The PyQtGraph module is a graphics and user interface library for Python that provides functionality commonly required in designing and science applications. Its primary goals are to provide fast, interactive graphics for displaying data (plots, video, etc.). Widget used for display and analysis of image data. Implements many features like displaying 2D and 3D image data. For 3D data, a z-axis slider is displayed allowing the user to select which frame is displayed. Displays histogram of image data with movable region defining the dark/light levels, editable gradient provides a color lookup table, frame slider may also be moved using left/right arrow keys as well as pgup, pgdn, home, and end.
Basic analysis features includes:
1. ROI and embedded plot for measuring image values across frames
2. Image normalization / background subtraction
We can create an image view with the help of command given below:
# creating a pyqtgraph image view object img = pg.ImageView()
Step-by-step Approach:
- Import pyqtgraph, pyqt5 and numpy modules.
- Create Main window class.
- Create an image view object.
- Create an image using numpy and gaussian filter of the pyqtgraph module.
- Create a custom color map and set it to the image view.
- Add the image video view to the grid layout with other widgets.
- Set grid layout widget as the central widget of main window.
Below is the implementation based on the above approach:
Python3
# import required modules from PyQt5.QtWidgets import * import sys import numpy as np import pyqtgraph as pg from PyQt5.QtGui import * from PyQt5.QtCore import * from collections import namedtuple # Main window class class Window(QMainWindow): def __init__( self ): super ().__init__() # setting title self .setWindowTitle( "PyQtGraph" ) # setting geometry self .setGeometry( 100 , 100 , 600 , 500 ) # icon icon = QIcon( "skin.png" ) # setting icon to the window self .setWindowIcon(icon) # calling method self .UiComponents() # showing all the widgets self .show() # method for components def UiComponents( self ): # creating a widget object widget = QWidget() # creating a label label = QLabel( "GeeksforLazyroar Image View" ) # setting minimum width label.setMinimumWidth( 130 ) # making label do word wrap label.setWordWrap( True ) # setting configuration options pg.setConfigOptions(antialias = True ) # creating image view object imv = pg.ImageView() # Create random 3D data set with noisy signals img = pg.gaussianFilter(np.random.normal( size = ( 200 , 200 )), ( 5 , 5 )) * 20 + 100 # setting new axis to image img = img[np.newaxis, :, :] # decay data decay = np.exp( - np.linspace( 0 , 0.3 , 100 ))[:, np.newaxis, np.newaxis] # random data data = np.random.normal(size = ( 100 , 200 , 200 )) data + = img * decay data + = 2 # adding time-varying signal sig = np.zeros(data.shape[ 0 ]) sig[ 30 :] + = np.exp( - np.linspace( 1 , 10 , 70 )) sig[ 40 :] + = np.exp( - np.linspace( 1 , 10 , 60 )) sig[ 70 :] + = np.exp( - np.linspace( 1 , 10 , 30 )) sig = sig[:, np.newaxis, np.newaxis] * 3 data[:, 50 : 60 , 30 : 40 ] + = sig # Displaying the data and assign each frame a time value from 1.0 to 3.0 imv.setImage(data, xvals = np.linspace( 1. , 3. , data.shape[ 0 ])) # Set a custom color map colors = [ ( 0 , 0 , 0 ), ( 45 , 5 , 61 ), ( 84 , 42 , 55 ), ( 150 , 87 , 60 ), ( 208 , 171 , 141 ), ( 255 , 255 , 255 ) ] # color map cmap = pg.ColorMap(pos = np.linspace( 0.0 , 1.0 , 6 ), color = colors) # setting color map to the image view imv.setColorMap(cmap) # Creating a grid layout layout = QGridLayout() # minimum width value of the label label.setFixedWidth( 130 ) # setting this layout to the widget widget.setLayout(layout) # adding label in the layout layout.addWidget(label, 1 , 0 ) # plot window goes on right side, spanning 3 rows layout.addWidget(imv, 0 , 1 , 3 , 1 ) # setting this widget as central widget of the main window self .setCentralWidget(widget) # Driver Code # create pyqt5 app App = QApplication(sys.argv) # create the instance of our Window window = Window() # start the app sys.exit(App. exec ()) |
Output: