Matplotlib figure to image as a numpy array

Question

I’m trying to get a numpy array image from a Matplotlib figure and I’m currently doing it by saving to a file, then reading the file back in, but I feel like there has to be a better way. Here’s what I’m doing now:

from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure

fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.gca()

ax.text(0.0,0.0,"Test", fontsize=45)
ax.axis('off')

canvas.print_figure("output.png")
image = plt.imread("output.png")

I tried this:

image = np.fromstring( canvas.tostring_rgb(), dtype='uint8' )

from an example I found but it gives me an error saying that ‘FigureCanvasAgg’ object has no attribute ‘renderer’.

Asked By: John Stanford

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Source

Answer 1

In order to get the figure contents as RGB pixel values, the matplotlib.backend_bases.Renderer needs to first draw the contents of the canvas. You can do this by manually calling canvas.draw():

from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure

fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.gca()

ax.text(0.0,0.0,"Test", fontsize=45)
ax.axis('off')

canvas.draw()       # draw the canvas, cache the renderer

image = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')

See here for more info on the Matplotlib API.

Answered By: ali_m

Answer 2

from the docs:

https://matplotlib.org/gallery/user_interfaces/canvasagg.html#sphx-glr-gallery-user-interfaces-canvasagg-py

fig = Figure(figsize=(5, 4), dpi=100)
# A canvas must be manually attached to the figure (pyplot would automatically
# do it).  This is done by instantiating the canvas with the figure as
# argument.
canvas = FigureCanvasAgg(fig)

# your plotting here

canvas.draw()
s, (width, height) = canvas.print_to_buffer()

# Option 2a: Convert to a NumPy array.
X = np.fromstring(s, np.uint8).reshape((height, width, 4))

Answered By: MrE

Answer 3

For people who are searching an answer for this question, this is the code gathered from previous answers. Keep in mind that the method np.fromstring is deprecated and np.frombuffer is used instead.

#Image from plot
ax.axis('off')
fig.tight_layout(pad=0)

# To remove the huge white borders
ax.margins(0)

fig.canvas.draw()
image_from_plot = np.frombuffer(fig.canvas.tostring_rgb(), dtype=np.uint8)
image_from_plot = image_from_plot.reshape(fig.canvas.get_width_height()[::-1] + (3,))

Answered By: Jorge Diaz

Answer 4

To fix the large margins Jorge references, add ax.margins(0). See here for details.

Answered By: cdw

Answer 5

I think there is some update, which is easier.

canvas.draw()
buf = canvas.buffer_rgba()
X = np.asarray(buf)

Updated version from the docs:

from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.figure import Figure
import numpy as np

# make a Figure and attach it to a canvas.
fig = Figure(figsize=(5, 4), dpi=100)
canvas = FigureCanvasAgg(fig)

# Do some plotting here
ax = fig.add_subplot(111)
ax.plot([1, 2, 3])

# Retrieve a view on the renderer buffer
canvas.draw()
buf = canvas.buffer_rgba()
# convert to a NumPy array
X = np.asarray(buf)

Answered By: starriet

Matplotlib figure to image as a numpy array

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