Image manipulation using mpl for @stefanv.

sample.py

"""
Example of applying text to an image for Stefan VdW.

The image is not transfomed throgh the mpl pipeline, and is instead
constrained to pixel space of the figure's resulting image.

"""

def new_figure(width, height):
    """
    Creates a figure, outside of the PyPlot interface, which can draw mpl
    components on top of an image.
    
    """
    from matplotlib.backends.backend_agg import FigureCanvasAgg
    from matplotlib.figure import Figure
    
    fig = Figure(figsize=(width / 100., height / 100.), dpi=100)
    # Create the canvas for the figure (which gets attached to the
    # figure inside the constructor.
    FigureCanvasAgg(fig)
    return fig


def figure_image(figure, image):
    """Adds a FirgureImage instance to a figure.
    
    A FigureImage is an image which is not transformed in the mpl
    stack, and so its pixels are 1-to-1 with the final figure. If the
    final figure is not of the **exact** size of the image, parts of the
    image will either be cropped, or parts of the figure will be empty.
    
    """
    from matplotlib.image import FigureImage
    figimg = FigureImage(figure)
    figimg.set_array(image)
    figure.images.append(figimg)
    return figimg


def verify(new_img, old_img):
    import matplotlib.pyplot as plt
    plt.switch_backend('tkagg')
    fig, axes = plt.subplots(3, 3, sharex=True, squeeze=True, sharey=True)
    axes[0, 0].set_title('Original')
    axes[0, 1].set_title('New')
    axes[0, 2].set_title('Diff (0 masked)')

    axes[0, 0].set_ylabel('Red')
    axes[1, 0].set_ylabel('Green')
    axes[2, 0].set_ylabel('Blue')

    for channel in range(3):
        axes[channel, 0].imshow(old_img[:, :, channel], interpolation='none')
        axes[channel, 1].imshow(new_img[:, :, channel], interpolation='none')
        diff = img[:, :, channel] - new_img[:, :, channel]
        diff = np.ma.masked_equal(diff, 0)
        axes[channel, 2].imshow(diff)
    plt.show()


if __name__ == '__main__':
    from skimage.data import lena
    
    img = lena()
    width, height = img.shape[:2]
    
    # Create a new figure. This can either be with PyPlot (with the right 
    # dpi etc.) or just by calling the utility function.
    fig = new_figure(width, height)
    # fig = plt.figure(figsize=(width / 100., height / 100.), dpi=100)


    figure_image(fig, img)

    # Do whatever we want on the figure (a transform=None) will give us
    # pixel coordinates from the **bottom left** of the figure.
    text = fig.text(200, 100, 'Hello Lena', size=20)
    text.set_transform(None)

    # We can pump this to a file.
    fig.savefig('out.png', dpi=100)
    # Or get hold of it as an array.
    import numpy as np
    import numpy.ma
    new_img = np.array(fig.canvas.buffer_rgba()).reshape([width, height, 4])


    verify(new_img, img)

@stefanv - threw this together on the train. I'm not sure what's going on with the red channel - looks like the image itself is being modified which is unexpected.

HTH