Commit 310f8c6b authored by Bryce Hepner's avatar Bryce Hepner
Browse files

added saving feature

parent 408baf5a

.gitignore

+2 −1
Original line number Original line Diff line number Diff line
@@ -7,3 +7,4 @@ attic 
/compress_experiment.ipynb

/compress_experiment.ipynb

*.txt

*.txt

!backup.txt

!backup.txt

*.tiff
 
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RunningInParallel.py

0 → 100644
+52 −0
Original line number Original line Diff line number Diff line 
from ipyparallel import Client

from WorkingPyDemo import *

from time import time

def initialize():

    """

    Write a function that initializes a Client object, creates a Direct

    View with all available engines, and imports scipy.sparse as spar on

    all engines. Return the DirectView.

    """

    client = Client() # Only works if a cluster is running.

    dview = client[:]

    dview.execute("from WorkingPyDemo import *") #neede d for others

    dview.block = True

    return dview

if __name__ == "__main__":

    scenes = file_extractor(folder_name)

    images = image_extractor(scenes)

    dview = initialize()

    list_dic = np.load("first_dic.npy", allow_pickle=True)

    bins = [21,32,48]

    starttime = time()

    

    def save_an_image(filename):

        """



        """

        newnamesforlater = []

        list_dic = np.load("first_dic.npy", allow_pickle=True)

        bins = [21,32,48]

        image, new_error, diff = huffman(filename, 4, False)

        encoded_string = encoder(new_error, list_dic, diff, bins)

        inletters = bitstring_to_bytes(encoded_string)

        if filename[-5:] == ".tiff":

            newname = filename[:-5]

        else:

            newname = filename[:-4]

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

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

            f.write(inletters)

    def decode_an_image(filename):

        list_dic = np.load("first_dic.npy", allow_pickle=True)

        bins = [21,32,48]

        image, new_error, diff = huffman(filename, 4, False)

        if filename[-5:] == ".tiff":

            newname = filename[:-5]

        else:

            newname = filename[:-4]

        encoded_string2 = bytes_to_bitstring(read_from_file(newname + "_Compressed.txt"))

        reconstruct_image = decoder(encoded_string2, list_dic, bins, False)

    dview.map_sync(save_an_image, images[200:])

    # dview.map_sync(decode_an_image, images[0:6])

    print(time() - starttime)
 
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WorkingPyDemo.py

+49 −30
Original line number Original line Diff line number Diff line
@@ -9,7 +9,7 @@ from sklearn.neighbors import KernelDensity 
from collections import Counter

from collections import Counter

import numpy.linalg as la

import numpy.linalg as la

from time import time

from time import time



import tifffile as tiff

folder_name = "images"

folder_name = "images"

outputlocation = ""

outputlocation = ""
@@ -494,34 +494,53 @@ def bytes_to_bitstring(input_bytearray): 
    for i, item in enumerate(int_array):

    for i, item in enumerate(int_array):

        end_string += (bin(item)[2:].zfill(8))

        end_string += (bin(item)[2:].zfill(8))

    return end_string

    return end_string



def text_to_tiff(filename, list_dic, bins):

    encoded_string = bytes_to_bitstring(read_from_file(filename))

    reconstruct_image = decoder(encoded_string, list_dic, bins, False)

    reconstruct_image = reconstruct_image.astype(np.uint16)

    reconstruct_image = Image.fromarray(reconstruct_image)

    reconstruct_image.save(filename[:-16]+"_reconstructed.tiff", "TIFF")

# starttime = time()

# starttime = time()

if __name__ == "__main__":

    

    scenes = file_extractor(folder_name)

    scenes = file_extractor(folder_name)

newnamesforlater = []

    images = image_extractor(scenes)

    images = image_extractor(scenes)

    newnamesforlater = []

    # print(len(images))

    list_dic, bins = make_dictionary(images, 4, False)

    list_dic, bins = make_dictionary(images, 4, False)

file_sizes_new = []

    # file_sizes_new = []

file_sizes_old = []

    # file_sizes_old = []

# np.save("first_dic.npy", list_dic)



for i in range(1):

    np.save("first_dic.npy", list_dic)

    # for i in range(6):

    #     image, new_error, diff = huffman(images[i], 4, False)

    #     image, new_error, diff = huffman(images[i], 4, False)

    #     encoded_string = encoder(new_error, list_dic, diff, bins)

    #     encoded_string = encoder(new_error, list_dic, diff, bins)

    #     inletters = bitstring_to_bytes(encoded_string)

    #     inletters = bitstring_to_bytes(encoded_string)

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



        newname = images[i][:-5]

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

    else:

        #     newname = images[i][:-5]

        newname = images[i][:-4]

        # else:

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

        #     newname = images[i][:-4]

        # print(newname)

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

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

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

        #     f.write(inletters)

        #     f.write(inletters)

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

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

    file_sizes_old.append((os.path.getsize(images[i])))

    #     file_sizes_old.append((os.path.getsize(images[i])))

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

    # file_sizes_new.append(os.path.getsize("first_dic.npy"))

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

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

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

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



    # bins = [21,32,48]

# for i,item in enumerate(newnamesforlater[0:10]):

#     starttime = time()

    # for i,item in enumerate(newnamesforlater[0:6]):

    #     image, new_error, diff = huffman(images[i], 4, False)

    #     image, new_error, diff = huffman(images[i], 4, False)

    #     encoded_string2 = bytes_to_bitstring(read_from_file(item))

    #     encoded_string2 = bytes_to_bitstring(read_from_file(item))

    #     reconstruct_image = decoder(encoded_string2, list_dic, bins, False)

    #     reconstruct_image = decoder(encoded_string2, list_dic, bins, False)

    #     print(np.allclose(image, reconstruct_image))

    #     print(np.allclose(image, reconstruct_image))

    # print(time()-starttime)

    # text_to_tiff("images/1626033496_437803/1626033496_437803_3._Compressed.txt", list_dic, bins)

    # original_image = Image.open("images/1626033496_437803/1626033496_437803_3.tiff")

    # original_image = np.array(original_image)[1:]

    # secondimage = Image.open("images/1626033496_437803/1626033496_437803_3_reconstructed.tiff")

    # secondimage = np.array(secondimage)

    # print(np.allclose(original_image, secondimage))
 
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first_dic.npy

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images/1626032610_393963/1626032610_393963_0._Compressed.txt

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