def run_clean_up(folder):
debug_mode = True
mylog = Logger("Clean up",
folder + "main_logfile.txt",
debug_mode=debug_mode)
mylog.log("clean up for folder: ")
mylog.log(folder)
avg = AvgFolderMem(folder)
subfolders = ["processed_images", "aligned_images", "correlation_images"]
for subfolder in subfolders:
mylog.log("Cleaned: " + subfolder)
shutil.rmtree(avg.subfolders[subfolder])
# py imports
# My imports
from AvgFolder_class import AvgFolderMem
# Flat Field correction manager
if __name__ == "__main__":
# gather dark field
pathdfh = "../../../darkfield/horizontal/"
# average pictures
dfh = AvgFolderMem(pathdfh)
dfh.gather_pictures()
dfh.c2gscale()
dfh.squareit()
dfh.binning(2)
dfh.average(aligned=False, debug=True)
dfh.save_avg()
dfh.avg.show_image()
plt.show()
pathtodataset = "../../../silentcam/dataset36/"
avg = AvgFolderMem(pathtodataset)
def run_average_gray(folder):
# options
debug_mode = True
# chose path to image sequence folder
datasetpath = folder
memsave = True # True | False
preprocop = [("convert to grayscale", ), ("square it", ), ("binning", 0),
("transpose", ), ("normalize", )]
custom_template = False # True | False
template_image_path = folder + "template_folder/template.png" # path to image
auto_template_type = "UseFirstImage" # "Use First Image" | "Average"
save_template = True # True | False
align_images = True # True | False
align_mode = "fixed" # "fixed | tree" // fixed still fastest option
align_space = (-1, 1, 0.1) # (min angle, max angle, precision)
# logger
mylog = Logger("Averaging Gray",
datasetpath + "main_logfile.txt",
debug_mode=debug_mode)
mylog.log("Debug mode: " + "ON" if debug_mode == True else "OFF")
mylog.log("For the folder:")
mylog.log(datasetpath)
mylog.log("Averaging type: grey")
mylog.log("Memory saving mode: " + str(memsave))
mylog.log(
"------------------------------\nLoading dataset\n------------------------------"
)
if memsave:
avg = AvgFolderMem(datasetpath)
else:
avg = AvgFolder(datasetpath)
avg.gather_pictures()
# build the informatiosn
mylog.log("number of pictures:" + str(avg.init_imgs.n))
image = avg.init_imgs.get_image(0)
mylog.log("Size of images: " + str(image.data.shape[0]) + "x" +
str(image.data.shape[1]))
mylog.log("--- Start preporcessing ---", True)
nametofunc = {}
nametofunc[preprocop[0]] = lambda: avg.c2gscale()
nametofunc[preprocop[1]] = lambda: avg.squareit()
nametofunc[preprocop[2]] = lambda n: avg.binning(n)
nametofunc[preprocop[3]] = lambda: avg.transpose()
nametofunc[preprocop[4]] = lambda: avg.normalize()
for name in preprocop:
if len(name) == 1:
nametofunc[name]()
mylog.log("Process: " + name[0])
if len(name) == 2:
nametofunc[name](name[1])
mylog.log("Process: " + name[0] + "Arguments: " + str(name[1]))
mylog.log("Processing took: ", True)
mylog.log(
"------------------------------\nGenerating template\n------------------------------"
)
if custom_template:
custom_t = MyImage(template_image_path)
custom_t.convert2grayscale()
mylog.log("Template loaded from: " + template_image_path)
mylog.log("Template image is: {0}x{1}".format(custom_t.get_sizex(),
custom_t.get_sizey()))
avg.generate_template(custom_t)
else:
avg.generate_template(auto_template_type)
mylog.log("Template generated: " + auto_template_type)
mylog.log("Template generated", True)
if save_template:
avg.save_template()
if debug_mode:
avg.template.show_image()
plt.show()
avg.template.inspect()
if align_images:
mylog.log(
"------------------------------\nAlignment\n------------------------------"
)
mylog.log("Choosen Aligment: " + align_mode)
alignnames = ["min angle: ", " |max angle: ", " |precision: "]
mylog.log("".join(a + str(d) for a, d in zip(alignnames, align_space)))
avg.align_images(align_mode, align_space, debug_mode)
avg.save_shifts()
mylog.log("Alignment done", True)
if avg.anglestree != None:
mylog.log("Numnber of template generated: " +
str(len(avg.anglestree.angles_nodes)))
mylog.log("Normally would be: " + str(
len(np.arange(align_space[0], align_space[1], align_space[2])))
)
else:
mylog.log("Numnber of template generated: " +
str(avg.templaterotsft.n))
mylog.log("Shifts saved")
mylog.log(
"------------------------------\nAverage\n------------------------------"
)
avg.average(debug=debug_mode)
avg.save_avg()
mylog.log("Average Complete", True)
if debug_mode:
avg.avg.show_image()
plt.show()
avg.avg.inspect()
mylog.log("End procedure", True)
def __init__(self, root, path):
# main path
self.mpath = path
# create main frame
self.mframe = Frame(root)
self.mframe.image = {}
self.consoleframe = Frame(self.mframe)
self.consoleframe.grid(row=0, column=0, rowspan=2)
# add a beauty label
l = Label(self.consoleframe, text="Console:")
l.grid(row=0, column=0)
# create text box as a console
self.constext = ConsWidget(self.consoleframe)
self.constext.textbox.grid(row=1, column=0)
# use the averaging class to load the images from the folder
self.myavg = AvgFolderMem(self.mpath)
self.myavg.gather_pictures()
self.image_index = ConnectIndex(0)
self.max_images = self.myavg.init_imgs.n
titles = [
"Initial Images", "Processed Images", "Aligned Images",
"Corr Images"
]
positions = [(0, 1), (0, 3), (0, 4), (1, 2)]
myimgseqs = [
self.myavg.init_imgs, self.myavg.imgs, self.myavg.algimgs,
self.myavg.corrs
]
self.canvarr = []
for title, position, imgseq in zip(titles, positions, myimgseqs):
frame = Frame(self.mframe)
frame.grid(row=position[0], column=position[1])
mycanv = ImageCanvSeq(frame, imgseq, title, (256, 256), self.myavg,
self.constext)
mycanv.frame.pack()
self.canvarr.append(mycanv)
# create a text box
# give a canvas for the averaged image
self.avgimg = Frame(self.mframe)
self.avgimg.grid(row=0, column=5)
myimg = ImageCanv(self.avgimg, "Average", (256, 256), self.myavg,
self.constext)
myimg.cframe.grid(row=0, column=0)
pathtoavg = self.myavg.get_avg_path()
myimg.show_image(pathtoavg)
# give a canvas for the template images
self.templateimg = Frame(self.mframe)
self.templateimg.grid(row=1, column=1)
myimg = ImageCanv(self.templateimg, "Template", (256, 256), self.myavg,
self.constext)
myimg.cframe.grid(row=0, column=0)
pathtotemplate = self.myavg.get_template_path()
myimg.show_image(pathtotemplate)
# add the shift and angles
# buttons to control images together
bleft = Button(self.mframe, text="< conn", command=self.prev_pic)
bleft.grid(row=2, column=1)
bright = Button(self.mframe, text="conn >", command=self.next_pic)
bright.grid(row=2, column=3)
# create custom cross correlation
# create a button analyze correlation.
bcorr = Button(self.mframe, text="correlate", command=self.correlate)
bcorr.grid(row=2, column=2)