The code on this page uses the Matplotlib and Pillow packages which can be installed from the terminal via the following commands:
# "python3.12" should correspond to the version of Python you are using
python3.12 -m pip install matplotlib
python3.12 -m pip install pillow
Once finished, import these packages into your Python script along with the built-in platform
and json
modules:
# Matplotlib is for creating static, animated and interactive visualizations
from matplotlib import pyplot as plt
# Pillow is a fork of the Python Imaging Library (PIL) for image processing
from PIL import Image
# Access to underlying platform's identifying data
import platform
# JSON encoder and decoder
import json
Later on in this tutorial we will be creating interactive plots. If you get the following error while trying to do that it means that the backend being used for displaying the image is not set up for interactive mode:
"UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown"
Try using a different backend, for example ‘Qt5Agg’ or ‘TkAgg’. As of 2024-01-31, ‘Qt5Agg’ works on Ubuntu 22.04 and can be installed from the terminal with:
python3 -m pip install PyQt5
python3 -m pip install PySide2
Then, you can switch to it from within your Python script:
# Use a backend that supports interactive mode
plt.switch_backend('Qt5Agg')
As of 2024-01-31, Tkinter has been released for Python 3.11 but not for Python 3.12 on Ubuntu 22.04. As a result, the ‘TkAgg’ backend will work in 3.11 but not in 3.12. You can install Tkinter from the terminal via the following
sudo apt-get install python3-tk
# or
sudo apt-get install python3.11-tk
# but not `sudo apt-get install python3.12-tk`
Once installed, you can switch to TkAgg:
plt.switch_backend('TkAgg')
For our tutorial, we’ll use an image of Red from the Generation I Pokémon games:
If this image file is in the same folder as your Python script you can import it like this:
# Import image
img = Image.open('red-225x225.png')
# Display image
plt.imshow(img, cmap='gray')
plt.xticks([])
plt.yticks([])
In order to get the best view, maximise the window that’s showing your image:
# Maximise the window
manager = plt.get_current_fig_manager()
if plt.get_backend() == 'TkAgg':
if platform.system() == 'Linux':
manager.resize(*manager.window.maxsize())
elif platform.system() == 'Windows':
manager.window.state('zoomed')
elif plt.get_backend() == 'Qt5Agg':
if platform.system() == 'Linux':
manager.window.showMaximized()
else:
print('ERROR: different Matplotlib backend detected!')
Our image is static at this point; if we were to click on it nothing would happen. We need to enable plot interaction by using plt.ion()
which will mean that interactive mode is on (plt.ioff()
would turn it off):
plt.ion()
Finally, show the image:
plt.show()
What we want to do now is be able to click on the image and record the x- and y-coordinates of the clicks. Let’s initialise a list to store that information and use plt.ginput()
to prompt the user for two clicks worth of graphical input:
# Click and get click locations
click_locations = []
number = 2
if number == 1:
print(f'Click on the graph once')
else:
print(f'Click on the graph {number} times')
click_locations.extend(plt.ginput(number))
## Click on the graph 2 times
Save the list of the click locations to an external text file:
filename = 'Click Locations.txt'
with open(filename, 'w') as file:
json.dump(click_locations, file)
Plot the image and the click locations on top of the existing image:
plt.imshow(img)
plt.xticks([])
plt.yticks([])
print('Click locations:')
for click_location in click_locations:
print(click_location)
plt.plot(click_location[0], click_location[1], 'r+')
# Maximise window
manager = plt.get_current_fig_manager()
if plt.get_backend() == 'TkAgg':
manager = plt.get_current_fig_manager()
if platform.system() == 'Linux':
manager.resize(*manager.window.maxsize())
elif platform.system() == 'Windows':
manager.window.state('zoomed')
elif plt.get_backend() == 'Qt5Agg':
if platform.system() == 'Linux':
manager.window.showMaximized()
else:
print('ERROR: different matplotlib backend detected!')
# Disable plot interaction
plt.ioff()
# Show image
plt.show()
## Click locations:
## (117.95930425766653, 106.80037618471599)
## (170.8976657937763, 61.339184357096315)
The two places where I clicked on the image are shown as red crosses.