import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import numpy as np
from skimage.filters import threshold_otsu
from skimage.segmentation import clear_border
from skimage.measure import label, regionprops
from skimage.morphology import opening, closing, square
from skimage.color import label2rgb
from skimage.color import rgb2gray

image = rgb2gray(plt.imread('strongi.jpg'))[100:-100, 100:-100]

# apply threshold
thresh = threshold_otsu(image)
#closing
bw = closing(image > thresh, square(3))
#opening
bww = opening(bw, square(3))

# remove artifacts connected to image border
cleared = clear_border(bww)

# label image regions
cmap = plt.get_cmap("tab20")
cmaps=np.array([cmap(i) for i in range(cmap.N)])
label_image = label(cleared)
image_label_overlay = label2rgb(label_image,colors=cmaps, image=image)

fig, ax = plt.subplots(figsize=(8, 6))
ax.imshow(image_label_overlay)

for region in regionprops(label_image):
    # take regions with large enough areas
    if region.area >= 100:
        # draw rectangle around segmented coins
        minr, minc, maxr, maxc = region.bbox
        rect = mpatches.Rectangle((minc, minr), maxc - minc, maxr - minr,
                                  fill=False, edgecolor='g', linewidth=3)
        ax.add_patch(rect)

ax.set_axis_off()
plt.savefig('plot_label.jpg',dpi=100)
plt.show()

properties=regionprops(label_image)
area=np.array([prop.area for prop in properties])
label=np.array([prop.label for prop in properties])
centroid=np.array([prop.centroid for prop in properties])

area[area>100]
#array([1457, 2554, 3155, 1579, 1315, 2929, 3919, 2849, 3943, 3706])

label[area>100]
#array([ 4,  6,  7,  8,  9, 16, 19, 20, 24, 26])

centroid[area>100]
"""
array([[ 77.65339739, 299.37062457],
       [132.5082224 , 149.93970243],
       [137.55847861, 250.30174326],
       [144.00379987,  78.81697277],
       [157.08745247, 316.88365019],
       [221.82963469, 184.11266644],
       [242.8532789 ,  86.42817045],
       [242.07827308, 292.95998596],
       [299.91732184, 188.02967284],
       [323.8440367 , 273.36022666]])
"""

img_c = plt.imread('strongi.jpg')[100:-100, 100:-100]
sabos=[]
for region in regionprops(label_image):
    if region.area >= 100:
        minr, minc, maxr, maxc = region.bbox
        sabo = img_c[minr:maxr,minc:maxc,:]
        sabos.append(sabo)

from mpl_toolkits.axes_grid1 import ImageGrid
fig = plt.figure(figsize=(8, 6))
grid = ImageGrid(fig, 111,
                 nrows_ncols=(2, 5),
                 axes_pad=0.2,
                 share_all=True,
                 )
for i in range(len(sabos)):
           grid[i].imshow(sabos[i])
           grid[i].axis('off')
           grid[i].set_title('label='+str(label[area>100][i])+'')
plt.savefig('plot_label_cactus.jpg',dpi=123)