Commit e505d52d authored by Bryce Hepner's avatar Bryce Hepner
Browse files

trying to find a good metric

parent 2bc3f4c7

ErrorImageCreator.py

+1 −1
Original line number Diff line number Diff line
@@ -90,7 +90,7 @@ def color_adjust(visual_array): 
if __name__ == "__main__":

    scenes = file_extractor("averaged_images(11)")

    images = image_extractor(scenes)

    list_dic = np.load("second_dic.npy", allow_pickle="TRUE")

    list_dic = np.load("second_dict.npy", allow_pickle="TRUE")

    bins = [21,32,48]

    print(images)

    encoded_string2 = bytes_to_bitstring(read_from_file(images[0][:-5] + "_Compressed.txt"))

FPNprojstart.py

0 → 100644
+104 −0
Original line number Diff line number Diff line 
from functools import singledispatchmethod

from cv2 import mean

import numpy as np

from WorkingPyDemo import *

from Remove_Noise import *

import pandas as pd

import statsmodels.api as sm

from matplotlib import pyplot as plt

from sklearn.metrics import mean_squared_error

# scenes = file_extractor("images")

# images = image_extractor(scenes)

# print(images)



scenes = remote_file_extractor("/media/elphel/NVME/lwir16-proc/te0607/scenes/")

images = remote_image_extractor(scenes)

# images = find_only_in_channel(images, "11")

sftp_client = setup_remote_sftpclient()

image_array = np.array(Image.open(sftp_client.open(images[250])))

# image_array = np.array(Image.open(images[250])).astype(np.uint16)

# print(image_array[0])

# print(images[0:5])

# print(image_array[0,0].dtype)

thebitstring = bytes_to_bitstring(image_array[0])

frame = thebitstring[84*8:88*8]

# print(int(frame,2))

otherframe = thebitstring[88*8:92*8]

# print(int(otherframe,2))

# print(image_array[0].astype(np.uint16))

# print(image_array[0,42])

# print(bin(image_array[0,0])[2:].zfill(16))

# for i in range(len(images)):

#     image_array = np.array(Image.open(images[i]))

#     print(image_array[0,91] - image_array[0,90])

# print(np.array(Image.open(images[100]))[0])

def uint16_array_to_bitstring(array):

    bitstring = ""

    for i in range(len(array)):

        bitstring += bin(array[i])[2:].zfill(16)

    return bitstring

def repopulate_array_with_bitstring(bitstring):

    array = []

    for i in range(0,len(bitstring),8):

        array.append(int(bitstring[i:i+8],2))

    return np.array(array)

def intarray_to_uint32(int_array):

    bitstring = ""

    # print(int_array)

    for i in range(len(int_array)):

        bitstring += bin(int_array[i])[2:].zfill(8)

    # print(bitstring)

    return int(bitstring,2)

# print(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[0:6])

frame_spacings = []

signaltonoise = []

information_array = np.zeros((len(images),3))

def celcius_to_kelvin(celcius):

    return celcius + 273.15



for i in range(len(images)):

    image_array = np.array(Image.open(sftp_client.open(images[i]))).astype(np.uint16)

    current_frame_count = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[84:88])

    frame_count_at_FFC = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[88:92])

    # signaltonoise.append(1/np.std(image_array[1:]))

    information_array[i,0] = current_frame_count - frame_count_at_FFC

    # information_array[i,-1] = 1/np.std(image_array[1:])

    information_array[i,-1] = mean_squared_error(image_array[1:],gaussian_filter(image_array[1:],sigma=.3))

    # print(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[76:77])

    # print("start")

    information_array[i,1] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[94:96]) - \

    celcius_to_kelvin(intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[162:166]))

    # information_array[i,2] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[96:98])

    # information_array[i,2] = celcius_to_kelvin(intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[162:166]))

    # information_array[i,4] = information_array[i,1] - information_array[i,2]

    # information_array[i,5] = information_array[i,1] - information_array[i,3]

    # information_array[i,4] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[170:174])

    # information_array[i,5] = intarray_to_uint32(repopulate_array_with_bitstring(uint16_array_to_bitstring(image_array[0]))[174:178])

    # frame_spacings.append(current_frame_count - frame_count_at_FFC)

# print(np.argmin(signaltonoise))

# print(np.argmax(signaltonoise))

# print(np.min(abs(np.array(frame_spacings))))

# print("middle")





mask = information_array[:,0] > 0

information_df = pd.DataFrame(information_array[mask],columns=["Frame_Spacing","Curr_Temp_Diff","Signal_to_Noise"])

information_df.to_csv("information_weird_array.csv")

# information_df = pd.read_csv("information_array.csv")

information_array = information_df.values

plt.scatter(information_array[:,0],information_array[:,-1],s=1)

plt.legend()

plt.xlabel("Frame_Spacing")

plt.ylabel("Signal_to_Noise")

plt.show()

print(np.max(information_array[:,0]))

print(information_array[-5:-1,0])



X = sm.add_constant(information_df.drop(["Signal_to_Noise"],axis=1))



y = information_df["Signal_to_Noise"]





end_result = sm.OLS(y,X).fit()

print(end_result.summary())

sftp_client.close()

FullTester.ipynb

+1 −1
Original line number Diff line number Diff line 
%% Cell type:code id: tags:



``` python

from WorkingPyDemo import *

from time import time

# import imageio

import png

```



%% Cell type:code id: tags:



``` python

scenes = file_extractor("images")

images = image_extractor(scenes)

print(len(images)) #

print(len(images))

newnamesforlater = []

file_sizes_new = []

file_sizes_old = []

list_dic = np.load("first_dict.npy", allow_pickle="TRUE")

bins = [21,32,48]

for i in range(len(images)):



    if images[i][-5:] == ".tiff":

        newname = images[i][:-5]

    else:

        newname = images[i][:-4]

    if images[i][-18:] != "Compressedlzw.tiff":

        newnamesforlater.append(newname + "_Compressed.txt")

    # with open(newname + "_Compressed.txt", 'wb') as f:

    #     f.write(inletters)

        file_sizes_new.append((os.path.getsize(newname + "_Compressed.txt")))

        file_sizes_old.append((os.path.getsize(newname + "RemovedFirstLine" + ".tif")))

        # file_sizes_old.append((os.path.getsize(newname + ".tiff")))

file_sizes_new.append(os.path.getsize("first_dict.npy"))

print(len(newnamesforlater))

print(np.sum(file_sizes_new)/np.sum(file_sizes_old))

```



%% Output



    263

    263

    0.4041666246254766



%% Cell type:code id: tags:



``` python

for i, filename in enumerate(images):

    newimage = Image.open(filename)

    newimage = np.array(newimage)

    newimage = newimage[1:]

    newimage = Image.fromarray(newimage)

    newimage.save(filename[:-5]+ "RemovedFirstLine" + ".tif")

```



%% Cell type:code id: tags:



``` python

print(file_sizes_new[214]/file_sizes_old[214])

print(np.max(file_sizes_new)/file_sizes_old[125])

print((np.sum([file_sizes_new[0:16]]))/np.sum(file_sizes_old[0:16]))

print((np.sum([file_sizes_new[0:16]]) + file_sizes_new[-1])/np.sum(file_sizes_old[0:16]))

print(np.sum(file_sizes_new)/np.sum(file_sizes_old))

print(np.sum(file_sizes_new[:-1])/np.sum(file_sizes_old))

print((np.sum([file_sizes_new[0]]))/np.sum(file_sizes_old[0]))

print((np.sum([file_sizes_new[0]])+ file_sizes_new[-1])/np.sum(file_sizes_old[0]))

```



%% Output



    0.3767853274384346

    0.4979190885485795

    0.39729075321671686

    0.4193614393682817

    0.4041666246254766

    0.4028289866441236

    0.3980978882715315

    0.7512288666965683



%% Cell type:code id: tags:



``` python

pngsizes = []

for i, filename in enumerate(images):

    newimage = Image.open(filename)

    newimage = np.array(newimage)

    newimage = newimage[1:].astype(np.uint16)

    with open(newnamesforlater[i][:-4] + ".png", 'wb') as f:

        writer = png.Writer(newimage.shape[1], newimage.shape[0], greyscale=True, bitdepth=16)

        writer.write(f, newimage)

    pngsizes.append(os.path.getsize(newnamesforlater[i][:-4] + ".png"))

print(np.sum(pngsizes)/np.sum(file_sizes_old))

# print(0.6485158723863795)

```



%% Output



    0.6097255182418949

    0.6485158723863795



%% Cell type:code id: tags:



``` python

pngsizes = []

for i in range(19,20):

    newimage = Image.open(images[i])

    print(np.array(newimage))

    newimage = (np.array(newimage) - np.min(newimage)).astype(int)

    # newimage = newimage[1:]

    with open(newnamesforlater[i][:-4] + ".png", 'wb') as f:

        writer = png.Writer(newimage.shape[1], newimage.shape[0], greyscale=True, bitdepth=16)

        writer.write(f, newimage)

    pngsizes.append(os.path.getsize(newnamesforlater[i][:-4] + ".png"))

print(np.sum(pngsizes)/file_sizes_old[19])

```



%% Output



    0.6493572339400003



%% Cell type:code id: tags:



``` python

print(os.path.getsize("1626032610_393963_0.xcf")/os.path.getsize("images/1626032610_393963/1626032610_393963_0.tiff"))

```



%% Output



    0.5676821409714287



%% Cell type:code id: tags:



``` python

print(os.path.getsize("1626032610_393963_0.png")/os.path.getsize("images/1626032610_393963/1626032610_393963_0.tiff"))

```



%% Output



    0.4855910784741866



%% Cell type:code id: tags:



``` python

for i, filename in enumerate(images):

    original = Image.open(filename)

    compressed = Image.open(newnamesforlater[i][:-4] + ".png")

    original = np.array(original)[1:]

    compressed = np.array(compressed)

    if not np.allclose(original, compressed):

        print(i)

```



%% Cell type:code id: tags:



``` python

print((np.sum(pngsizes))/np.sum(file_sizes_old))

print((np.sum(pngsizes) - np.sum(file_sizes_new))/np.sum(pngsizes))

```



%% Output



    0.6120739575336334

    0.33712836894440124



%% Cell type:code id: tags:



``` python

```



%% Cell type:code id: tags:



``` python

from PIL import TiffTags

TiffTags.LIBTIFF_CORE.add(318)

```



%% Cell type:code id: tags:



``` python

lwz_sizes = []

for i, filename in enumerate(images):

    newimage = Image.open(filename)

    newimage = np.array(newimage)

    newimage = newimage[1:].astype(np.uint16)

    newimage = Image.fromarray(newimage)

    newimage.save(newnamesforlater[i][:-4]+ "lzw" + ".tiff", compression='tiff_lzw', tiffinfo={317: 2})



    lwz_sizes.append(os.path.getsize(newnamesforlater[i][:-4]+ "lzw" + ".tiff"))

print(np.sum(lwz_sizes)/np.sum(file_sizes_old))

```



%% Output



    0.6169964597214944



%% Cell type:code id: tags:



``` python

lwz_sizes = []

for i in range(19,20):

    print(images[i])

    newimage = Image.open(images[i])

    newimage = np.array(newimage)

    newimage = newimage[1:]

    newimage = Image.fromarray(newimage)

    newimage.save(newnamesforlater[i][:-4]+ "lzw" + ".tiff", compression='tiff_lzw', tiffinfo={317: 2})



    lwz_sizes.append(os.path.getsize(newnamesforlater[i][:-4]+ "lzw" + ".tiff"))

print(np.sum(lwz_sizes)/np.sum(file_sizes_old))

```



%% Output



    images/1626032610_393963/NoInterference.tiff

    0.005975943965048414



%% Cell type:code id: tags:



``` python

print(np.sum(lwz_sizes)/file_sizes_old[19])

```



%% Output



    0.7888902959444759



%% Cell type:code id: tags:



``` python

print((np.sum(lwz_sizes) - np.sum(file_sizes_new))/np.sum(lwz_sizes))

```



%% Output



    0.34492564114323154



%% Cell type:code id: tags:



``` python

print(len(images))

for i, item in enumerate(images):

    # print(item[-18:])

    if item[-18:] == "Compressedlzw.tiff":

        os.remove(item)

scenes = file_extractor(folder_name)

images = image_extractor(scenes)

print(len(images))

```



%% Output



    526

    263



%% Cell type:code id: tags:



``` python

def all_image_extractor(scenes):

    """

    This function gives the list of all of the valid images

    Parameters:

        scenes (list): a list of all the files in the directory

    Returns:

        images (list): a list of all the images in the directory

    """

    image_folder = []

    for scene in scenes:

        files = os.listdir(scene)

        for file in files:

            if file[-7:] == "_6.tiff":

                continue

            else:

                image_folder.append(os.path.join(scene, file))

    return image_folder #returns a list of file paths to .tiff files in the specified directory given in file_extractor

```



%% Cell type:code id: tags:



``` python

all_files = all_image_extractor(scenes)

print(len(all_files))

for i, item in enumerate(all_files):

    # print(item[-18:])

    print(item[-21:])

    if item[-21:] == "RemovedFirstLine.tiff":

        os.remove(item)

scenes = file_extractor(folder_name)

all_files = all_image_extractor(scenes)

print(len(all_files))

```



%% Output



    1442

    13_Compressedlzw.tiff

    7803_3_Compressed.png

    7803_5_Compressed.png

    7803_1_Compressed.png

    _5_Compressedlzw.tiff

    803_14_Compressed.png

    2RemovedFirstLine.tif

    7803_8_Compressed.txt

    0RemovedFirstLine.tif

    _7_Compressedlzw.tiff

    4RemovedFirstLine.tif

    10_Compressedlzw.tiff

    033496_437803_11.tiff

    _0_Compressedlzw.tiff

    7803_8_Compressed.png

    3RemovedFirstLine.tif

    033496_437803_13.tiff

    6033496_437803_18.jp4

    7803_4_Compressed.txt

    7803_3_Compressed.txt

    _2_Compressedlzw.tiff

    803_10_Compressed.png

    803_15_Compressed.txt

    5RemovedFirstLine.tif

    7803_7_Compressed.png

    _8_Compressedlzw.tiff

    803_13_Compressed.txt

    7803_9_Compressed.png

    033496_437803_15.tiff

    9RemovedFirstLine.tif

    803_13_Compressed.png

    6033496_437803_19.jp4

    7803_1_Compressed.txt

    7803_2_Compressed.txt

    7803_5_Compressed.txt

    8RemovedFirstLine.tif

    4RemovedFirstLine.tif

    803_12_Compressed.txt

    033496_437803_12.tiff

    12_Compressedlzw.tiff

    803_11_Compressed.png

    6033496_437803_2.tiff

    _1_Compressedlzw.tiff

    803_12_Compressed.png

    803_14_Compressed.txt

    7803_0_Compressed.png

    _3_Compressedlzw.tiff

    6033496_437803_17.jp4

    7RemovedFirstLine.tif

    7803_7_Compressed.txt

    _9_Compressedlzw.tiff

    6033496_437803_1.tiff

    2RemovedFirstLine.tif

    1RemovedFirstLine.tif

    7803_4_Compressed.png

    7803_2_Compressed.png

    3RemovedFirstLine.tif

    11_Compressedlzw.tiff

    033496_437803_14.tiff

    7803_0_Compressed.txt

    6033496_437803_16.jp4

    6033496_437803_4.tiff

    5RemovedFirstLine.tif

    6033496_437803_8.tiff

    1RemovedFirstLine.tif

    6033496_437803_9.tiff

    033496_437803_10.tiff

    803_11_Compressed.txt

    0RemovedFirstLine.tif

    _4_Compressedlzw.tiff

    7803_9_Compressed.txt

    803_15_Compressed.png

    6033496_437803_3.tiff

    803_10_Compressed.txt

    6033496_437803_7.tiff

    14_Compressedlzw.tiff

    6033496_437803_5.tiff

    15_Compressedlzw.tiff

    6033496_437803_0.tiff

    963_13_Compressed.png

    11_Compressedlzw.tiff

    7RemovedFirstLine.tif

    2RemovedFirstLine.tif

    032610_393963_11.tiff

    _1_Compressedlzw.tiff

    1RemovedFirstLine.tif

    032610_393963_12.tiff

    _7_Compressedlzw.tiff

    3963_4_Compressed.txt

    3963_4_Compressed.png

    3963_5_Compressed.txt

    3963_1_Compressed.txt

    5RemovedFirstLine.tif

    6032610_393963_0.tiff

    _3_Compressedlzw.tiff

    3RemovedFirstLine.tif

    3963_7_Compressed.txt

    1RemovedFirstLine.tif

    3963_8_Compressed.txt

    963_14_Compressed.png

    13_Compressedlzw.tiff

    6032610_393963_8.tiff

    3963_9_Compressed.png

    963_15_Compressed.png

    4RemovedFirstLine.tif

    3963_2_Compressed.png

    10_Compressedlzw.tiff

    963_12_Compressed.png

    _2_Compressedlzw.tiff

    3963_7_Compressed.png

    963_10_Compressed.png

    963_15_Compressed.txt

    3963_0_Compressed.txt

    3/NoInterference.tiff

    9RemovedFirstLine.tif

    6032610_393963_9.tiff

    14_Compressedlzw.tiff

    963_13_Compressed.txt

    _4_Compressedlzw.tiff

    963_14_Compressed.txt

    032610_393963_13.tiff

    3963_5_Compressed.png

    2RemovedFirstLine.tif

    963_11_Compressed.txt

    3963_1_Compressed.png

    _0_Compressedlzw.tiff

    4RemovedFirstLine.tif

    032610_393963_15.tiff

    3963_9_Compressed.txt

    963_10_Compressed.txt

    6032610_393963_2.tiff

    5RemovedFirstLine.tif

    6032610_393963_3.tiff

    963_11_Compressed.png

    3963_2_Compressed.txt

    3963_8_Compressed.png

    3963_3_Compressed.txt

    _9_Compressedlzw.tiff

    12_Compressedlzw.tiff

    _8_Compressedlzw.tiff

    3963_3_Compressed.png

    6032610_393963_7.tiff

    032610_393963_14.tiff

    963_12_Compressed.txt

    0RemovedFirstLine.tif

    eRemovedFirstLine.tif

    0RemovedFirstLine.tif

    6032610_393963_5.tiff

    6032610_393963_4.tiff

    032610_393963_10.tiff

    8RemovedFirstLine.tif

    _5_Compressedlzw.tiff

    3RemovedFirstLine.tif

    6032610_393963_1.tiff

    15_Compressedlzw.tiff

    3963_0_Compressed.png

    477_11_Compressed.png

    _0_Compressedlzw.tiff

    6477_1_Compressed.png

    0843156_796477_1.tiff

    0843156_796477_2.tiff

    6477_2_Compressed.txt

    0843156_796477_8.tiff

    13_Compressedlzw.tiff

    3RemovedFirstLine.tif

    3RemovedFirstLine.tif

    4RemovedFirstLine.tif

    0843156_796477_7.tiff

    0843156_796477_4.tiff

    _8_Compressedlzw.tiff

    _2_Compressedlzw.tiff

    6477_4_Compressed.png

    6477_9_Compressed.txt

    477_10_Compressed.png

    7RemovedFirstLine.tif

    477_12_Compressed.txt

    6477_2_Compressed.png

    11_Compressedlzw.tiff

    4RemovedFirstLine.tif

    1RemovedFirstLine.tif

    843156_796477_12.tiff

    6477_8_Compressed.png

    8RemovedFirstLine.tif

    14_Compressedlzw.tiff

    5RemovedFirstLine.tif

    843156_796477_13.tiff

    477_14_Compressed.png

    6477_7_Compressed.png

    12_Compressedlzw.tiff

    _7_Compressedlzw.tiff

    _9_Compressedlzw.tiff

    _1_Compressedlzw.tiff

    477_15_Compressed.txt

    0843156_796477_3.tiff

    843156_796477_11.tiff

    2RemovedFirstLine.tif

    843156_796477_10.tiff

    0843156_796477_5.tiff

    2RemovedFirstLine.tif

    6477_8_Compressed.txt

    1RemovedFirstLine.tif

    0843156_796477_9.tiff

    0RemovedFirstLine.tif

    843156_796477_14.tiff

    477_13_Compressed.png

    _4_Compressedlzw.tiff

    6477_3_Compressed.txt

    5RemovedFirstLine.tif

    477_15_Compressed.png

    6477_5_Compressed.png

    843156_796477_15.tiff

    477_11_Compressed.txt

    6477_9_Compressed.png

    _5_Compressedlzw.tiff

    6477_0_Compressed.txt

    6477_0_Compressed.png

    477_12_Compressed.png

    0RemovedFirstLine.tif

    10_Compressedlzw.tiff

    477_10_Compressed.txt

    477_13_Compressed.txt

    477_14_Compressed.txt

    6477_3_Compressed.png

    15_Compressedlzw.tiff

    _3_Compressedlzw.tiff

    6477_4_Compressed.txt

    6477_7_Compressed.txt

    9RemovedFirstLine.tif

    0843156_796477_0.tiff

    6477_5_Compressed.txt

    6477_1_Compressed.txt

    083_14_Compressed.png

    083_10_Compressed.txt

    083_9._Compressed.txt

    5RemovedFirstLine.tif

    6033067_752083_7.tiff

    _8_Compressedlzw.tiff

    _7_Compressedlzw.tiff

    8RemovedFirstLine.tif

    083_11_Compressed.txt

    033067_752083_10.tiff

    11_Compressedlzw.tiff

    6033067_752083_3.tiff

    14_Compressedlzw.tiff

    3RemovedFirstLine.tif

    2083_2_Compressed.txt

    7RemovedFirstLine.tif

    3RemovedFirstLine.tif

    1RemovedFirstLine.tif

    083_14_Compressed.txt

    13_Compressedlzw.tiff

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    1442



%% Cell type:code id: tags:



``` python

```

Remove_Noise.py

+11 −11
Original line number Diff line number Diff line
@@ -211,7 +211,7 @@ def save_testable_images(images, selected_channel, quantity_of_images): 
    images = find_only_in_channel(images, selected_channel)



    # image_locations = np.random.choice(len(images), quantity_of_images, replace=False)

    image_locations = np.arange(quantity_of_images) + 5000

    image_locations = np.arange(quantity_of_images) + 10000



    selected_images = np.array(images)[image_locations]
@@ -270,7 +270,7 @@ if __name__ == "__main__": 
    images = remote_image_extractor(scenes)

    images = find_only_in_channel(images, "11")

    # average_image = np.array(Image.open("Average_On_Channel(" + "11" + ").tiff"))

    # save_testable_images(images,"11",3)

    save_testable_images(images,"11",5)

    # plt.imshow(color_adjust(average_image),cmap='gray',vmin = 0, vmax=1)

    # plt.show()
@@ -287,27 +287,27 @@ if __name__ == "__main__": 
    # print(test_image)

    plt.subplot(121)

    plt.imshow(color_adjust(adjust_to_original(test_image,average_image)),cmap='gray',vmin = 0, vmax=1)

    plt.subplot(122)

    # plt.subplot(122)

    # plt.show()

    # print(gaussian_kernel)

    little_more_blurred = convolve2d(np.pad(test_image,2, mode = 'edge'),gaussian_kernel, "valid")

    # little_more_blurred = convolve2d(np.pad(test_image,2, mode = 'edge'),gaussian_kernel, "valid")

    # print(little_more_blurred)

    print(little_more_blurred.shape)

    # print(little_more_blurred.shape)

    # print(little_inverter(gaussian_kernel)@gaussian_kernel)

    altered_image = Image.fromarray(little_more_blurred.astype(np.uint16))

    # altered_image = Image.fromarray(little_more_blurred.astype(np.uint16))



    altered_image.save("averaged_images(" + "11" + ")/innerfolder" + "/testable.tiff")

    plt.imshow(color_adjust(little_more_blurred[3:-3,3:-3]),cmap='gray',vmin = 0, vmax=1)

    # altered_image.save("averaged_images(" + "11" + ")/innerfolder" + "/testable.tiff")

    # plt.imshow(color_adjust(little_more_blurred[3:-3,3:-3]),cmap='gray',vmin = 0, vmax=1)

    # plt.show()

    # renewed_array = 

    # H = fft(kernel)

	# deconvolved = np.real(ifft(fft(signal)*np.conj(H)/(H*np.conj(H) + lambd**2)))

    back_to_normal = wiener(little_more_blurred,gaussian_kernel,.02,clip=False)

    # back_to_normal = wiener(little_more_blurred,gaussian_kernel,.02,clip=False)

    # print(back_to_normal)

    # print(back_to_normal.shape)

    

    # plt.imshow(color_adjust(back_to_normal), cmap='gray',vmin = 0, vmax=1)

    plt.show()

    # plt.show()

    # newimage = Image.fromarray(test_image - average_image)

    # newimage.save("NoInterference.tiff")
@@ -320,6 +320,6 @@ if __name__ == "__main__": 
    # print(np.linalg.inv(np.array([[3,0,-1],[0,3,3],[1,-3,-4]])))

    # print(np.linalg.pinv(np.array([[-1,-1,1], [-1,0,1], [-1,1,1], [0,-1,1]])))



    last_image = Image.open("NoInterference.tiff")

    # last_image = Image.open("NoInterference.tiff")

    # plt.imshow(color_adjust(np.array(last_image)),cmap='gray',vmin = 0, vmax=1)

    # plt.show()

information_array.csv

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+211894 −0

File added.

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