2

I want print All image pixel into array

print(image[:,:,0])

result : 

[[ 56  62  91 ...,  75  93 118]
 [ 84  71  80 ...,  75  71  88]
 [106  74 100 ...,  87  76  80]
 ..., 
 [ 72  60  48 ...,  79  78  58]
 [ 66  86  94 ...,  91  89  92]
 [143 109  82 ...,  28  26  26]]

using PIL

im = Image.open("image.BMP")
pixels = list(im.getdata())
print(pixels)

result :

(120, 120, 120), (116, 116, 116), (95, 95, 95), (113, 113, 113), (102, 102, 102), (95, 95, 95), (80, 80, 80), (87, 87, 87), (85, 85, 85), (61, 61, 61), (64, 64, 64), (104, 104, 104), (119, 119, 119),.........

Question :

How to print all pixel number without cut like this (...,)

 [ 66  86  94 ...,  91  89  92]

How to print pixel using PIL without print same number 3 times like this

(104, 104, 104), (119, 119, 119),......

and print more neat.

Improve this question

1 Answer 1

Reset to default
1

Assuming the first one is using numpy under the hood, use np.set_printoptions to control the output.

Simple example:

Code:

import numpy as np

x = np.random.randint(0, 255, size=(32, 32))
print(x)

np.set_printoptions(threshold=np.inf, linewidth=140)
print(x)

Output:

[[ 42 117  61 ... 185 136 218]
 [104 217 154 ...  56 178 215]
 [152 124 164 ... 230 195  91]
 ... 
 [ 76 105 191 ... 194 248 229]
 [228  33 100 ... 173   0  22]
 [242 216 128 ... 174 134  94]]
[[ 42 117  61  46 194 238 153 196  93  70 140  73 202 188  57  57  82 149  49 125  30 209 158 155 213 224 244  24 246 185 136 218]
 [104 217 154 229  82 243  40  67  98 125  28  14 230 104 174 124 142 124  66   3 109  55  48  69 226 178 229 239  77  56 178 215]
 [152 124 164 223  24 253 215 100  84 250   2  43  82  62  28  89  21 144 196 195 194 230 232 120 182  15  48 136  81 230 195  91]
 [148  40  78  97 246 101 179  41  60  32 160 200 237 153  97 195  84  66 123  42 216 244 155 110  57 145 129  89  96  41 108 200]
 [104 116 130  75 131 177  54  19 139 105  48  99 161  49  90 251 186 140 203 246  91 179 190  89 121  78 234  44 195 115  68 151]
 [216  17 149 179 150 205 174 186  69 251 138 173 177 202 158  88   2 252 117 140 152 109 107  38  31 101  40 150 113  93  42  20]
 [160  47   5 203  40 233 161 229 236 116   6 139 222 149  66 140 211 126  90 187 136 116  72 138  42 127   7 227  37 253 114 156]
 [161 233  76 233 199  67 105  63 200 110 185  86 100 136 144 140  22  79  17  96  75 120  53 103 213   0  59  78  70 226 134 192]
 [  9  16 104 198 230  74   1 181  21 244   9  58  87 106 234 197 193 101 233 206 214 180  81 200  83   7 224  36 239  87 207  10]
 [195  40  31 145 244  56 160 161  96  57  29 179 225 181 113 248  62 152  81 125  72 124 236 158  27  52  82 195  91 180 182 235]
 [ 27  80 238  79  81 164  24  52  32 233  50 218  53  18 207  58 227 134  69  75 237  81 234  46 235   3 109  13 221  69 251 198]
 [154 112 151 104 143 152 210 122 141 163 106  87 163  15 147  76 222 248 236 166  42  33  48 216  77 128  21 247  65  73 145 192]
 [208 253 172   6  50 193 166 179  69 211 173 155 183 212 148  80 166   1  67 117 216 226 228 220  64 195 228  51 104 159 190 251]
 [194  76 183 196  49  24  22 170 224 209  18 139  99 181  39 242 103 252 221  85 165 133  50 240  40 174  94 121 109  45   0  24]
 [ 16  51  46  74 196  40 222 241 145 163 253 220 195 164  48  83 157  48 108 171 225  24  43 239  34 219  46 190  72 146 166  24]
 [  6  11 138 157  97 154 114 131 200 131 248  98  58 115 136 239 180 170 212 166 130 228 131   3 251  52   6 149 247 230 139  96]
 [ 73 243  71 110  94  29  80   5  75  44 169 178 220  17 251 214 174  95 123 252 139 184 200 229  69 252 161 243 107 214 234 199]
 [104  82 135 126 177 114  66  44 188 207 121 196  59 245 172 102 200  34 128  10 179 210  46 199 254 218 206 212  23 143 116 112]
 [217 175  51 207 211 143 186  69 243 121  44  95 241 227 126 250 184 169  92  87 198 220 178 224 145   8 222 177  12 126 232  46]
 [ 64  30  51 142 198   2 193 209  71  55   1 139  43  96  20  43 188  76  70  51 128  79 209 193 213 201 115 139 154 170 235  69]
 [132 177  68 129  52 218 136 194 221 173 198  14  56 112 139  99 203  18  56  30  17   2 179 132  70  46 152  69 128 111 201 227]
 [112 250  32  77 122  45 118 189   8 182  16 126 250 231  45  80  93 104 175 188 203 145  60  12 199 103 162  94 107 229 155 116]
 [242 160  70 116 173 105  15  52 119 182 158 118 229  89 104  40 184 171  16  75  81 188   4 178 232 147 151 127 223 126  22  75]
 [101 170 192 172 188 245  62 115 254  24 180  28  71 113 159 196 216 217  11 102   9 190 180 149  33   0  67 234  70 207 137 118]
 [ 86 155 194  13 112 190 104 172  92  15 210  96  29 130  77 215  97   5  57 251 236  33 246 234 144 230 244 164 167  72  50 204]
 [163  88 188  11  61  75 196 239  68  88 241  48 144 172  57 186 107 227  88 147  37 174 125 253  17 155 177  49 156  93  56 225]
 [200  58 127  87 228  80  70 150 202 217 170 235 246  13 247 158 102 108  22 134 100 161 208 170 166 100  38  74 166 253  16  66]
 [ 65 233  34  17  27  90 171 142  27  48  28 218  79 179  31 137 132 130 189  26 166  16  84 190 126 172   2  10 110 204 207  69]
 [ 38 237  55  52  17 245 199 110 118 226  46 106  15  67 169  58 216 157 123 194 100  82  91 174  60 108  75  21  39 147  88 249]
 [ 76 105 191 183 241  73 121 131  30  88 127 213 121 210  37   7  59 106 172 237  58 241  21  35  65 193 103   5  11 194 248 229]
 [228  33 100 153 247  82 233 167 135 140 158 194 149 176 202  88  34 141 123  88 117 231 191  32 231 234 141 244  66 173   0  22]
 [242 216 128  97 184  52 251 160  23 243 138  96 199 204  85  52 168 184 173  99 216 229  28 182 114  95  32   5 187 174 134  94]]
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4 Comments

Thank you for your answer. do you know how to save the number to text or excel?
Look at np.savetxt (enough for csv-like tasks) and the more general entry np: input/output. For excel you will need some 3rd-party library. Not my cup of tea, but i would recommend in this case to look what pandas is using (probably well-done decision given available candidates). Excel I/O
thank you, actually np.savetxt works for me but i got an error ValueError: cannot reshape array of size 504273 into shape (407,413) do you know how to fix it ?
This is not related to this question and is too broad. Do some basic numpy-research first. Learn how to read their docs. The answer to why it's not working is: 407 * 413 = 86691 != 504273. It's not even a multiple (e.g. 3 when people discarded color-channels) so you did some serious mistake. But well... totally off-topic here.

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