Small changes for testing, revert behind if bad

    A       ndarray(3 X 3): system of equation

    """

    image_obj = Image.open(tiff_image_path)    #Open the image and read it as an Image object

    image_array = np.array(image_obj)[1:,:].astype(int)    #Convert to an array, leaving out the first row because the first row is just housekeeping data

    # image_array = np.array(image_obj)[1:].astype(int)    #Convert to an array, leaving out the first row because the first row is just housekeeping data

    image_array = np.array(image_obj).astype(int)

    # image_array = image_array.astype(int) 

    # A = np.array([[3,0,-1],[0,3,3],[1,-3,-4]]) # the matrix for system of equation

    Ainv = np.array([[0.5,-0.5,-0.5],[-0.5,1.83333333,1.5],[0.5,-1.5,-1.5]])

    scenes = file_extractor(folder_name)

    images = image_extractor(scenes)

    newnamesforlater = []

    # list_dic, bins = make_dictionary(images[0:1], 4, False)

    list_dic, bins = make_dictionary(images[19:20], 4, False)

    file_sizes_new = []

    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(images):

        if "NoI" in item:

            print(item)

            print(i)

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

    for i in range(len(images[0:5])):

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

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

        # inletters = bitstring_to_bytes(encoded_string)

    for i in range(19,len(images[0:20])):

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

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

        inletters = bitstring_to_bytes(encoded_string)

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

            newname = images[i][:-5]

        else:

            newname = images[i][:-4]

        print(newname)

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

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

        #     f.write(inletters)

        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(images[i])))

        # sleep(5)

        # if i % 50 == 0:

        #     print(i)

        #     sleep(20)

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

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

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

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

    bins = [21,32,48]

    for i,item in enumerate(newnamesforlater):

        print(item)

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

        encoded_string2 = bytes_to_bitstring(read_from_file(item))

        starttime = time()

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

        print(np.allclose(image, reconstruct_image))

        print(time() - starttime)

    # for i,item in enumerate(newnamesforlater):

    #     print(item)

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

    #     encoded_string2 = bytes_to_bitstring(read_from_file(item))

    #     starttime = time()

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

    #     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:]