l have an RGB image of dimension (224,224,3). l applied superpixel segmentation on it using SLIC algorithm.
As follow :
img= skimageIO.imread("first_image.jpeg")
print('img shape', img.shape) # (224,224,3)
segments_slic = slic(img, n_segments=1000, compactness=0.01, sigma=1) # Up to 1000 segments
segments_slic.shape
(224,224)
Number of returned segments are :
np.max(segments_slic)
Out[49]: 595
From 0 to 595. So, we have 596 superpixels (regions).
Let's take a look at segments_slic[0]
segments_slic[0]
Out[51]:
array([ 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5,
5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7,
8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9,
10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12,
12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 14, 14, 14,
14, 14, 14, 14, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 16, 16, 16,
16, 16, 16, 16, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18,
18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 20, 20,
20, 20, 20, 20, 20, 20, 20, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21,
21, 21, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, 23,
23, 23, 23, 23, 23, 23, 24, 24, 24, 24, 24, 24, 24, 25, 25, 25, 25,
25, 25, 25])
What l would like to get ?
for each superpixel region make two arrays as follow:
1) Array : contain the indexes of the pixels belonging to the same superpixel.
For instance
superpixel_list[0] contains all the indexes of the pixels belonging to superpixel 0 .
superpixel_list[400] contains all the indexes of the pixels belonging to superpixel 400
2)superpixel_pixel_values[0] : contains the pixel values (in RGB) of the pixels belonging to superpixel 0.
For instance, let's say that pixels 0, 24 , 29, 53 belongs to the superpixel 0. Then we get
superpixel[0]= [[223,118,33],[245,222,198],[98,17,255],[255,255,0]]# RGB values of pixels belonging to superpixel 0
What is the efficient/optimized way to do that ? (Because l have l dataset of images to loop over)
EDIT-1
def sp_idx(s, index = True):
u = np.unique(s)
if index:
return [np.where(s == i) for i in u]
else:
return [s[s == i] for i in u]
#return [s[np.where(s == i)] for i in u] gives the same but is slower
superpixel_list = sp_idx(segments_slic)
superpixel = sp_idx(segments_slic, index = False)
In superpixel_list we are supposed to get a list containing the index of pixels belonging to the same superpixel.
For instance
superpixel_list[0] is supposed to get all the pixel indexes of the pixel affected to superpixel 0
however l get the following :
superpixel_list[0]
Out[73]:
(array([ 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2,
3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5,
5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7,
7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 10,
10, 10, 10, 10, 11, 11, 11, 11, 12, 12, 12, 12, 13, 13, 13]),
array([0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5, 0, 1, 2, 3, 4, 5,
6, 0, 1, 2, 3, 4, 5, 6, 0, 1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4, 5, 6,
7, 0, 1, 2, 3, 4, 5, 6, 0, 1, 2, 3, 4, 5, 6, 0, 1, 2, 3, 4, 5, 0, 1,
2, 3, 4, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2]))
Why two arrays ?
In superpixel[0] for instance we are supposed to get the RGB pixel values of each pixel affected to supepixel 0 as follow :
for instance pixels 0, 24 , 29, 53 are affected to superpixel 0 then :
superpixel[0]= [[223,118,33],[245,222,198],[98,17,255],[255,255,0]]
However when l use your function l get the following :
superpixel[0]
Out[79]:
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
Thank you for your help
Can be done using np.where and the resulting indices.
def sp_idx(s, index = True):
u = np.unique(s)
return [np.where(s == i) for i in u]
superpixel_list = sp_idx(segments_slic)
superpixel = [img[idx] for idx in superpixel_list]
Related
I want to create a torch tensor of size 100 with values 10 and 100.
For example: The following gives a tensor of values between 5 and 6.
torch.randint(5,7,(100,))
tensor([6, 6, 6, 5, 5, 6, 6, 6, 6, 5, 6, 6, 6, 6, 6, 5, 6, 5, 5, 6, 5, 5, 5, 5,
6, 5, 5, 5, 5, 5, 6, 6, 6, 5, 6, 6, 5, 5, 5, 5, 6, 5, 5, 5, 5, 5, 6, 5,
5, 6, 5, 6, 5, 6, 5, 6, 6, 6, 6, 5, 6, 6, 6, 5, 5, 5, 6, 6, 6, 6, 5, 6,
5, 5, 5, 5, 6, 6, 5, 6, 6, 6, 5, 5, 6, 6, 5, 6, 6, 6, 5, 5, 5, 5, 5, 6,
6, 6, 5, 6])
Instead of this, I want a tensor with values 10 and 100 and I do not want the values between the integers 10 and 100. Tensor should just contain 10 and 100. How do I do that?
Thanks in advance.
If you sample from {0, 1} then a simple mapping from [0, 1] to [10, 100] will suffice
Here x -> (b-a)x + a = (100-10)x + 10 = 90x + 10 will work:
>>> rand = torch.randint(0, 2, (100,))
tensor([0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0,
0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0,
0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1,
0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1,
1, 1, 0, 0])
>>> 90*rand+10
tensor([ 10, 10, 100, 100, 100, 100, 10, 100, 100, 100, 100, 10, 10, 100,
100, 10, 100, 100, 10, 100, 100, 100, 10, 10, 10, 10, 10, 100,
10, 10, 100, 10, 100, 100, 10, 10, 100, 10, 10, 10, 10, 10,
100, 10, 10, 100, 10, 10, 10, 100, 100, 100, 100, 10, 100, 100,
10, 10, 100, 10, 100, 10, 100, 10, 100, 100, 10, 10, 10, 10,
100, 100, 10, 10, 100, 100, 10, 10, 10, 100, 10, 10, 100, 10,
100, 100, 10, 10, 100, 10, 100, 10, 10, 10, 100, 100, 100, 100,
10, 10])
You can achieve that by using the python function random.choice() to create a list of random numbers then convert it to a tensor:
import random
import torch
list_numbers = random.choices([100,10], k=100)
random_numbers = torch.Tensor(list_numbers)
print(random_numbers)
I am using a stack class to store 2d lists of strings and integers.
The lists serve as tables and I have the following code:
print('pushing')
print(lookup_table)
tables_to_be_tested.push(lookup_table)
print('new table')
print(lookup_table)
print('top of stack: ')
print(tables_to_be_tested.peek())
lookup_table[0][c2index] = c1_value
print('top of stack 2: ')
print(tables_to_be_tested.peek())
The line lookup_table[0][c2index] = c1_value only updates one value in the first list
Here is my output:
pushing
[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [39, 50, 38, 53, 28, 37, 49, 52, 31, 42], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
new table
[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [39, 50, 38, 53, 28, 37, 49, 52, 31, 42], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
top of stack:
[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [39, 50, 38, 53, 28, 37, 49, 52, 31, 42], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
top of stack 2:
[[0, 1, 2, 3, 4, 10, 6, 7, 8, 9], [39, 50, 38, 53, 28, 37, 49, 52, 31, 42], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
The lists are created independently like this: lookup_table = [[],[],[]] and are appended to in a for loop.
The calculation should not affect the 2d list in the stack and yet it does. Why is this? What is a solution?
I'm trying to knowing which is the color of a pixel through it's x and y. The colors are from this image.
Capturing the colors with Photoshop I've got this list of colors:
"#5D385A", "#6D3B47", "#6F5C4B", "#50717A", "#547057", "#4C6180", "#717080", "#705574", "#726B59", "#5E4854", "#415A4B", "#425A64", "#3A4E6F"
However, when I try to get the color of a pixel from the image, this color doesn't match with the previous list. And, I've got 95 different colors when in the image there are only 13 different colors.
I open the image and get the color from a pixel with this class:
import PIL.Image
class Image:
def __init__(self, file):
self.image = PIL.Image.open(file).convert("RGB")
def get_color(self, x, y):
color = self.image.getpixel((x,y))
color = ("#%02x%02x%02x" % color).upper()
return color
Here is a short list of x and y of positions where I take the color:
144, 74
140, 46
150, 53
85, 87
160, 48
147, 60
137, 49
149, 53
148, 60
143, 52
161, 30
166, 23
134, 38
146, 29
155, 40
129, 37
154, 66
153, 38
151, 33
128, 36
How is that possible? How can I get 95 different colors from the image when there is only 13 different colors?
Edit I:
I have get all the colors from each pixel in the image and no one has the color what I get with Photoshop.
I have got 256 different colors, this is the list and number times found it.
{'#885F7D': 15, '#541B47': 15, '#68355B': 819, '#65355D': 17, '#78384A': 19, '#7E3942': 19, '#7B3846': 4588, '#7C3346': 39, '#7D3046': 50, '#773F4C': 21, '#785A49': 4, '#775F49': 35, '#765C49': 17540, '#7A4648': 21, '#756349': 62, '#785B49': 56, '#7C3546': 14, '#765D49': 12, '#7A4F48': 14, '#7C3746': 29, '#785549': 7, '#775D4A': 8, '#785749': 8, '#551743': 1, '#6A3158': 39, '#68325A': 6, '#86617E': 1, '#66385D': 31, '#6C2C56': 6, '#6C2A56': 7, '#6D2B54': 3, '#678D97': 88, '#2C5B6A': 60, '#416C79': 43, '#3F717A': 7, '#43686A': 64, '#5C5F71': 32, '#465771': 3, '#5E5666': 14, '#5D4C66': 7, '#644160': 2, '#683C5F': 2, '#659197': 2, '#1C606C': 88, '#32767E': 61, '#227B84': 59, '#3A757A': 60, '#803342': 16, '#7D3745': 6, '#3A727B': 7374, '#3B7479': 3, '#36747C': 11, '#6C4450': 104, '#82303F': 18, '#852B3B': 28, '#694A56': 3, '#3D7179': 15, '#694E59': 15, '#7D3545': 11, '#387283': 30, '#3B717B': 17, '#3A727D': 16, '#7B5A48': 37, '#832B43': 11, '#3B7184': 21, '#2A7C66': 1, '#5D5D4E': 2, '#3B7180': 23, '#41715A': 6, '#45714D': 44, '#297D59': 6, '#407256': 32, '#417160': 13, '#437155': 5275, '#467055': 16, '#327A58': 7, '#68514E': 4, '#407756': 2, '#3C7356': 22, '#56654F': 17, '#437154': 15, '#387457': 30, '#3F7169': 14, '#4B6D54': 9, '#805C49': 105, '#735E4A': 10, '#7F5747': 63, '#755C49': 9, '#457154': 16, '#337558': 45, '#536B52': 18, '#735944': 95, '#7B614F': 96, '#5D6750': 36, '#437156': 43, '#69624D': 21, '#457151': 29, '#3D7172': 10, '#70604B': 10, '#487458': 2, '#45744D': 96, '#447352': 2, '#23596C': 2, '#3C6A7E': 59, '#3F696B': 41, '#64819B': 37, '#204D73': 92, '#3C5E82': 60, '#3A5E8A': 93, '#385B92': 1, '#3C6182': 4212, '#5D7F9A': 1, '#0C4A72': 2, '#305E82': 118, '#5C6982': 118, '#8F8D9B': 26, '#646473': 3, '#7B7482': 118, '#5A7169': 14, '#39714D': 12, '#727182': 2691, '#797189': 13, '#3E724D': 1, '#3B7155': 51, '#885947': 1, '#7D5744': 1, '#866251': 1, '#4F7056': 51, '#675C48': 106, '#707289': 10, '#736E6C': 11, '#746B51': 12, '#756C58': 116, '#82705C': 27, '#135941': 27, '#235D44': 105, '#255B44': 24, '#1D5943': 45, '#2B5C46': 108, '#2B5C45': 8, '#746C58': 5469, '#2E5C46': 17561, '#7E705B': 32, '#4F634D': 10, '#7B6E5A': 32, '#45614B': 14, '#707584': 117, '#6E788C': 1, '#72716E': 1, '#75677E': 117, '#746684': 1, '#766D59': 26, '#3D5F49': 11, '#255943': 33, '#957890': 39, '#7A5174': 117, '#7C4B7C': 2, '#775E6A': 62, '#727152': 39, '#726C58': 32, '#365E47': 12, '#683F63': 37, '#7A5476': 4212, '#79507A': 37, '#766166': 38, '#7A6D57': 15, '#6E6B56': 13, '#2D5D46': 5, '#696A54': 4, '#2C5B45': 8, '#626852': 8, '#305C46': 24, '#2E5C44': 26, '#7E577B': 2, '#7C567A': 55, '#7A517A': 58, '#784F79': 1, '#5F3855': 1, '#724F68': 57, '#727053': 59, '#856C77': 89, '#51303E': 91, '#62444F': 56, '#60404E': 1, '#767558': 56, '#654654': 7521, '#623F53': 16, '#674B54': 7, '#747057': 25, '#746B58': 40, '#623E53': 15, '#654754': 40, '#757158': 11, '#6F6C56': 2, '#644554': 29, '#613D53': 16, '#6B5555': 15, '#6F5E56': 15, '#756D57': 11, '#634354': 7, '#634153': 13, '#716457': 7, '#644254': 7, '#654354': 4, '#305C48': 3, '#726C59': 2, '#7E7055': 6, '#817155': 7, '#48615F': 4, '#0A5649': 1, '#2E5C3E': 26, '#135669': 2, '#2C5B68': 34, '#2B5C53': 21, '#2E5C41': 58, '#415F60': 3, '#0F5667': 5, '#2C5B64': 4676, '#2C5B66': 19, '#2C5B5B': 17, '#2E5C4D': 8, '#175966': 7, '#375D61': 2, '#61675B': 1, '#2F5B64': 20, '#2C5B60': 16, '#2F5B4A': 3, '#55675E': 2, '#2E5C4A': 8, '#275C64': 23, '#674654': 10, '#385260': 1, '#684553': 26, '#1C5E66': 46, '#564D59': 5, '#3D5660': 8, '#4F4F5B': 10, '#5E4A57': 7, '#365961': 5, '#47525D': 8, '#5C4B57': 4, '#614756': 2, '#5A4759': 36, '#504A60': 10, '#404B67': 7, '#2C5667': 18, '#8B6B75': 1, '#2B4D71': 876, '#2D5D62': 18, '#7C6D7B': 1, '#58728D': 16, '#0A365F': 16, '#21553E': 4, '#335F4B': 1, '#35624D': 20, '#3D6752': 4}
I don't understand anything. How is it possible that no one pixel has the color that I've got in Photoshop?
Edit II:
With the same code, I have got the color map of another image. This is the image:
The predominant colors that you can see in this image are these:
"#F50A22", "#00EC83", "#00A200", "#0007A4", "#9D132B", "#734500", "#6230FF", "#F42AFF", "#BEFF00", "#EC7800", "#65DCD1", "#FF6D00" : "#004500"
Executing the test, how I said, the same code. I've got that all these colors are found it in the image among others! And no one of them how in the first image.
The results are:
Colors matched: {'#F50A22': 2245, '#00EC83': 9437, '#00A200': 21039, '#0007A4': 8772, '#9D132B': 99, '#734500': 2970, '#6230FF': 112, '#F42AFF': 5271, '#BEFF00': 2380, '#EC7800': 3076, '#65DCD1': 6503, '#FF6D00': 4709, '#004500': 6612}
colors matched: 13
And other colors found it in the image are:
Other colors: {'#FFFFFF': 1931, '#FCFFFD': 27, '#FAFFFB': 2, '#F7FEF9': 12, '#F4FEF7': 10, '#F6FEF8': 20, '#F6FDF8': 1, '#F9FEFA': 12, '#FBFEFC': 9, '#FEFFFE': 40, '#FAFEFB': 12, '#FBFFFC': 7, '#F3FEF6': 7, '#F4FDF6': 2, '#F5FDF7': 1, '#F2FDF5': 3, '#EEFDF2': 3, '#F2FDF6': 7, '#F4FEF8': 12, '#EFFDF4': 3, '#E5FCEC': 4, '#DAFAE5': 1, '#D3FAE0': 3, '#D4FAE0': 1, '#DAFAE4': 1, '#DFFBE8': 1, '#E9FCEF': 3, '#EDFDF2': 2, '#EFFDF3': 3, '#E2FBEA': 3, '#E2FCEA': 3, '#EFFEF3': 1, '#F2FEF5': 1, '#EDFCF1': 2, '#EBFDF0': 1, '#F1FDF4': 1, '#F3FEF7': 4, '#EDFDF1': 2, '#E7FCEE': 3, '#E3FCEB': 1, '#E0FCE9': 1, '#DCFBE6': 5, '#DAFBE5': 1, '#D9FAE4': 1, '#D9FAE3': 1, '#E3FCEC': 1, '#EEFDF3': 1, '#D7FAE2': 1, '#D1FADF': 1, '#D1FADE': 1, '#D6FAE2': 1, '#E1FBEA': 2, '#EBFDF1': 1, '#DFFBE9': 1, '#DEFBE7': 2, '#DBFBE5': 1, '#F6132A': 111, '#00EC84': 33, '#00EC85': 16, '#04EC86': 11, '#14EC87': 3, '#F40D23': 3, '#F20E24': 1, '#F50B22': 8, '#F11426': 2, '#F40C23': 1, '#EF1A28': 1, '#EE1B29': 1, '#F01827': 1, '#F21125': 1, '#F40D24': 1, '#F40E24': 1, '#774A03': 165, '#F40E23': 1, '#F50C22': 1, '#F6142A': 3, '#00EC82': 1, '#00EB82': 2, '#00EA7F': 1, '#00EB81': 1, '#6FE09C': 1, '#7E5416': 2, '#00A300': 78, '#00A500': 43, '#D9403B': 1, '#00AB16': 1, '#00A600': 40, '#00A700': 1123, '#5E2AFF': 2471, '#00B213': 2, '#00AA00': 6, '#7A4F0D': 3, '#6636FF': 2, '#00AE02': 2, '#00AC00': 3, '#00AB08': 2, '#00A800': 12, '#00A900': 8, '#00B317': 1, '#6C3CFF': 1, '#00AE00': 2, '#00AE14': 1, '#00A903': 1, '#7F55FE': 1, '#6CEE9F': 1, '#00AD00': 2, '#6CDCD2': 268, '#6A3CFE': 2, '#7549FF': 1, '#4ED688': 1, '#6B3DFF': 1, '#5E2BFF': 24, '#6839FD': 1, '#6231FE': 1, '#5E31FC': 2, '#00AF08': 1, '#00AC07': 1, '#6339FA': 1, '#5F33FB': 3, '#5F30FD': 3, '#00B10E': 1, '#656565': 1, '#00AB00': 2, '#00B02D': 2, '#6037F9': 1, '#5F2EFE': 2, '#5F3EF5': 1, '#5F32FC': 1, '#6040F4': 1, '#5F32FB': 2, '#6041F3': 1, '#6042F2': 1, '#7145FC': 1, '#5F2CFF': 10, '#6147EF': 1, '#6454EA': 1, '#6036F9': 1, '#685AEA': 1, '#00AF2F': 1, '#6B57EE': 1, '#00B110': 1, '#00AA02': 1, '#8ADBD3': 3, '#683CFB': 1, '#72DDD2': 3, '#6D47F8': 1, '#775EF3': 1, '#9CD7D1': 2, '#5E31FD': 1, '#00AB18': 1, '#82DCD3': 1, '#673EFB': 1, '#7450F9': 1, '#612EFF': 8, '#6236FB': 1, '#602CFF': 5, '#6B49F7': 1, '#602DFF': 7, '#5F2BFF': 6, '#6334FD': 1, '#2EEB8B': 1, '#704AFB': 1, '#6231FF': 1, '#6738FE': 1, '#612DFF': 3, '#3FEB8F': 1, '#66DBD1': 5, '#67D8D2': 1, '#00AE2B': 1, '#65DAD2': 1, '#F42DFF': 15, '#FC67FF': 6, '#F246FA': 1, '#F84CFF': 7, '#6233FF': 1, '#6ADCD2': 22, '#6132FE': 1, '#FBFEFE': 2, '#F434FF': 5, '#F8FDFC': 1, '#68DCD1': 33, '#6034FE': 1, '#FB5DFF': 2, '#FAFEFD': 2, '#F2FBFA': 1, '#6442FA': 1, '#6031FF': 1, '#F539FF': 7, '#F5FCFC': 1, '#E7F9F6': 1, '#F02AFF': 5, '#EFFBF9': 2, '#DDF6F3': 1, '#5F2EFF': 1, '#DD2BFF': 1, '#E82AFF': 1, '#F32AFF': 8, '#F744FF': 3, '#E7F9F7': 1, '#CFF2EF': 1, '#6136FD': 1, '#5F2AFF': 1, '#DD2AFF': 1, '#E42AFF': 1, '#EC2AFF': 2, '#E1F7F4': 1, '#C3EFEA': 1, '#6031FE': 1, '#EA2AFF': 2, '#ED2AFF': 1, '#DAF6F2': 1, '#BAEEE7': 1, '#6DDDD3': 2, '#6937FF': 1, '#ED37FE': 1, '#D7F5F1': 2, '#B6EDE6': 1, '#69DDD2': 2, '#74DFD4': 1, '#81DED9': 1, '#EF2BFF': 1, '#B3ECE7': 1, '#7ED7D4': 1, '#F22AFF': 2, '#D9F5F2': 1, '#B7EDE7': 1, '#DB39FC': 1, '#F12EFF': 1, '#E0F7F4': 1, '#C2EFEA': 1, '#87DBD3': 1, '#E737FE': 1, '#E6F8F6': 2, '#CCF2EE': 1, '#84DCD3': 1, '#ECFAF9': 1, '#D8F5F2': 1, '#65DCD0': 5, '#69DBCF': 6, '#6ADCD1': 1, '#98D3CD': 1, '#F440FC': 1, '#F42CFF': 7, '#F4FCFB': 1, '#6FD9CC': 2, '#6FD9CB': 3, '#6BDBCF': 1, '#7ED7C8': 1, '#80D3C1': 1, '#F531FF': 3, '#F42BFF': 35, '#FDFEFE': 2, '#F8FDFD': 1, '#83D8CB': 1, '#7ED3C2': 1, '#FF7100': 78, '#FEFFFF': 1, '#97D2CC': 1, '#FF7000': 40, '#FF6E00': 40, '#FF7925': 1, '#F33FF7': 1, '#6FDDD2': 2, '#FF6B00': 8, '#F62DF4': 1, '#F52BFB': 1, '#FF7409': 1, '#F62DF3': 1, '#F52BFC': 3, '#A2CFCA': 1, '#F73FE3': 1, '#F52DF9': 1, '#F42AFE': 1, '#FF7400': 4, '#FF730E': 1, '#FC36D5': 1, '#F62DF1': 1, '#F52BFD': 1, '#F52CFF': 6, '#F52DFF': 13, '#76DDD3': 2, '#FF6C00': 8, '#F831EA': 1, '#F52BFA': 3, '#F632FF': 1, '#8DDAD2': 1, '#F836E6': 1, '#F52BF9': 2, '#A4CCC8': 1, '#FF6A08': 1, '#7ADDD3': 1, '#FF690B': 1, '#F42BFE': 1, '#92D9D2': 2, '#FF6E0B': 1, '#F031FA': 1, '#A7C8C5': 1, '#FF6429': 1, '#FF7200': 62, '#FF671A': 1, '#7EDCD3': 1, '#EC35F6': 1, '#6CDACE': 1, '#6DDBD0': 1, '#FF671C': 1, '#FF7104': 1, '#FF6911': 1, '#FF642C': 1, '#FF6B23': 1, '#FF6E13': 1, '#FF7300': 5, '#F530FF': 1, '#F532FF': 3, '#6DDDD2': 1, '#F533FF': 1, '#F635FF': 1, '#F537FF': 8, '#F539FE': 2, '#F538FF': 9, '#00AC1A': 4, '#FF780E': 1, '#004B04': 29, '#FF873C': 1, '#FF7C1B': 1, '#FF7606': 4, '#FF780C': 1, '#FF7502': 1, '#FF7504': 1, '#FF770A': 2, '#004A03': 9, '#004A02': 5, '#F73FFF': 2, '#F435FF': 1, '#004700': 9, '#FF7A0F': 1, '#F52EFF': 1, '#F63BFF': 1, '#F638FF': 1, '#004600': 22, '#004B03': 3, '#004901': 8, '#FF7D1D': 1, '#F43EFB': 1, '#FF8533': 1, '#F62DF6': 1, '#FF7F24': 1, '#004902': 3, '#004900': 1, '#F441FC': 1, '#C1E057': 1, '#C2FD00': 5, '#C1F700': 1, '#C0FE00': 176, '#C4EE30': 2, '#C3E846': 1, '#C2FB00': 2, '#FEFEFE': 9, '#004C07': 11, '#B8FB00': 2, '#C3FB00': 1, '#FDFEFD': 5, '#BAFB00': 2, '#C5F11A': 2, '#B3F600': 2, '#BEFC00': 1, '#C1FD00': 7, '#FBFCFB': 3, '#BCDE52': 1, '#BBFE00': 9, '#FAFBFA': 2, '#B6F700': 1, '#BDFB00': 1, '#C3F800': 5, '#F331FF': 1, '#B2F500': 1, '#BDF900': 1, '#BDFD00': 1, '#BBFC00': 2, '#BDFE00': 10, '#C3EA40': 1, '#FCFDFC': 4, '#B5F600': 2, '#BCFD00': 7, '#C4E847': 1, '#CDFD09': 3, '#2337B3': 1, '#4251B6': 1, '#C5ED37': 1, '#D5FF3E': 17, '#0012A7': 625, '#004B06': 1, '#CFFE22': 5, '#B6F900': 2, '#C5FD00': 5, '#D3FF3C': 3, '#005010': 1, '#CBFD00': 5, '#C2FE00': 3, '#B8F900': 2, '#D2FE31': 8, '#C8FD00': 3, '#B9FA00': 2, '#C4FD00': 3, '#F8FBF9': 2, '#CCFE08': 3, '#F4F6F4': 2, '#C7FD00': 5, '#EBF1EC': 1, '#F8F9F7': 1, '#E1EAE4': 1, '#004701': 1, '#132AAF': 2, '#D5E2D8': 1, '#F1F5F2': 2, '#D1DFD5': 1, '#EC8417': 1, '#D4E1D7': 1, '#F3F5F3': 1, '#D9E4DC': 1, '#EB7800': 15, '#ED7B00': 133, '#F6F8F5': 1, '#DEE8E0': 1, '#E6EDE6': 1, '#FAFDFB': 1, '#EAF0EB': 1, '#EEF3EF': 1, '#EA7700': 2, '#F5F7F5': 1, '#C2E64E': 1, '#CAFD00': 2, '#F7FAF8': 1, '#E87700': 2, '#EA7800': 7, '#004C06': 2, '#CFFE20': 2, '#004A05': 1, '#E37600': 1, '#E67700': 1, '#00591D': 1, '#990A22': 2077, '#A6293C': 1, '#021EAA': 1, '#0007A3': 6, '#0009A1': 2, '#001697': 2, '#000B9F': 2, '#00119B': 1})
total other colors: 448
Both images are png.
How is it possible that I found all the colors among others in the second image and not found anyone of the color searched in the first image?
you can see 13 colors yes! but the code doesn't because it's more precise than your eyes.
try zooming into the picture more, you'll see that between the colors there is another lighter one, which can consist of more than one color to go from one to the other, also I noticed some black and white at the left side "maybe it's just from your snipping tool or something"
but what I'm saying is, the code is right :)
you can try and create a photo using paint and only two colors with the fill tool, and make sure it's only one color without any gradient.
I found the problem and the solution. The problem is that I'm using images which has been created from a previous export. I mean, I have resized and make an export from an original imagin and in this momento something happens in Photoshop or whatever other program which produce an image with many other colors and not the original colors.
So, you have to run the process over the original version of the image, the export from the vectorized image. If you make an export from this export and then run the process, you will have problems like me.
I have a 2d numpy array as such:
import numpy as np
a = np.arange(20).reshape((2,10))
# array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
# [10, 11, 12, 13, 14, 15, 16, 17, 18, 19]])
I want to swap pairs of elements in each row. The desired output looks like this:
# array([[ 9, 0, 2, 1, 4, 3, 6, 5, 8, 7],
# [19, 10, 12, 11, 14, 13, 16, 15, 18, 17]])
I managed to find a solution in 1d:
a = np.arange(10)
# does the job for all pairs except the first
output = np.roll(np.flip(np.roll(a,-1).reshape((-1,2)),1).flatten(),2)
# first pair done manually
output[0] = a[-1]
output[1] = a[0]
Any ideas on a "numpy only" solution for the 2d case ?
Owing to the first pair not exactly subscribing to the usual pair swap, we can do that separately. For the rest, it would relatively straight-forward with reshaping to split axes and flip axis. Hence, it would be -
In [42]: a # 2D input array
Out[42]:
array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14, 15, 16, 17, 18, 19]])
In [43]: b2 = a[:,1:-1].reshape(a.shape[0],-1,2)[...,::-1].reshape(a.shape[0],-1)
In [44]: np.hstack((a[:,[-1,0]],b2))
Out[44]:
array([[ 9, 0, 2, 1, 4, 3, 6, 5, 8, 7],
[19, 10, 12, 11, 14, 13, 16, 15, 18, 17]])
Alternatively, stack and then reshape+flip-axis -
In [50]: a1 = np.hstack((a[:,[0,-1]],a[:,1:-1]))
In [51]: a1.reshape(a.shape[0],-1,2)[...,::-1].reshape(a.shape[0],-1)
Out[51]:
array([[ 9, 0, 2, 1, 4, 3, 6, 5, 8, 7],
[19, 10, 12, 11, 14, 13, 16, 15, 18, 17]])
I'm trying to programm the Data Encyption Standard on my own and I'm struggling to Programm the SBoxes. I know there is already a module to encrypt and decrypt with the DES but my teacher asked to programm it myself, so here is what i have:
import random
from re import findall
class DES:
def __init__(self):
self. Eingabe=""
self.Schluessel=""
self.NachrichtBinaer=""
self.Bitslinks=""
self.Bitsrechts=""
self.Teil1=""
self.Teil2=""
self.Subkey=""
self.pcschluessel=""
self.subkeyliste=[]
self.initialpermutation=""
self.liste1=[]
self.Bits48=""
self.ausgabesbox=[]
self.liste2=[]
def EingabeNachricht(self):
self.Eingabe=input("Geben Sie ein Wort ein:")
print ("Eingegebenes Wort: ",self.Eingabe)
def Bitumwandlung(self):
for i in range(0,len(self.Eingabe)):
self.NachrichtBinaer=self.NachrichtBinaer+bin(ord(self.Eingabe[i]))
self.NachrichtBinaer=self.NachrichtBinaer.replace("b","")
if len(self.NachrichtBinaer)<64:
self.NachrichtBinaer=self.NachrichtBinaer.rjust(64,"0")
self.NachrichtBinaer="0000000100100011010001010110011110001001101010111100110111101111"
print ("Nachricht in Binaer: ",self.NachrichtBinaer)
def Teilen(self):
self.Bitslinks=self.initialpermutation[:int(len(self.initialpermutation)/2)]
self.Bitsrechts=self.initialpermutation[int(len(self.initialpermutation)/2):]
print ("Teil links: ",self.Bitslinks)
print ("Teil rechts: ",self.Bitsrechts)
def SchluesselGenerieren(self):
#self.Schluessel= getrandbits(64)
self.Schluessel="0001001100110100010101110111100110011011101111001101111111110001"
def ippermutation(self):
ip = [57, 49, 41, 33, 25, 17, 9,1,
59, 51, 43, 35, 27, 19, 11, 3,
61, 53, 45, 37, 29, 21, 13, 5,
63, 55, 47, 39, 31, 23, 15, 7,
56, 48, 40, 32, 24, 16, 8, 0,
58, 50, 42, 34, 26, 18, 10, 2,
60, 52, 44, 36, 28, 20, 12, 4,
62, 54, 46, 38, 30, 22, 14, 6
]
for i in ip:
self.initialpermutation=self.initialpermutation+self.NachrichtBinaer[i]
print ("Erste Permutation: ",self.initialpermutation)
def Expandieren(self):
ExpandierenTabelle = [
31,0,1,2,3,4,
3,4,5,6,7,8,
7,8,9,10,11,12,
11,12,13,14,15,16,
15,16,17,18,19,20,
9,20,21,22,23,24,
3,24,25,26,27,28,
27,28,29,30,31,0]
for Elemente in ExpandierenTabelle:
self.Bits48 = self.Bits48 + self.Bitsrechts[Elemente]
print ("expandiert: ",self.Bits48)
def XOR(self,wert1,wert2):
antwort=wert1^wert2
return antwort
def SBox(self):
self.sbox=[
[[14, 4, 13, 1, 2, 15, 11, 8, 3, 10, 6, 12, 5, 9, 0, 7],
[0, 15, 7, 4, 14, 2, 13, 1, 10, 6, 12, 11, 9, 5, 3, 8],
[4, 1, 14, 8, 13, 6, 2, 11, 15, 12, 9, 7, 3, 10, 5, 0],
[15, 12, 8, 2, 4, 9, 1, 7, 5, 11, 3, 14, 10, 0, 6, 13]],
# S2
[[15, 1, 8, 14, 6, 11, 3, 4, 9, 7, 2, 13, 12, 0, 5, 10],
[3, 13, 4, 7, 15, 2, 8, 14, 12, 0, 1, 10, 6, 9, 11, 5],
[0, 14, 7, 11, 10, 4, 13, 1, 5, 8, 12, 6, 9, 3, 2, 15],
[13, 8, 10, 1, 3, 15, 4, 2, 11, 6, 7, 12, 0, 5, 14, 9]],
# S3
[[10, 0, 9, 14, 6, 3, 15, 5, 1, 13, 12, 7, 11, 4, 2, 8],
[13, 7, 0, 9, 3, 4, 6, 10, 2, 8, 5, 14, 12, 11, 15, 1],
[13, 6, 4, 9, 8, 15, 3, 0, 11, 1, 2, 12, 5, 10, 14, 7],
[1, 10, 13, 0, 6, 9, 8, 7, 4, 15, 14, 3, 11, 5, 2, 12]],
# S4
[[7, 13, 14, 3, 0, 6, 9, 10, 1, 2, 8, 5, 11, 12, 4, 15],
[13, 8, 11, 5, 6, 15, 0, 3, 4, 7, 2, 12, 1, 10, 14, 9],
[10, 6, 9, 0, 12, 11, 7, 13, 15, 1, 3, 14, 5, 2, 8, 4],
[3, 15, 0, 6, 10, 1, 13, 8, 9, 4, 5, 11, 12, 7, 2, 14]],
# S5
[[2, 12, 4, 1, 7, 10, 11, 6, 8, 5, 3, 15, 13, 0, 14, 9],
[14, 11, 2, 12, 4, 7, 13, 1, 5, 0, 15, 10, 3, 9, 8, 6],
[4, 2, 1, 11, 10, 13, 7, 8, 15, 9, 12, 5, 6, 3, 0, 14],
[11, 8, 12, 7, 1, 14, 2, 13, 6, 15, 0, 9, 10, 4, 5, 3]],
# S6
[[12, 1, 10, 15, 9, 2, 6, 8, 0, 13, 3, 4, 14, 7, 5, 11],
[10, 15, 4, 2, 7, 12, 9, 5, 6, 1, 13, 14, 0, 11, 3, 8],
[9, 14, 15, 5, 2, 8, 12, 3, 7, 0, 4, 10, 1, 13, 11, 6],
[4, 3, 2, 12, 9, 5, 15, 10, 11, 14, 1, 7, 6, 0, 8, 13]],
# S7
[[4, 11, 2, 14, 15, 0, 8, 13, 3, 12, 9, 7, 5, 10, 6, 1],
[13, 0, 11, 7, 4, 9, 1, 10, 14, 3, 5, 12, 2, 15, 8, 6],
[1, 4, 11, 13, 12, 3, 7, 14, 10, 15, 6, 8, 0, 5, 9, 2],
[6, 11, 13, 8, 1, 4, 10, 7, 9, 5, 0, 15, 14, 2, 3, 12]],
# S8
[[13, 2, 8, 4, 6, 15, 11, 1, 10, 9, 3, 14, 5, 0, 12, 7],
[1, 15, 13, 8, 10, 3, 7, 4, 12, 5, 6, 11, 0, 14, 9, 2],
[7, 11, 4, 1, 9, 12, 14, 2, 0, 6, 10, 13, 15, 3, 5, 8],
[2, 1, 14, 7, 4, 10, 8, 13, 15, 12, 9, 0, 3, 5, 6, 11]]
]
for z in range(len(self.sbox)):
for y in range(len(self.sbox[z])):
for x in range(len(self.sbox[z][y])):
ausserebits=self.liste2[x][z][0]+self.liste2[x][z][-1]
innerebits=self.liste2[x][z][1:5]
print ("innere: ",innerebits)
print ("aussere: ",ausserebits)
def pc1undteilen(self):
pc1 = [56,48,40,32,24,16,8,
0,57,49,41,33,25,17,
9,1,58,50,42,34,26,
18,19,2,59,51,43,35,
62,54,46,38,30,22,14,
6,61,53,45,37,29,21,
13,5,60,52,44,36,28,
20,2,4,27,19,11,3]
#Subkey = ""
for j in pc1:
self.Subkey = self.Subkey+self.Schluessel[j]
self.Teil1=self.Subkey[:int(len(self.Subkey)/2)]
self.Teil2=self.Subkey[int(len(self.Subkey)/2):]
print("Schluessel64 :",self.Subkey)
print("SchluesselTeil1 :",self.Teil1)
print("SchluesselTeil2 :",self.Teil2)
def rotationundpc2(self):
pc2 = [
13, 16, 10, 23, 0, 4,
2, 27, 14, 5, 20, 9,
22, 18, 11, 3, 25, 7,
15, 6, 26, 19, 12, 1,
40, 51, 30, 36, 46, 54,
29, 39, 50, 44, 32, 47,
43, 48, 38, 55, 33, 52,
45, 41, 49, 35, 28, 31]
rotation = [
1, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1]
k=0
#schluesselliste
self.Teil1=list(self.Teil1)
self.Teil2=list(self.Teil2)
while k<16:
#rotation
u=0
while u < rotation[k]:
self.Teil1.append(self.Teil1[0])
del self.Teil1[0]
self.Teil2.append(self.Teil2[0])
del self.Teil2[0]
self.Teil1="".join(self.Teil1)
self.Teil2="".join(self.Teil2)
self.subschluessel=self.Teil1+self.Teil2
print("Teil1: ",self.Teil1)
print("Teil2: ",self.Teil2)
print ("Subschluessel: ",self.subschluessel)
self.Teil1=list(self.Teil1)
self.Teil2=list(self.Teil2)
u+=1
#pc2 und erstellung der 16 subkeys
for index2 in pc2:
self.subkeyliste.append(self.subschluessel[index2])
k+=1
while len(self.subkeyliste)>0:
self.liste1.append("".join(self.subkeyliste[0:48]))
del self.subkeyliste[0:48]
print ("Subkeyliste: ",self.liste1)
def sechsbitunterteilung(self):
for l in range(0,16):
self.liste2.append(findall("......",listenachxor[l]))
print ("liste2: ",self.liste2)
#objekt der klasse DES wird erstellt
listenachxor=[]
Krypto=DES()
#Schluesselgenerieren
Krypto.SchluesselGenerieren()
Krypto.pc1undteilen()
Krypto.rotationundpc2()
Krypto.EingabeNachricht()
Krypto.Bitumwandlung()
Krypto.ippermutation()
Krypto.Teilen()
Krypto.Expandieren()
for p in range(0,16):
listenachxor.append(bin(Krypto.XOR(int(Krypto.liste1[p],2),int(Krypto.Bits48,2))))
listenachxor[p]=listenachxor[p].replace("b","")
print ("listenachxor: ",listenachxor)
Krypto.sechsbitunterteilung()
Krypto.SBox()
By the way the problem is on this part of the programm, the rest just works fine:
for z in range(len(self.sbox)):
for y in range(len(self.sbox[z])):
for x in range(len(self.sbox[z][y])):
ausserebits=self.liste2[x][z][0]+self.liste2[x][z][-1]
innerebits=self.liste2[x][z][1:5]
print ("innere: ",innerebits)
print ("aussere: ",ausserebits)