#!/Users/CiderBones/anaconda3/bin/python

# Testing out scikit-image with a scanned fluorescent maize ear

import numpy as np
import matplotlib.pyplot as plt
from skimage import io
from skimage.filters import sobel
from skimage.color import rgb2gray

# Importing the image as a numpy array
maize = io.imread('/Users/CiderBones/Desktop/Laboratory/computer_vision/scikit-image/X402x498-2m1.png')

# Testing to see if the image imported properly; it looks like it did.
print(type(maize))
print(maize.shape)

# Converting the image to grayscale
maize_grayscale = rgb2gray(maize)

# Something's wrong with the histogram: after converting it to grayscale
# everything's at 0.
hist = np.histogram(maize_grayscale, bins=np.arange(0, 256))

# Puts the image into some kind of cache that can be show with plt.show()
# io.imshow(maize_grayscale)

fig, axes = plt.subplots(1, 2, figsize=(8, 3))
axes[0].imshow(maize_grayscale, cmap=plt.cm.gray, interpolation='nearest')
axes[0].axis('off')
axes[1].plot(hist[1][:-1], hist[0], lw=2)
axes[1].set_title('histogram of gray values')

# Shows both the original image and the histogram of gray values. Not sure how to
# remove an images once it's in the cache from imshow(). For some reason this is
# showing both the maize ear and the maize ear plus the histogram. Actually I think
# I see in line 29 where it's adding both to the same line.
plt.show()


# Doing some region-based segmentation

elevation_map = sobel(maize_grayscale)
fig, ax = plt.subplots(figsize=(4, 3))
ax.imshow(elevation_map, cmap=plt.cm.gray, interpolation='nearest')
ax.set_title('elevation map')
ax.axis('off')

plt.show()


# Finding markers of the background and the kernels based on extreme parts of the
# histogram of gray values. Not sure what that means. Not working, maybe tied to
# the histogram not working?
markers = np.zeros_like(maize_grayscale)
markers[maize_grayscale < 30] = 1
markers[maize_grayscale > 150] = 2

fig, ax = plt.subplots(figsize=(4, 3))
ax.imshow(markers, cmap=plt.cm.nipy_spectral, interpolation='nearest')
ax.set_title('markers')
ax.axis('off')

plt.show()