Most efficient way of displaying jpgs with bokeh? Image_rgba surprisingly slow - bokeh

Question

I've tried using the bokeh image_rgba method but found it to be very slow, I'm just displaying a 1000*500 px image and the html takes ~5 seconds to load (nothing is web based here, I have everything running/stored locally)
Again the code itself runs fast, itùs just displaying the image thqt is slow. I've been trying exqmples from the bokeh gallery and the speed is fine.
I'm thus wondering if there is anything I could do for the html to load faster? Is image_rgba the best way to go to display an image with bokeh?
This is the code I use:
pic = PIL.Image.open('/Users/blabla/eiffelTower.jpg')
self.imgArray = np.array(pic)
N1 = imgArray.shape[0]
N2 = imgArray.shape[1]
img = np.zeros((N1,prolongatedN2), dtype=np.uint32)
view = img.view(dtype=np.uint8).reshape((N1, N2, 4))
view[:N1,:N2,0] = self.imgArray[range(N1-1,-1,-1),:N2,0]
view[:N1,:N2,1] = self.imgArray[range(N1-1,-1,-1),:N2,1]
view[:N1,:N2,2] = self.imgArray[range(N1-1,-1,-1),:N2,2]
fig = bokeh.plotting.figure(plot_width = plot_width, plot_height=plot_height)
fig.image_rgba(image=[img], x=[0], y=[0],
dw=[plot_width], dh=[plot_height])
script, div = bokeh.embed.components(p.fig, INLINE)
output_file('testBokeh.html')
show(fig)
Again I'm quite surprised that displaying a locally stored 1000*500 pixels would be so slow.

Answer 1

FWIW, I do this, and it's very fast.
from __future__ import division
import numpy as np
from PIL import Image
from bokeh.plotting import figure, show, output_file
# Open image, and make sure it's RGB*A*
lena_img = Image.open('Lenna_rect.png').convert('RGBA')
xdim, ydim = lena_img.size
print("Dimensions: ({xdim}, {ydim})".format(**locals()))
# Create an array representation for the image `img`, and an 8-bit "4
# layer/RGBA" version of it `view`.
img = np.empty((ydim, xdim), dtype=np.uint32)
view = img.view(dtype=np.uint8).reshape((ydim, xdim, 4))
# Copy the RGBA image into view, flipping it so it comes right-side up
# with a lower-left origin
view[:,:,:] = np.flipud(np.asarray(lena_img))
# Display the 32-bit RGBA image
dim = max(xdim, ydim)
fig = figure(title="Lena",
x_range=(0,dim), y_range=(0,dim),
# Specifying xdim/ydim isn't quire right :-(
# width=xdim, height=ydim,
)
fig.image_rgba(image=[img], x=0, y=0, dw=xdim, dh=ydim)
output_file("lena.html", title="image example")
show(fig) # open a browser