In [1]:
import numpy as np
import pandas as pd
import math
import cv2
import argparse
import imutils
import os
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.patches as patches
import matplotlib.colors as colors
import matplotlib.image as mpimg
from sklearn import decomposition
from sklearn.preprocessing import normalize
from sklearn.metrics import mean_squared_error
from sklearn.neighbors import NearestNeighbors
from skimage import data, io, filters,measure
from skimage.feature import match_template
import scipy
from scipy.ndimage.interpolation import shift
from scipy import ndimage,spatial
from scipy.optimize import leastsq, minimize
import scipy.ndimage.filters as filters
from IPython.display import display, HTML
from PIL import Image
import PIL.ImageOps
from imutils import contours
import re
In [24]:
directory = "/home/janekg89/Develop/Pycharm_Projects/flutype_webapp/master_uncomplete/collections/170725_E8/"
for fname in os.listdir(directory): # change directory as needed
if os.path.isfile(directory+'/{}'.format(fname)):# make sure it's a file, not a directory entry
if ".tif" in fname: # search for string
r = re.compile('(.*?).tif')
m = r.search(fname)
name = m.group(1)
print(name)
image = Image.open(directory+'/{}'.format(fname))
if name == "E8_ nach quenchen_inkubiert_24h waschen_ 400_100_alle farben.tif":
image.seek(1)
if name == "E8_ nach quenchen_ 500_50_alle farben":
image.seek(2)
image = image.convert(mode='1')
image.save(directory+m.group(1)+"1"+".jpg", "JPEG")
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