old_contents: import argparse
  import pandas as pd
  import skimage.io
  import skimage.color
  import warnings
  
  def get_pixel_values(im, pixel_table, white_obj, threshold, offset=[0,0]):
      data = skimage.io.imread(im)
      if len(data.shape) == 3 and data.shape[-1] > 1:
          data = skimage.color.rgb2grey(data)
      x = []
      y = []
      img_height = data.shape[0]
      img_width = data.shape[1]
      for j in range(img_width):
          for i in range(img_height):
              if white_obj == False:
                  if data[i,j] <= threshold:
                      x.append(j + offset[0])
                      y.append(img_height-(i+1) + offset[1])
              elif data[i,j] >= threshold:
                      x.append(j + offset[0])
                      y.append(img_height-(i+1) + offset[1])
                      
      df = pd.DataFrame()
      df['x'] = x
      df['y'] = y
      df.to_csv(pixel_table, sep="\t", index = False)
                       
  if __name__=="__main__":
      parser = argparse.ArgumentParser(description = "Create a csv table with Coordinates of the ROI")
      parser.add_argument("im", help = "Paste path to out.png (output created by transformation)")
      parser.add_argument("pixel_table", help = "Paste path to file in which list with all pixles > threshold should be saved")
      parser.add_argument('offset_x', type=int, help='offset in x direction (width)', default=0)
      parser.add_argument('offset_y', type=int, help='offset in y direction (height)', default=0)
      parser.add_argument("--white_obj", dest = "white_obj", default=False, help = "If set objects in image are white otherwise black", action = "store_true")
      parser.add_argument("--threshold", dest = "threshold", default = 0.5, help = "Enter desired threshold value", type = float)
      
      args = parser.parse_args()  
      # with warnings.catch_warnings():
  	#     warnings.simplefilter("ignore") 
      get_pixel_values(args.im, args.pixel_table, args.white_obj, args.threshold, [args.offset_x, args.offset_y])     
  
new_contents: import argparse
  import pandas as pd
  import skimage.io
  import skimage.color
  import warnings
  
  def get_pixel_values(im, pixel_table, white_obj, threshold, offset=[0,0]):
      data = skimage.io.imread(im)
      if len(data.shape) == 3 and data.shape[-1] > 1:
          data = skimage.color.rgb2grey(data)
      x = []
      y = []
      img_height = data.shape[0]
      img_width = data.shape[1]
      for j in range(img_width):
          for i in range(img_height):
              if white_obj == False:
                  if data[i,j] <= threshold:
                      x.append(i + offset[0])
                      y.append(j + offset[1])
              elif data[i,j] >= threshold:
                      x.append(i + offset[0])
                      y.append(j + offset[1])
                      
      df = pd.DataFrame()
      df['x'] = x
      df['y'] = y
      df.to_csv(pixel_table, sep="\t", index = False)
                       
  if __name__=="__main__":
      parser = argparse.ArgumentParser(description = "Create a csv table with Coordinates of the ROI")
      parser.add_argument("im", help = "Paste path to out.png (output created by transformation)")
      parser.add_argument("pixel_table", help = "Paste path to file in which list with all pixles > threshold should be saved")
      parser.add_argument('offset_x', type=int, help='offset in x direction (width)', default=0)
      parser.add_argument('offset_y', type=int, help='offset in y direction (height)', default=0)
      parser.add_argument("--white_obj", dest = "white_obj", default=False, help = "If set objects in image are white otherwise black", action = "store_true")
      parser.add_argument("--threshold", dest = "threshold", default = 0.5, help = "Enter desired threshold value", type = float)
      
      args = parser.parse_args()  
      # with warnings.catch_warnings():
  	#     warnings.simplefilter("ignore") 
      get_pixel_values(args.im, args.pixel_table, args.white_obj, args.threshold, [args.offset_x, args.offset_y])     
  
subject: revert switching of x and y axis