Timeline for Crop black border of image using NumPy
Current License: CC BY-SA 3.0
12 events
| when toggle format | what | by | license | comment | |
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| Jul 20, 2019 at 3:23 | history | protected | Jamal | ||
| Jun 24, 2016 at 14:10 | vote | accept | CommunityBot | ||
| Jun 24, 2016 at 9:50 | comment | added | CiaPan | Generally, as I can see in your data, what you want to remove is much less than what you need to keep. So I'd suggest not to scan the whole image to detect all non-black pixels, but rather scan all four edges line by line, to detect black stripes to be removed – and break the scan as soon as a non-black pixel is found. Note that those stripes overlap at corners, you may want to avoid scanning those overlap areas twice. However, it is still a very ineffective scanning pixel by pixel... | |
| Jun 24, 2016 at 9:09 | answer | added | Divakar | timeline score: 29 | |
| Jun 24, 2016 at 8:49 | answer | added | Gareth Rees | timeline score: 22 | |
| Jun 24, 2016 at 7:23 | history | tweeted | twitter.com/StackCodeReview/status/746242224225136640 | ||
| Jun 24, 2016 at 1:45 | history | edited | Jamal | CC BY-SA 3.0 |
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| Jun 24, 2016 at 1:39 | comment | added | user108668 | I normally use cv2 to resize it afterwards. I can use Cv2 methods if theres a quick way on it! Maybe i tagged with the wrong reasons.. But yes, i do use opencv and cv2 for python. | |
| Jun 24, 2016 at 1:36 | comment | added | 200_success | You have tagged this question as opencv, but it isn't clear that there is any use of OpenCV in your code. Can you clarify? | |
| Jun 24, 2016 at 1:34 | history | edited | 200_success | CC BY-SA 3.0 |
added 112 characters in body; edited tags; edited title; added 5 characters in body
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| Jun 24, 2016 at 1:29 | review | First posts | |||
| Jun 24, 2016 at 3:20 | |||||
| Jun 24, 2016 at 1:27 | history | asked | user108668 | CC BY-SA 3.0 |