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Interactive pixel information of an image in Python?



Short version: is there a Python method for displaying an image which shows, in real time, the pixel indices and intensities? So that as I move the cursor over the image, I have a continually updated display such as pixel[103,214] = 198 (for grayscale) or pixel[103,214] = (138,24,211) for rgb?

Long version:

Suppose I open a grayscale image saved as an ndarray im and display it with imshow from matplotlib:

im = plt.imread('image.png')

What I get is the image, and in the bottom right of the window frame, an interactive display of the pixel indices. Except that they're not quite, as the values are not integers: x=134.64 y=129.169 for example.

If I set the display with correct resolution:


the x and y values are still not integers.

The imshow method from the spectral package does a better job:

import spectral as spc

Then in the bottom right I now have pixel=[103,152] for example.

However, none of these methods also shows the pixel values. So I have two questions:

  1. Can the imshow from matplotlib (and the imshow from scikit-image) be coerced into showing the correct (integer) pixel indices?
  2. Can any of these methods be extended to show the pixel values as well?
python image image-processing matplotlib scikit-image
  this question
asked Dec 30 '14 at 11:19 Alasdair 386 3 14


2 Answers

There a couple of different ways to go about this.

You can monkey-patch ax.format_coord, similar to this official example. I'm going to use a slightly more "pythonic" approach here that doesn't rely on global variables. (Note that I'm assuming no extent kwarg was specified, similar to the matplotlib example. To be fully general, you need to do a touch more work.)

import numpy as np
import matplotlib.pyplot as plt

class Formatter(object):
    def __init__(self, im): = im
    def __call__(self, x, y):
        z =[int(y), int(x)]
        return 'x={:.01f}, y={:.01f}, z={:.01f}'.format(x, y, z)

data = np.random.random((10,10))

fig, ax = plt.subplots()
im = ax.imshow(data, interpolation='none')
ax.format_coord = Formatter(im)

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  this qu

Alternatively, just to plug one of my own projects, you can use mpldatacursor for this. If you specify hover=True, the box will pop up whenever you hover over an enabled artist. (By default it only pops up when clicked.) Note that mpldatacursor does handle the extent and origin kwargs to imshow correctly.

import numpy as np
import matplotlib.pyplot as plt
import mpldatacursor

data = np.random.random((10,10))

fig, ax = plt.subplots()
ax.imshow(data, interpolation='none')

mpldatacursor.datacursor(hover=True, bbox=dict(alpha=1, fc='w'))

Also, I forgot to mention how to show the pixel indices. In the first example, it's just assuming that i, j = int(y), int(x). You can add those in place of x and y, if you'd prefer.

With mpldatacursor, you can specify them with a custom formatter. The i and j arguments are the correct pixel indices, regardless of the extent and origin of the image plotted.

For example (note the extent of the image vs. the i,j coordinates displayed):

import numpy as np
import matplotlib.pyplot as plt
import mpldatacursor

data = np.random.random((10,10))

fig, ax = plt.subplots()
ax.imshow(data, interpolation='none', extent=[0, 1.5*np.pi, 0, np.pi])

mpldatacursor.datacursor(hover=True, bbox=dict(alpha=1, fc='w'),
                         formatter='i, j = {i}, {j}\nz = {z:.02g}'.format)

  this answer
edited Dec 30 '14 at 16:37 answered Dec 30 '14 at 15:01 Joe Kington 131k 19 315 317      Duplicate of… and links there in. I think this is a better answer than any of the other ones. Can you mark all of them as duplicates of this one (I have already voted on most of them before I had 1-vote duplicate close)? –  tacaswell Dec 30 '14 at 16:55      And can you put in a PR to change the official example to use the Formatter class? –  tacaswell Dec 30 '14 at 16:56      @tcaswell - Done on the close votes. (And thanks!) If any of those seem significantly different from this question, feel free to re-open them. I'll put in a PR for the example later tonight. –  Joe Kington Dec 30 '14 at 17:29      Is mpldatacursor supposed to work for two subplots? I tried and got very strange results. I get a cursor box simultaneously over both subplots. –  Yonatan Simson Mar 31 '15 at 11:43 1   @YonatanSimson - Yes, it should work. However, I think your problem might be related to a bug I just fixed a couple of days ago:… If you have a chance, you might try reinstalling from the current github master. Sorry about that! –  Joe Kington Apr 1 '15 at 18:43  |  show more comments

All of the examples that I have seen only work if your x and y extents start from 0. Here is code that uses your image extents to find the z value.

import numpy as np
import matplotlib.pyplot as plt

fig, ax = plt.subplots()

d = np.array([[i+j for i in range(-5, 6)] for j in range(-5, 6)])
im = ax.imshow(d)
im.set_extent((-5, 5, -5, 5))

def format_coord(x, y):
    """Format the x and y string display."""
    imgs = ax.get_images()
    if len(imgs) > 0:
        for img in imgs:
                array = img.get_array()
                extent = img.get_extent()

                # Get the x and y index spacing
                x_space = np.linspace(extent[0], extent[1], array.shape[1])
                y_space = np.linspace(extent[3], extent[2], array.shape[0])

                # Find the closest index
                x_idx= (np.abs(x_space - x)).argmin()
                y_idx= (np.abs(y_space - y)).argmin()

                # Grab z
                z = array[y_idx, x_idx]
                return 'x={:1.4f}, y={:1.4f}, z={:1.4f}'.format(x, y, z)
            except (TypeError, ValueError):
        return 'x={:1.4f}, y={:1.4f}, z={:1.4f}'.format(x, y, 0)
    return 'x={:1.4f}, y={:1.4f}'.format(x, y)
# end format_coord

ax.format_coord = format_coord

If you are using PySide/PyQT here is an example to have a mouse hover tooltip for the data

import matplotlib
matplotlib.rcParams["backend.qt4"] = "PySide"
import matplotlib.pyplot as plt

fig, ax = plt.subplots()

# Mouse tooltip
from PySide import QtGui, QtCore
mouse_tooltip = QtGui.QLabel()

def show_tooltip(msg):
    msg = msg.replace(', ', '\n')

    pos = QtGui.QCursor.pos()
    mouse_tooltip.move(pos.x()+20, pos.y()+15)

# Show the plot

  this answer
answered Oct 5 '16 at 22:42 HashSplat 2,056 1 7 19


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