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'.

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.

Answer 2

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,))