#!/usr/bin/env python
# coding: utf-8

# # Image Manipulation with skimage

# This example builds a simple UI for performing basic image manipulation with [scikit-image](http://scikit-image.org/).

# In[ ]:


from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display


# In[ ]:


import skimage
from skimage import data, filter, io


# In[ ]:


i = data.coffee()


# In[ ]:


io.Image(i)


# In[ ]:


def edit_image(image, sigma=0.1, r=1.0, g=1.0, b=1.0):
    new_image = filter.gaussian_filter(image, sigma=sigma, multichannel=True)
    new_image[:,:,0] = r*new_image[:,:,0]
    new_image[:,:,1] = g*new_image[:,:,1]
    new_image[:,:,2] = b*new_image[:,:,2]
    new_image = io.Image(new_image)
    display(new_image)
    return new_image


# In[ ]:


lims = (0.0,1.0,0.01)
w = interactive(edit_image, image=fixed(i), sigma=(0.0,10.0,0.1), r=lims, g=lims, b=lims)
display(w)


# In[ ]:


w.result


# ## Python 3 only: Function annotations

# In Python 3, you can use the new function annotation syntax to describe widgets for interact:

# In[ ]:


lims = (0.0,1.0,0.01)

@interact
def edit_image(image: fixed(i), sigma:(0.0,10.0,0.1)=0.1, r:lims=1.0, g:lims=1.0, b:lims=1.0):
    new_image = filter.gaussian_filter(image, sigma=sigma, multichannel=True)
    new_image[:,:,0] = r*new_image[:,:,0]
    new_image[:,:,1] = g*new_image[:,:,1]
    new_image[:,:,2] = b*new_image[:,:,2]
    new_image = io.Image(new_image)
    display(new_image)
    return new_image