content: #https://github.com/tflearn/tflearn/issues/180
  from __future__ import division, print_function, absolute_import
  
  import tflearn
  from tflearn.data_utils import shuffle, to_categorical
  from tflearn.layers.core import input_data, dropout, fully_connected
  from tflearn.layers.conv import conv_2d, max_pool_2d
  from tflearn.layers.normalization import local_response_normalization, batch_normalization
  from tflearn.layers.estimator import regression
  from tflearn.data_utils import image_preloader
  import skimage
  from skimage import data
  from skimage import filters
  import os
  from skimage import io
  import numpy as np
  from scipy import ndimage
  import matplotlib.pyplot as plt
  
  reds="../images/pictures/red/"
  greens="../images/pictures/green/"
  redshist="../images/histograms/red/"
  greenshist="../images/histograms/green/"
  directory=reds
  histdirectory=redshist
  for filename in os.listdir(directory):
      if filename.endswith(".jpg"): 
  	img = io.imread(os.path.join(directory, filename))
  	hist, bin_edges = np.histogram(img, bins=255)
  	bin_centers = 0.5*(bin_edges[:-1] + bin_edges[1:])
  	binary_img = img > 0.8
  	plt.figure(figsize=(1,1))
  	fig, ax = plt.subplots(nrows=1, ncols=1) #http://stackoverflow.com/questions/9622163/save-plot-to-image-file-instead-of-displaying-it-using-matplotlib-so-it-can-be
  	plt.plot(bin_centers, hist, lw=2)
  	fig.savefig(os.path.join(histdirectory, filename), bbox_inches='tight')
  	plt.close()
      else:
          continue
  