.QPushButton("Save Point Mask")
self.save_output_mask_btn.clicked.connect(self.save_output_mask)
self.save_output_link = QtWidgets.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 = QtWidgets.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 = QtWidgets.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 = QtWidgets.QPushButton("Replot")
self.count_replot_btn_all = QtWidgets.QPushButton("Replot All")
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 * 100))
self.abs_thr_txt.setFixedWidth(25)
"""
rel_thr_lbl = QtWidgets.QLabel('Rel Thr:')
self.rel_thr_txt = QtWidgets.QLineEdit(str(par_obj.rel_thr))
self.rel_thr_txt.setFixedWidth(25)
"""
self.min_distance_panel = QtWidgets.QHBoxLayout()
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(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 = QtWidgets.QHBoxLayout()
self.activate_roi_btn = QtWidgets.QPushButton("Toggle ROI tool")
self.activate_roi_btn.clicked.connect(self.activate_roi_btn_fn)
self.compl_btn = QtWidgets.QPushButton("Save ROI")
self.compl_btn.clicked.connect(self.cursor.complete_roi)
self.clear_btn = QtWidgets.QPushButton("Clear ROI")
self.clear_btn.clicked.connect(self.cursor.clear_ROI)
self.interpolate_btn = QtWidgets.QPushButton("Interpolate (z)")
self.interpolate_btn.clicked.connect(self.interpolate_roi_fn)
self.interpolate_time_btn = QtWidgets.QPushButton("Interpolate (t)")
self.interpolate_time_btn.clicked.connect(self.interpolate_roi_in_time_fn)
roi_panel = QtWidgets.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 = QtWidgets.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 = 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(toolbar)
box.addWidget(self.image_status_text)
self.image_status_text.showMessage("Status: Please Select a Region and Click 'Save ROI'. ")
self.modelLoadedText = QtWidgets.QLabel(self)
self.imageNumText = QtWidgets.QLabel(self)
self.evalStatusText = QtWidgets.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 wheelEvent(self, event):
"""When the mousewheel is rotated"""
if event.angleDelta().y() > 3:
self.Btn_fns.next_im(par_obj)
if event.angleDelta().y() < -3:
self.Btn_fns.prev_im(par_obj)
if event.angleDelta().x() > 10:
self.Btn_fns.next_time(par_obj)
if event.angleDelta().x() < -10:
self.Btn_fns.prev_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
for fileno in range(par_obj.max_file):
imfile = par_obj.filehandlers[fileno]
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())
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.double_feat_arr = {}
par_obj.feat_arr = {}
par_obj.pred_arr = {}
par_obj.sum_pred = {}
par_obj.maxPred = 0 # resets scaling for display between models
par_obj.minPred = 100
"""
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)
"""
for fileno, imfile in par_obj.filehandlers.items():
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 == False:
par_obj.data_store["feat_arr"][fileno][tpt][i] = []
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, "double_feat_arr")
par_obj.data_store["double_feat_arr"][fileno][tpt] = {}
else:
par_obj.data_store["feat_arr"][fileno][tpt] = {}
# 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 * 100))
# 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()
# Win_fn()
channel_wid = QtWidgets.QWidget()
channel_lay = QtWidgets.QHBoxLayout()
channel_wid.setLayout(channel_lay)
evalImWin.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:
item.hide()
item.deleteLater()
ChannelGroup = create_channel_objects(self, par_obj, par_obj.numCH)
for chbx, clabel, contrast, blabel, brightness in ChannelGroup:
channel_lay.addWidget(chbx)
channel_lay.addWidget(clabel)
channel_lay.addWidget(contrast)
channel_lay.addWidget(blabel)
channel_lay.addWidget(brightness)
# contrast.show()
chbx.show()
chbx.setChecked(True)
self.ChannelGroup = ChannelGroup
channel_lay.addStretch()
win_tab.setCurrentWidget(evalImWin)
app.processEvents()
def goto_img_fn(self, zslice=None, tpt=None, imno=None, keep_roi=False):
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(QtWidgets.QCheckBox):
def __init__(self):
QtWidgets.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(QtWidgets.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 = QtWidgets.QTextEdit()
self.setCentralWidget(self.textEdit)
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")
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 = QtWidgets.QFileDialog.getOpenFileName(self, 'Open file', '/home')
par_obj.file_array = []
path = None
for path in QtWidgets.QFileDialog.getOpenFileNames(
self, "Open files", self.par_obj.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 = par_obj.file_array + path
if path == None:
return
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"), "wb"))
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 = QtWidgets.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 = QtWidgets.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 = QtWidgets.QLabel(self.modelTabObj)
text3.setText(str(self.par_obj.file_array[i]))
self.modelTabObj.setCellWidget(c, 3, text3)
c = c + 1
self.modelTabObj.show()
if self.type == "im":
if self.par_obj.file_array.__len__() == 0:
self.modelTabObj.hide()
class loadModelBtn(QtWidgets.QPushButton):
def __init__(self, par_obj, int_obj, parent, idnum, fileName):
QtWidgets.QPushButton.__init__(self, parent)
self.par_obj = par_obj
self.int_obj = int_obj
self.modelNum = idnum
self.fileName = fileName
self.clicked.connect(self.onClick)
self.type = []
def onClick(self):
self.int_obj.loadModelFn(self.par_obj, self.fileName)
class removeImBtn(QtWidgets.QPushButton):
def __init__(self, parent, par_obj, table, idnum):
QtWidgets.QPushButton.__init__(self, parent)
self.modelNum = idnum
self.par_obj = par_obj
self.clicked.connect(self.onClick)
self.table = table
def onClick(self):
self.par_obj.file_array.pop(self.modelNum)
self.table.refreshTable()
# Creates win, an instance of QWidget