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dialogs.py
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dialogs.py
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# Standard library imports
import logging
import os
import sys
import traceback
from shutil import copyfile
# Third-party imports
import cv2
from matplotlib import cm
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas, NavigationToolbar2QT
from matplotlib.figure import Figure
import numpy as np
from PIL import Image
import qimage2ndarray
# PyQt6 imports
from PyQt6 import QtCore, QtGui, QtWidgets # Changed from PySide6
from PyQt6.QtCore import *
from PyQt6.QtGui import *
from PyQt6.QtWidgets import *
from PyQt6.uic import loadUi # PyQt6 has uic to load UI files
# Custom library imports
import widgets as wid
import resources as res
from tools import thermal_tools as tt
from tools import ai_tools as ai
from scipy.ndimage import maximum_filter, minimum_filter
# basic logger functionality
log = logging.getLogger(__name__)
handler = logging.StreamHandler(stream=sys.stdout)
log.addHandler(handler)
CLASS_COLORS = {
0: QColor(255, 0, 0), # Red for class 0
1: QColor(0, 255, 0), # Green for class 1
2: QColor(0, 0, 255), # Blue for class 2
3: QColor(255, 255, 0), # Yellow for class 3
4: QColor(255, 0, 255), # Magenta for class 4
# Add more colors as needed for additional classes
}
def show_exception_box(log_msg):
"""Checks if a QApplication instance is available and shows a messagebox with the exception message.
If unavailable (non-console application), log an additional notice.
"""
if QtWidgets.QApplication.instance() is not None:
errorbox = QtWidgets.QMessageBox()
errorbox.setText("Oops. An unexpected error occured:\n{0}".format(log_msg))
errorbox.exec()
else:
log.debug("No QApplication instance available.")
class UncaughtHook(QtCore.QObject):
_exception_caught = QtCore.pyqtSignal(object)
def __init__(self, *args, **kwargs):
super(UncaughtHook, self).__init__(*args, **kwargs)
# this registers the exception_hook() function as hook with the Python interpreter
sys.excepthook = self.exception_hook
# connect signal to execute the message box function always on main thread
self._exception_caught.connect(show_exception_box)
def exception_hook(self, exc_type, exc_value, exc_traceback):
"""Function handling uncaught exceptions.
It is triggered each time an uncaught exception occurs.
"""
if issubclass(exc_type, KeyboardInterrupt):
# ignore keyboard interrupt to support console applications
sys.__excepthook__(exc_type, exc_value, exc_traceback)
else:
exc_info = (exc_type, exc_value, exc_traceback)
log_msg = '\n'.join([''.join(traceback.format_tb(exc_traceback)),
'{0}: {1}'.format(exc_type.__name__, exc_value)])
log.critical("Uncaught exception:\n {0}".format(log_msg), exc_info=exc_info)
# trigger message box show
self._exception_caught.emit(log_msg)
# create a global instance of our class to register the hook
qt_exception_hook = UncaughtHook()
class AboutDialog(QtWidgets.QDialog):
def __init__(self):
super().__init__()
self.setWindowTitle('What is this app about?')
self.setFixedSize(300, 300)
self.layout = QtWidgets.QVBoxLayout()
about_text = QtWidgets.QLabel(
'The Thermogram app was made to simplify the analysis of thermal images. Any question/remark: samuel.dubois@buildwise.be')
about_text.setWordWrap(True)
logos1 = QtWidgets.QLabel()
pixmap = QtGui.QPixmap(res.find('img/logo_buildwise2.png'))
w = self.width()
pixmap = pixmap.scaledToWidth(100, QtCore.Qt.TransformationMode.SmoothTransformation)
logos1.setPixmap(pixmap)
self.layout.addWidget(about_text)
self.layout.addWidget(logos1, alignment=QtCore.Qt.AlignmentFlag.AlignCenter)
self.setLayout(self.layout)
class CustomGraphicsItem(QGraphicsItem):
def __init__(self, pixmap, target_size=None, parent=None):
super().__init__(parent)
self.pixmap = pixmap
self.opacity = 1.0
self.composition_mode = QtGui.QPainter.CompositionMode.CompositionMode_SourceOver
self.target_size = target_size
if self.target_size:
self.pixmap = self.pixmap.scaled(self.target_size, QtCore.Qt.AspectRatioMode.KeepAspectRatio,
QtCore.Qt.TransformationMode.SmoothTransformation)
def boundingRect(self):
return QRectF(self.pixmap.rect())
def paint(self, painter, option, widget=None):
painter.setOpacity(self.opacity)
painter.setCompositionMode(self.composition_mode)
painter.drawPixmap(0, 0, self.pixmap)
def setPixmap(self, pixmap, rescale=True):
self.pixmap = pixmap
if rescale:
self.pixmap = self.pixmap.scaled(self.target_size, QtCore.Qt.AspectRatioMode.KeepAspectRatio,
QtCore.Qt.TransformationMode.SmoothTransformation)
self.update()
class HotSpotDialog(QDialog):
def __init__(self, thermal_image, raw_data, parent=None):
super().__init__(parent)
self.raw_data = raw_data # Store the raw temperature data (NumPy array)
self.thermal_image = thermal_image # Path or QImage to the thermal JPEG
self.normalized_data = self.normalize_data(self.raw_data) # Normalize raw data to [0, 255]
self.prominence = 80 # Default prominence factor (relative to 0-255 scale)
self.structure_size = 35 # Default structure size
self.show_labels = True # Show temperature labels by default
self.exclude_edges = False # Whether to exclude maxima and minima at the edges
self.selection_mode = 'both' # Default is to show both maxima and minima
# List to keep track of spot measurements (both maxima and minima)
self.spot_measurements = []
# pen
self.pen = QPen()
# self.pen.setStyle(Qt.DashDotLine)
self.pen.setWidth(2)
# Layout setup
self.setWindowTitle("Detect Temperature Hot Spots")
self.layout = QVBoxLayout()
# Create a QGraphicsView to show the thermal image
self.graphics_view = QGraphicsView()
self.scene = QGraphicsScene(self)
self.graphics_view.setScene(self.scene)
self.layout.addWidget(self.graphics_view)
# Display the image
self.display_image()
# Slider to adjust the prominence factor
self.slider_label = QLabel("Prominence Factor: 80")
self.layout.addWidget(self.slider_label)
self.prominence_slider = QSlider(Qt.Orientation.Horizontal)
self.prominence_slider.setMinimum(1)
self.prominence_slider.setMaximum(255) # Adjust as needed
self.prominence_slider.setValue(80)
self.prominence_slider.valueChanged.connect(self.update_prominence)
self.layout.addWidget(self.prominence_slider)
# Slider to adjust the structure size
self.structure_slider_label = QLabel("Structure Size: 35")
self.layout.addWidget(self.structure_slider_label)
self.structure_slider = QSlider(Qt.Orientation.Horizontal)
self.structure_slider.setMinimum(5)
self.structure_slider.setMaximum(100) # Structure size from 1 to 10
self.structure_slider.setValue(35)
self.structure_slider.valueChanged.connect(self.update_structure_size)
self.layout.addWidget(self.structure_slider)
# ComboBox to choose between maxima, minima, or both
self.combo_box_label = QLabel("Show:")
self.layout.addWidget(self.combo_box_label)
self.combo_box = QComboBox()
self.combo_box.addItem("Both")
self.combo_box.addItem("Only Maxima")
self.combo_box.addItem("Only Minima")
self.combo_box.currentTextChanged.connect(self.update_selection_mode)
self.layout.addWidget(self.combo_box)
# Checkbox to toggle temperature labels
self.show_labels_checkbox = QCheckBox("Show Temperature Labels")
self.show_labels_checkbox.setChecked(True) # Default is checked
self.show_labels_checkbox.stateChanged.connect(self.toggle_labels)
self.layout.addWidget(self.show_labels_checkbox)
# Checkbox for excluding edge maxima and minima
self.exclude_edges_checkbox = QCheckBox("Exclude Edge Maxima and Minima")
self.exclude_edges_checkbox.setChecked(False)
self.exclude_edges_checkbox.stateChanged.connect(self.toggle_edge_exclusion)
self.layout.addWidget(self.exclude_edges_checkbox)
self.setLayout(self.layout)
def normalize_data(self, raw_data):
"""Normalize the raw temperature data to the 0-255 range."""
min_val = np.min(raw_data)
max_val = np.max(raw_data)
normalized = 255 * (raw_data - min_val) / (max_val - min_val)
return normalized
def display_image(self):
# Convert thermal_image to a QPixmap and display it in the QGraphicsView
if isinstance(self.thermal_image, str): # If it's a path, load the image
image = QImage(self.thermal_image)
elif isinstance(self.thermal_image, QImage):
image = self.thermal_image
else:
raise ValueError("Invalid thermal image format")
pixmap = QPixmap.fromImage(image)
self.pixmap_item = QGraphicsPixmapItem(pixmap)
self.scene.addItem(self.pixmap_item) # Add the pixmap to the scene
# Detect local maxima and minima and display them on the image
self.detect_hotspots()
def update_prominence(self):
# Update prominence factor and refresh hot spot detection
self.prominence = self.prominence_slider.value()
self.slider_label.setText(f"Prominence Factor: {self.prominence}")
self.detect_hotspots()
def update_structure_size(self):
# Update structure size and refresh hot spot detection
self.structure_size = self.structure_slider.value()
self.structure_slider_label.setText(f"Structure Size: {self.structure_size}")
self.detect_hotspots()
def update_selection_mode(self, mode):
"""Update whether to show maxima, minima, or both."""
if mode == "Only Maxima":
self.selection_mode = 'maxima'
elif mode == "Only Minima":
self.selection_mode = 'minima'
else:
self.selection_mode = 'both'
self.detect_hotspots()
def toggle_labels(self):
# Toggle visibility of temperature labels
self.show_labels = self.show_labels_checkbox.isChecked()
for spot in self.spot_measurements:
if spot.text_item:
spot.text_item.setVisible(self.show_labels)
def toggle_edge_exclusion(self):
# Toggle exclusion of edge maxima and minima
self.exclude_edges = self.exclude_edges_checkbox.isChecked()
self.detect_hotspots()
def detect_hotspots(self):
# Clear previous spots from the scene
self.clear_spot_measurements()
# Create a square structure based on the current structure size
structure = np.ones((self.structure_size, self.structure_size), dtype=bool)
# Detect local maxima
local_max = (self.normalized_data == maximum_filter(self.normalized_data, footprint=structure))
# Detect local minima (inverted maxima detection)
local_min = (self.normalized_data == minimum_filter(self.normalized_data, footprint=structure))
# Exclude maxima and minima near the edges if requested
if self.exclude_edges:
local_max[0, :] = False
local_max[-1, :] = False
local_max[:, 0] = False
local_max[:, -1] = False
local_min[0, :] = False
local_min[-1, :] = False
local_min[:, 0] = False
local_min[:, -1] = False
# Get indices of the detected local maxima
maxima_indices = np.argwhere(local_max)
# Get indices of the detected local minima
minima_indices = np.argwhere(local_min)
# Filter maxima and minima based on prominence
filtered_maxima = self.filter_by_prominence(maxima_indices, is_maxima=True)
filtered_minima = self.filter_by_prominence(minima_indices, is_maxima=False)
# Based on the selection mode, display only maxima, only minima, or both
if self.selection_mode in ['maxima', 'both']:
# Add markers for the filtered maxima (red)
for maximum in filtered_maxima:
x, y = maximum
self.add_spot(x, y, color=Qt.GlobalColor.red)
if self.selection_mode in ['minima', 'both']:
# Add markers for the filtered minima (blue)
for minimum in filtered_minima:
x, y = minimum
self.add_spot(x, y, color=Qt.GlobalColor.blue)
def filter_by_prominence(self, extrema_indices, is_maxima=True):
"""Filter detected maxima or minima based on the prominence value."""
filtered_extrema = []
for point in extrema_indices:
x, y = point
point_value = self.normalized_data[x, y]
# Get the neighborhood around the point based on structure size
min_surrounding_value, max_surrounding_value = self.get_surrounding_extrema(x, y, self.structure_size)
# Calculate prominence
if is_maxima:
prominence = point_value - min_surrounding_value # Prominence for maxima
else:
prominence = max_surrounding_value - point_value # Prominence for minima
if prominence >= self.prominence:
filtered_extrema.append(point)
return filtered_extrema
def get_surrounding_extrema(self, x, y, structure_size):
"""Calculate the minimum and maximum values around a point based on the structure size."""
neighbors = []
# Adjust the neighborhood size based on structure size
for i in range(max(0, x - structure_size), min(self.raw_data.shape[0], x + structure_size + 1)):
for j in range(max(0, y - structure_size), min(self.raw_data.shape[1], y + structure_size + 1)):
if (i, j) != (x, y): # Exclude the point itself
neighbors.append(self.normalized_data[i, j])
if neighbors:
return min(neighbors), max(neighbors)
else:
return self.normalized_data[x, y], self.normalized_data[x, y]
def add_spot(self, x, y, color):
# Create a QPointF for the spot location
qpoint = QPointF(y, x)
# Create a PointMeas object
spot = tt.PointMeas(qpoint)
spot.temp = self.raw_data[x, y] # Assign the temperature value
# Create the ellipse and text items
spot.create_items()
# Set ellipse color
self.pen.setColor(color)
spot.ellipse_item.setPen(self.pen)
# Add ellipse and text to the scene
self.scene.addItem(spot.ellipse_item)
if self.show_labels:
self.scene.addItem(spot.text_item)
# Add all items to the scene for future reference
spot.all_items.append(spot.ellipse_item)
spot.all_items.append(spot.text_item)
# Store the measurement in the list
self.spot_measurements.append(spot)
def clear_spot_measurements(self):
# Remove all previously added items from the scene
for spot in self.spot_measurements:
for item in spot.all_items:
self.scene.removeItem(item)
self.spot_measurements.clear()
class ImageFusionDialog(QtWidgets.QDialog):
"""
Dialog that allows the user to choose advances thermography options
"""
def __init__(self, img_object, ir_img_path, dest_path_preview):
super().__init__()
basepath = os.path.dirname(__file__)
basename = 'fusion'
uifile = os.path.join(basepath, 'ui/%s.ui' % basename)
loadUi(uifile, self)
self.ir_path = ir_img_path
self.img_object = img_object
self.colormap_name = img_object.colormap
self.n_colors = img_object.n_colors
self.temperatures = img_object.raw_data_undis
self.dest_path_preview = dest_path_preview
self.scene = QGraphicsScene()
self.view.setScene(self.scene)
self.image_to_export = None
min_temp_scaled = self.scale_temperature(img_object.tmin)
max_temp_scaled = self.scale_temperature(img_object.tmax)
min_shown_temp_scaled = self.scale_temperature(img_object.tmin_shown)
max_shown_temp_scaled = self.scale_temperature(img_object.tmax_shown)
if min_shown_temp_scaled < min_temp_scaled:
min_shown_temp_scaled = min_temp_scaled
if max_shown_temp_scaled > max_temp_scaled:
max_shown_temp_scaled = max_temp_scaled
# range slider for shown data
self.range_slider_shown = wid.QRangeSlider()
self.range_slider_shown.handleSize = 10
self.range_slider_shown.back_color = QColor(220, 220, 220)
self.range_slider_shown.setLowerValue(min_shown_temp_scaled)
self.range_slider_shown.setUpperValue(max_shown_temp_scaled)
self.range_slider_shown.setMinimum(min_temp_scaled)
self.range_slider_shown.setMaximum(max_temp_scaled)
# range slider for palette
self.range_slider_map = wid.QRangeSlider(self.colormap_name)
self.range_slider_map.setLowerValue(min_shown_temp_scaled)
self.range_slider_map.setUpperValue(max_shown_temp_scaled)
self.range_slider_map.setMinimum(min_temp_scaled)
self.range_slider_map.setMaximum(max_temp_scaled)
self.range_slider_shown.lowerValueChanged.connect(self.updateIRImage)
self.range_slider_shown.upperValueChanged.connect(self.updateIRImage)
self.range_slider_map.lowerValueChanged.connect(self.recolorIRImage)
self.range_slider_map.upperValueChanged.connect(self.recolorIRImage)
# edit labels
self.label_max.setText(f'{str(min_shown_temp_scaled / 100)} °C')
self.label_min.setText(f'{str(max_shown_temp_scaled / 100)} °C')
# edit labels
self.label_max_2.setText(f'{str(max_shown_temp_scaled / 100)} °C')
self.label_min_2.setText(f'{str(min_shown_temp_scaled / 100)} °C')
# new label
self.verticalLayout_2.addWidget(self.range_slider_shown)
self.verticalLayout_2.addWidget(self.range_slider_map)
# Load images
colorPixmap = QPixmap(img_object.rgb_path)
thermalPixmap = QPixmap(self.ir_path)
# Create custom graphics items
self.colorImageItem = CustomGraphicsItem(colorPixmap)
self.thermalImageItem = CustomGraphicsItem(thermalPixmap, target_size=colorPixmap.size())
# Add items to scene
self.scene.addItem(self.colorImageItem)
self.scene.addItem(self.thermalImageItem)
# Fusion Mode ComboBox
modes = ['Screen',
'SourceOver',
'Multiply',
'Overlay',
'Darken',
'Lighten',
'ColorBurn',
'HardLight',
'SoftLight',
]
for mode in modes:
self.modeComboBox.addItem(mode)
self.modeComboBox.currentTextChanged.connect(self.changeFusionMode)
self.opacitySlider.setRange(0, 100)
self.opacitySlider.setValue(100)
self.opacitySlider.valueChanged.connect(self.changeOpacity)
self.changeFusionMode(self.modeComboBox.currentText())
self.changeOpacity(self.opacitySlider.value())
# button actions
self.buttonBox.accepted.connect(self.accept)
self.buttonBox.rejected.connect(self.reject)
self.grayscaleCheckbox.stateChanged.connect(self.toggleGrayscale)
self.updateIRImage(0)
def changeFusionMode(self, mode):
mode_complete = 'CompositionMode_' + mode
blend_mode = QPainter.CompositionMode.__members__[mode_complete]
self.thermalImageItem.composition_mode = blend_mode
self.thermalImageItem.update()
def changeOpacity(self, value):
self.thermalImageItem.opacity = value / 100.0
self.thermalImageItem.update()
def showEvent(self, event):
super().showEvent(event)
self.fitItemsInView()
def resizeEvent(self, event):
super().resizeEvent(event)
self.fitItemsInView()
def fitItemsInView(self):
# Disable scrollbars
self.view.setHorizontalScrollBarPolicy(QtCore.Qt.ScrollBarPolicy.ScrollBarAlwaysOff)
self.view.setVerticalScrollBarPolicy(QtCore.Qt.ScrollBarPolicy.ScrollBarAlwaysOff)
# Get the size of the view
view_rect = self.view.viewport().rect()
view_width = view_rect.width()
view_height = view_rect.height()
# Assuming colorPixmap is the pixmap of the color image item
pixmap_size = self.colorImageItem.pixmap.size()
pixmap_width = pixmap_size.width()
pixmap_height = pixmap_size.height()
# Calculate scale factors for width and height
scale_factor_width = view_width / pixmap_width
scale_factor_height = view_height / pixmap_height
# Use the smaller scale factor to keep the aspect ratio
scale_factor = min(scale_factor_width, scale_factor_height)
# Apply the scale factor to both pixmap items
self.colorImageItem.setScale(scale_factor)
self.thermalImageItem.setScale(scale_factor)
# Adjust the scene size to the scaled pixmap size
scaled_width = pixmap_width * scale_factor
scaled_height = pixmap_height * scale_factor
self.scene.setSceneRect(0, 0, scaled_width, scaled_height)
# Center the items in the view
self.colorImageItem.setPos((view_width - scaled_width) / 2, (view_height - scaled_height) / 2)
self.thermalImageItem.setPos((view_width - scaled_width) / 2, (view_height - scaled_height) / 2)
def recolorIRImage(self, value):
min_temp = self.range_slider_map.lowerValue() / 100.0 # Adjust if you used scaling
max_temp = self.range_slider_map.upperValue() / 100.0
# edit labels
self.label_max_2.setText(f'{str(max_temp)} °C')
self.label_min_2.setText(f'{str(min_temp)} °C')
# compute new normalized temperature
thermal_normalized = (self.temperatures - min_temp) / (max_temp - min_temp)
# get colormap
if self.colormap_name in tt.LIST_CUSTOM_CMAPS:
custom_cmap = tt.get_custom_cmaps(self.colormap_name, self.n_colors)
else:
custom_cmap = cm.get_cmap(self.colormap_name, self.n_colors)
thermal_cmap = custom_cmap(thermal_normalized)
thermal_cmap = np.uint8(thermal_cmap * 255)
img_thermal = Image.fromarray(thermal_cmap[:, :, [0, 1, 2]])
img_thermal.save(self.dest_path_preview)
self.ir_path = self.dest_path_preview
self.updateIRImage(0)
def updateIRImage(self, value):
min_temp = self.range_slider_shown.lowerValue() / 100.0 # Adjust if you used scaling
max_temp = self.range_slider_shown.upperValue() / 100.0
# edit labels
self.label_max.setText(f'{str(max_temp)} °C')
self.label_min.setText(f'{str(min_temp)} °C')
# Load the IR image and convert to NumPy array
ir_image = QImage(self.ir_path)
ir_image = ir_image.convertToFormat(QImage.Format.Format_ARGB32)
# Convert QImage to a 4-channel NumPy array (RGBA)
ir_array = qimage2ndarray.byte_view(ir_image)
# Ensure that the array has 4 channels (RGBA)
if ir_array.shape[2] == 3:
# Add an alpha channel if it's missing
alpha_channel = np.full((ir_array.shape[0], ir_array.shape[1], 1), 255, dtype=np.uint8)
ir_array = np.concatenate((ir_array, alpha_channel), axis=2)
elif ir_array.shape[2] == 4:
# Swap red and blue channels
ir_array = ir_array[..., [2, 1, 0, 3]] # BGR to RGB
# Create a mask where temperatures are outside the range
mask = ~((self.temperatures >= min_temp) & (self.temperatures <= max_temp))
# Apply the mask to the alpha channel, setting those pixels to transparent
ir_array[..., 3] = np.where(mask, 0, ir_array[..., 3])
# Convert the modified array back to QImage and then to QPixmap
updated_image = qimage2ndarray.array2qimage(ir_array, normalize=False)
updated_pixmap = QPixmap.fromImage(updated_image)
# Update the item
self.thermalImageItem.setPixmap(updated_pixmap)
self.thermalImageItem.update()
def scale_temperature(self, temp):
return int(temp * 100) # Scaling factor of 100
def toggleGrayscale(self):
if self.grayscaleCheckbox.isChecked():
# Convert to grayscale
gray_pixmap = self.colorImageItem.pixmap.toImage().convertToFormat(QImage.Format.Format_Grayscale8)
self.colorImageItem.setPixmap(QPixmap.fromImage(gray_pixmap), rescale=False)
else:
# Restore original color image
colorPixmap = QPixmap(self.img_object.rgb_path) # Assuming img_object is accessible
self.colorImageItem.setPixmap(colorPixmap, rescale=False)
self.colorImageItem.update()
def exportComposedImage(self, output_path):
"""
Export the composed image (fused color and infrared images) to the specified output path.
"""
# Determine the size of the composed image
width = self.colorImageItem.pixmap.width()
height = self.colorImageItem.pixmap.height()
# Create an empty QImage with the size of the final composed image
composed_image = QImage(width, height, QImage.Format.Format_ARGB32)
composed_image.fill(QtCore.Qt.GlobalColor.transparent) # Start with a transparent image
# Initialize a QPainter to draw on the composed QImage
painter = QPainter(composed_image)
# Draw the color image first
painter.drawPixmap(0, 0, self.colorImageItem.pixmap)
# Set the composition mode (e.g., Overlay, Multiply, etc.) and opacity
painter.setCompositionMode(self.thermalImageItem.composition_mode)
painter.setOpacity(self.thermalImageItem.opacity)
# Draw the infrared image with the appropriate blending mode
painter.drawPixmap(0, 0, self.thermalImageItem.pixmap)
# End the painter
painter.end()
if output_path.lower().endswith('.jpg') or output_path.lower().endswith('.jpeg'):
composed_image.save(output_path, 'JPEG', 100)
else:
composed_image.save(output_path) # PNG is lossless by default
composed_image.save(output_path)
class AlignmentDialog(QDialog):
def __init__(self, img_object, temp_folder, theta=[1.1, 0, 0]):
super().__init__()
# images to process
# copy images to temp folder
self.img_object = img_object
self.temp_folder = temp_folder
self.ir_path = os.path.join(temp_folder, 'IR.JPG')
self.rgb_path = os.path.join(temp_folder, 'RGB.JPG')
copyfile(img_object.path, self.ir_path)
copyfile(img_object.rgb_path_original, self.rgb_path)
# get focal and center points
"""
self.F = F
self.CX = 320
self.CY = 256
self.d_mat = d_mat
"""
# Initial theta values
# Parameters are [zoom, y-offset, x-offset]
self.theta = theta
# Setup UI
self.setWindowTitle("Thermal Image Processor")
self.setGeometry(100, 100, 800, 800)
# Main layout
layout = QVBoxLayout(self)
# Graphics view
self.graphics_view = QGraphicsView()
layout.addWidget(self.graphics_view)
self.scene = QGraphicsScene()
self.graphics_view.setScene(self.scene)
# Sliders and Labels for parameters
self.sliders = []
self.labels = []
param_names = ["zoom", "y-offset", "x-offset"]
param_ranges = [(0.5, 2), (-100, 100), (-100, 100)]
for i, (param_name, param_range) in enumerate(zip(param_names, param_ranges)):
label = QLabel(f"{param_name}: {self.theta[i]}")
layout.addWidget(label)
self.labels.append(label)
slider = QSlider(Qt.Orientation.Horizontal)
if i != 0:
slider.setMinimum(int(param_range[0] * 10))
slider.setMaximum(int(param_range[1] * 10))
slider.setValue(int(self.theta[i] * 10))
else:
slider.setMinimum(int(param_range[0] * 100))
slider.setMaximum(int(param_range[1] * 100))
slider.setValue(int(self.theta[i] * 100))
slider.valueChanged.connect(lambda value, x=i: self.update_parameter(x, value))
self.sliders.append(slider)
layout.addWidget(slider)
# Optimize button
self.optimize_button = QPushButton('Optimize')
self.optimize_button.clicked.connect(self.optimize)
layout.addWidget(self.optimize_button)
# Button box for OK and Cancel
button_layout = QHBoxLayout()
self.ok_button = QPushButton("OK")
self.cancel_button = QPushButton("Cancel")
button_layout.addWidget(self.ok_button)
button_layout.addWidget(self.cancel_button)
layout.addLayout(button_layout)
# Connect buttons to their actions
self.ok_button.clicked.connect(self.accept)
self.cancel_button.clicked.connect(self.reject)
# Load and process initial images
self.process_images()
def update_parameter(self, index, value):
if index != 0:
self.theta[index] = value / 10
self.labels[index].setText(f"{self.labels[index].text().split(':')[0]}: {value / 10}")
else:
self.theta[index] = value / 100
self.labels[index].setText(f"{self.labels[index].text().split(':')[0]}: {value / 100}")
self.process_images()
def optimize(self):
# Placeholder for optimize function
print("Optimization started...")
def convert_np_img_to_qimage(self, img):
"""Converts a numpy array image to QImage."""
if img.ndim == 3: # Color image
h, w, ch = img.shape
bytes_per_line = ch * w
qimage = QImage(img.data, w, h, bytes_per_line, QImage.Format.Format_RGB888)
else: # Grayscale image
h, w = img.shape
qimage = QImage(img.data, w, h, QImage.Format.Format_Grayscale8)
return qimage
def process_images(self):
# Image processing placeholder
print(f"Processing with theta: {self.theta}")
# This should call your actual image processing code
tt.process_th_image_with_zoom(self.img_object, self.temp_folder, self.theta)
# Read the original RGB image
rgb_image = cv2.imread(os.path.join(self.temp_folder, 'rescale.JPG'))
# Convert RGB image to grayscale for background
grayscale_rgb_image = cv2.cvtColor(rgb_image, cv2.COLOR_BGR2GRAY)
# Read or process the IR lines image
# Assuming 'lines_ir' is a binary image with lines as white (255) and background as black (0)
# For demonstration, replace this with an actual call to your image processing function
lines_ir = cv2.imread(os.path.join(self.temp_folder, 'ir_lines.JPG'), cv2.IMREAD_GRAYSCALE) # Placeholder
# Convert the grayscale image to a 3-channel image to overlay colors
grayscale_rgb_image_colored = cv2.cvtColor(grayscale_rgb_image, cv2.COLOR_GRAY2BGR)
# Overlay IR lines: Set them to blue (or any color you choose) on the grayscale image
grayscale_rgb_image_colored[lines_ir >= 100] = [255, 0, 0] # Blue: [B, G, R] - Change this color if needed
# Convert the overlay image to QImage for display
qimage = self.convert_np_img_to_qimage(grayscale_rgb_image_colored)
# Update QGraphicsScene
self.scene.clear()
pixmap_item = QGraphicsPixmapItem(QPixmap.fromImage(qimage))
self.scene.addItem(pixmap_item)
class DialogEdgeOptions(QtWidgets.QDialog):
"""
Dialog that allows the user to choose advances thermography options
"""
def __init__(self, parameters, parent=None):
QtWidgets.QDialog.__init__(self)
basepath = os.path.dirname(__file__)
basename = 'edge_options'
uifile = os.path.join(basepath, 'ui/%s.ui' % basename)
loadUi(uifile, self)
self.comboBox_blur_size.addItems([str(3), str(5), str(7)])
self.comboBox_color.addItems(['white', 'black'])
self.comboBox_method.addItems(['Sobel A', 'Kernel 1', 'Kernel 2', 'Canny', 'Canny-L2', 'ML'])
# button actions
self.buttonBox.accepted.connect(self.accept)
self.buttonBox.rejected.connect(self.reject)
self.checkBox.stateChanged.connect(self.toggle_combo)
# set initial parameters
self.parameters = parameters
self.set_ini_param()
def set_ini_param(self):
# Set initial values for combo boxes if parameters are provided
self.comboBox_method.setCurrentIndex(self.parameters[0])
index = self.comboBox_color.findText(self.parameters[1], QtCore.Qt.MatchFlag.MatchFixedString)
if index >= 0:
self.comboBox_color.setCurrentIndex(index)
if self.parameters[2]:
self.checkBox_bil.setChecked(True)
else:
self.checkBox_bil.setChecked(False)
if self.parameters[3]:
self.checkBox.setChecked(True)
else:
self.checkBox.setChecked(False)
index = self.comboBox_blur_size.findText(str(self.parameters[4]), QtCore.Qt.MatchFlag.MatchFixedString)
if index >= 0:
self.comboBox_blur_size.setCurrentIndex(index)
op_value = self.parameters[5]
self.horizontalSlider.setValue(int(op_value * 100))
def toggle_combo(self):
if self.checkBox.isChecked():
self.comboBox_blur_size.setEnabled(True)
else:
self.comboBox_blur_size.setEnabled(False)
class DialogThParams(QtWidgets.QDialog):
"""
Dialog that allows the user to choose advances thermography options
"""
def __init__(self, param, parent=None):
QtWidgets.QDialog.__init__(self)
basepath = os.path.dirname(__file__)
basename = 'dialog_options'
uifile = os.path.join(basepath, 'ui/%s.ui' % basename)
loadUi(uifile, self)
self.lineEdit_em.setText(str(param['emissivity']))
self.lineEdit_dist.setText(str(param['distance']))
self.lineEdit_rh.setText(str(param['humidity']))
self.lineEdit_temp.setText(str(param['reflection']))
# define constraints on lineEdit
# button actions
self.buttonBox.accepted.connect(self.accept)
self.buttonBox.rejected.connect(self.reject)
class MeasLineDialog(QtWidgets.QDialog):
def __init__(self, data):
QtWidgets.QDialog.__init__(self)
basepath = os.path.dirname(__file__)
basename = 'meas_dialog_2d'
uifile = os.path.join(basepath, 'ui/%s.ui' % basename)
loadUi(uifile, self)
self.data = data
self.y_values = data
self.x_values = np.arange(len(self.y_values))
# Assuming a DPI of 100
dpi = 100
width, height = 600 / dpi, 400 / dpi # Convert pixel dimensions to inches
# Plotting Area
self.figure = Figure(figsize=(width, height), dpi=dpi)
self.canvas = FigureCanvas(self.figure)
self.verticalLayout_2.addWidget(self.canvas)
ax = self.figure.add_subplot() # 1 row, 2 columns, second plot
ax.plot(self.x_values, self.y_values, 'b-') # Assuming 'r' is accessible and correctly sized
ax.set_xlabel("length [pixels]")
ax.set_ylabel("Temperature [°C]")
# Improve the axis
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_position(('data', 0))
ax.spines['left'].set_position(('data', 0))
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.grid(True, linestyle='--', which='both', zorder=0)
self.highlights = self.create_highlights()
# add table model for data
self.model = wid.TableModel(self.highlights)
self.tableView.setModel(self.model)
# add matplotlib toolbar
toolbar = NavigationToolbar2QT(self.canvas, self)
self.verticalLayout_2.addWidget(toolbar)
# button actions
self.buttonBox.accepted.connect(self.accept)
self.buttonBox.rejected.connect(self.reject)
self.create_connections()
def create_connections(self):
pass
def create_highlights(self):
# extrema
self.tmax = np.amax(self.y_values)
self.tmin = np.amin(self.y_values)
self.tmean = np.mean(self.y_values)
# normalized data
self.th_norm = (self.y_values - self.tmin) / (self.tmax - self.tmin)
highlights = [
['Max. Temp. [°C]', str(self.tmax)],
['Min. Temp. [°C]', str(self.tmin)],
['Average Temp. [°C]', str(self.tmean)]
]
return highlights
class Meas3dDialog_simple(QtWidgets.QDialog):
def __init__(self, rect_annot):
QtWidgets.QDialog.__init__(self)
basepath = os.path.dirname(__file__)
basename = 'meas_dialog_3d_simple'
uifile = os.path.join(basepath, 'ui/%s.ui' % basename)
loadUi(uifile, self)
self.setWindowTitle('Area Measurement')
self.matplot_c = wid.MplCanvas_project3d(self)
self.ax = self.matplot_c.figure.add_subplot(projection='3d') # add subplot, retrieve axis object
self.ax.view_init(elev=70, azim=-45, roll=0)
self.ax.set_zlabel('Temperature [°C]')
self.data = rect_annot.data_roi
self.highlights = rect_annot.compute_highlights()
# add table model for data
self.model = wid.TableModel(self.highlights)
self.tableView.setModel(self.model)
# add matplotlib toolbar
toolbar = NavigationToolbar2QT(self.matplot_c, self)
self.verticalLayout.addWidget(toolbar)
self.verticalLayout.addWidget(self.matplot_c)
# button actions
self.buttonBox.accepted.connect(self.accept)
self.buttonBox.rejected.connect(self.reject)
self.create_connections()
def create_connections(self):
pass
def surface_from_image_matplot(self, colormap, n_colors, col_low, col_high):
# colormap operation