felzenszwalb segmentations

gistfile1.txt

import glob
import skimage
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import glob

import matplotlib.pyplot as plt
import numpy as np

from skimage.segmentation import felzenszwalb, slic, quickshift, watershed
from skimage.segmentation import mark_boundaries
from skimage.util import img_as_float

from scipy import ndimage as nd
from skimage import feature

rgbs = glob.glob("*.jpeg")

rgbs = sorted(rgbs)
import PIL

import re

def natural_sort(l): 
    convert = lambda text: int(text) if text.isdigit() else text.lower() 
    alphanum_key = lambda key: [ convert(c) for c in re.split('([0-9]+)', key) ] 
    return sorted(l, key = alphanum_key)

for rgb_name in rgbs:
    rgb = np.array(PIL.Image.open(rgb_name))
    fig = plt.figure(figsize=(18,9))
    ax1 = fig.add_subplot(1, 2, 1)
    ax2 = fig.add_subplot(1, 2, 2)
    ax1.imshow(rgb)
    print(rgb_name)
    segments_fz = felzenszwalb(rgb, scale=100, sigma=1.5, min_size=150)  #min_size=150, sigma=1.5
    ax2.imshow(mark_boundaries(rgb, segments_fz))
    plt.title("Felzenszwalb Segments {}".format(np.unique(segments_fz).shape[0]))
    plt.savefig(rgb_name+"_segments.png", dpi=150, transparent=True, bbox_inches='tight')
    plt.close()