Mailman 3 September 2017 - scikit-image

Re: [scikit-image] 回复：Re: Code for the short course 'Image Processing using Python', @ IAMG2017
by Juan Nunez-Iglesias 04 Oct '17

04 Oct '17

On 21 Sep 2017, 5:00 PM +1000, Stefan van der Walt <stefanv(a)berkeley.edu>, wrote: > Thanks, I never noticed! All the lessons were contributed for teaching purposes, so I don't imagine adding a license now would be a problem. CC-BY is fine, although we should also consider CC-0. Sure. How about CC0 + adding a note in the readme, “if you find these tutorials useful, we appreciate mentioning them in any derivative works.”

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回复：Re: Code for the short course 'Image Processing using Python', @ IAMG2017
by imagepy＠sina.com 21 Sep '17

21 Sep '17

Hi Stefan: "segmentation lesson from the skimage_tutorial repo" did you means this?(https://github.com/scikit-image/skimage-tutorials/blob/master/lecture…, I am writing a simple imageprocessing book, It may be useful for me. Best regardsYXDragon----- 原始邮件 ----- 发件人：Stefan van der Walt <stefanv(a)berkeley.edu> 收件人：Alexandre Fioravante de Siqueira <siqueiraaf(a)gmail.com>, scikit-image(a)python.org 主题：Re: [scikit-image] Code for the short course 'Image Processing using Python', @ IAMG2017 日期：2017年09月21日 05点16分 Hi Alex On Tue, Sep 19, 2017, at 21:25, Alexandre Fioravante de Siqueira wrote: as I said in an old previous e-mail, I presented a short course using scikit-image for processing microscopy images at IAMG2017 (short course 8 at <http://iamg2017.com/courses/>). An alpha version of the codes is now available; please feel free to check it at <https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017>. Thanks for sharing these! Since it is still very raw, I'd be glad to receive your comments, suggestions and ideas! I'd say 1) stick to gray, viridis, and other reliable colormaps and 2) plot the found features so that they are easier to observe (currently just pixels inside a big image). You may also want to take a look at the segmentation lesson from the skimage_tutorial repo, which has a few sketches to clarify the workings of watershed. Best regards Stéfan _______________________________________________ scikit-image mailing list scikit-image(a)python.org https://mail.python.org/mailman/listinfo/scikit-image

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回复：Re: my watershed
by imagepy＠sina.com 21 Sep '17

21 Sep '17

add one:if scikit-image can implements a ridge filter. just like watershed mixed with the skeleton. make all region a same label, then do level loop, just stop when one pixel left. It's usful in geography and hydrology analysis. ----- 原始邮件 ----- 发件人：Juan Nunez-Iglesias <jni.soma(a)gmail.com> 收件人：scikit-image <scikit-image(a)python.org>, imagepy(a)sina.com, "Mailing_list_for_scikit-image_(http://scikit-image.org)" <scikit-image(a)python.org> 主题：Re: [scikit-image] my watershed 日期：2017年09月21日 13点48分 Hi Yan, Thanks for this. Simple functions are very good for one’s own images, as well as to understand an algorithm, but for a widely used library like scikit-image, flexibility and robustness are least as important as speed. In skimage, we aim to support floating point input images, for which your code won’t work. There is a lot of thought into edge cases going into the skimage implementation, which unfortunately could have an effect on performance. The question we need to solve isn’t “can we make a super-fast watershed implementation”, but, “can we make a flexible and robust implementation that is also fast?” Using Numba is certainly not off-limits, but any candidate implementation should at a minimum pass the skimage test suite. I once tried a level-by-level implementation of watershed, by the way. It has a fatal flaw, which is that valleys with no markers will never get labeled. Here’s a test case that works with skimage but fails in your implementation. (Note also that your implementation overwrites the seeds image, which is pretty crazy. =) Thanks again! Juan. In [44]: import watershed In [45]: from skimage import morphology In [46]: import numpy as np In [47]: image = np.array([1, 0, 1, 0, 1, 0, 1], dtype=np.uint8) In [48]: seeds = np.array([0, 1, 0, 0, 0, 2, 0]) In [49]: morphology.watershed(image, seeds) Out[49]: array([1, 1, 1, 1, 2, 2, 2], dtype=int32) In [50]: watershed.watershed(image, seeds) Out[50]: array([0, 0, 0, 0, 0, 0, 0]) In [51]: seeds Out[51]: array([0, 0, 0, 0, 0, 0, 0]) On 12 Sep 2017, 6:34 AM +1000, imagepy(a)sina.com, wrote: Hi: Now It supports nd. but less of test. this image, skimage cost 20s, mine less than 1s. It is wrriten with numba in 90 lines. did not support compactness, but it's simple, and fast. YXDragon _______________________________________________ scikit-image mailing list scikit-image(a)python.org https://mail.python.org/mailman/listinfo/scikit-image

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my watershed
by imagepy＠sina.com 21 Sep '17

21 Sep '17

Hi:Now It supports nd. but less of test. this image, skimage cost 20s, mine less than 1s.It is wrriten with numba in 90 lines. did not support compactness, but it's simple, and fast. YXDragon

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Re: [scikit-image] Code for the short course 'Image Processing using Python', @ IAMG2017
by Stefan van der Walt 20 Sep '17

20 Sep '17

Hi Alex On Tue, Sep 19, 2017, at 21:25, Alexandre Fioravante de Siqueira wrote:> as I said in an old previous e-mail, I presented a short course using > scikit-image for processing microscopy images at IAMG2017 (short > course 8 at <http://iamg2017.com/courses/>).> An alpha version of the codes is now available; please feel free to > check it at > <https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017> > . Thanks for sharing these! > Since it is still very raw, I'd be glad to receive your comments, > suggestions and ideas! I'd say 1) stick to gray, viridis, and other reliable colormaps and 2) plot the found features so that they are easier to observe (currently just pixels inside a big image). You may also want to take a look at the segmentation lesson from the skimage_tutorial repo, which has a few sketches to clarify the workings of watershed. Best regards Stéfan

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Code for the short course 'Image Processing using Python', @ IAMG2017
by Alexandre Fioravante de Siqueira 19 Sep '17

19 Sep '17

Dear all, as I said in an old previous e-mail, I presented a short course using scikit-image for processing microscopy images at IAMG2017 (short course 8 at <http://iamg2017.com/courses/> <http://iamg2017.com/courses/>). An alpha version of the codes is now available; please feel free to check it at <https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017> <https://github.com/alexandrejaguar/lectures/tree/master/2017/iamg2017>. Since it is still very raw, I'd be glad to receive your comments, suggestions and ideas! Thank you in advance. Kind regards, Alex -- ------------------------------------------------------------------------------ Dr. Alexandre 'Jaguar' Fioravante de Siqueira Grupo de Cronologia - Sala 13 Departamento de Raios Cósmicos e Cronologia - DRCC Instituto de Física "Gleb Wataghin" - IFGW Unicamp - Universidade Estadual de Campinas Rua Sérgio Buarque de Holanda, 777 Cidade Universitária Zeferino Vaz - CEP 13083-859 Campinas - SP - Brazil Phone: +55(19)3521-5362 Lattes curriculum: 3936721630855880 <http://lattes.cnpq.br/3936721630855880/> ORCID: 0000-0003-1320-4347 <http://orcid.org/0000-0003-1320-4347> Personal site: programmingscience.org <http://www.programmingscience.org/> Github: alexandrejaguar <http://www.github.com/alexandrejaguar/> Skype: alexandrejaguar Twitter: alexdesiqueira <http://www.twitter.com/alexdesiqueira/> ------------------------------------------------------------------------------

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转发：some question about h_minma (need a paremeter, and can run faster)
by imagepy＠sina.com 10 Sep '17

10 Sep '17

Sorry, May be I had send one, But I am not sure if I send suceessfully, because of the attachment is too large, so I send again, with a jpg format. Hi every one: As I mentioned befor, In the official example, use watershed to segment two circle, In this example, use pick_local_max to find the seed. But When I try on other binary images, there always are two local_max nearby, then the segment be too trivial. And I use the h_maxma and h_minma, I have some trouble: 1. when a region has more than one min value(same but not nearby), the result will mark them all. (I want to use them as seed to watershed, So I need any one, else the region will be broken, can we add a parameter to control?)2. h_minma run too slowly, (what more, the watershed run more slowly... so my program crashed! I had heard Juan will improve it in the next version) So I wrote h_minma/maxma and watershed myself (as a sub package of my project imagepy). My watershed now only support 2D, But the h_minma now is OK, works on nd. I had test one image: scikit-image's h_minma runs in 15s, and mine runs in 0.3s, 45times. I will attach my code and test image. If any one can have a look, and improve the h_minma function? I will write a issue on github soon. YXDragon

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回复：Re: 转发：some question about_h_minma_(need_a_paremeter,_and_can_run_faster)
by imagepy＠sina.com 10 Sep '17

10 Sep '17

Hi Stefan:OK, I would commen my code, and try to profile the skimage's code. then start a issue on github.I once tried to contribute to scikit-image. But give up, for I am averse to write cython. I prefer writting in pure C, and importting with ctypes, or writting pure python with numba (JNI recommend to me). So I agree with using numba to extend scikit-image(we discussed before).And I had wrote or improve some other function may be usful. I improved the medal axis, watershed, h_maxma/minma, and writed a ridge algrism(extract the ridge or river valley), and we can use them in imagepy interactively. I will attach some snapshot, please have a look.(I had wrapped many functions of scipy.ndimage and skimage in imagepy, and have built some user base in my country (China), they will feed back some questions to me, I think it's useful to imagepy and skimage) ----- 原始邮件 ----- 发件人：Stefan van der Walt <stefanv(a)berkeley.edu> 收件人：scikit-image(a)python.org 主题：Re: [scikit-image] 转发：some question about_h_minma_(need_a_paremeter,_and_can_run_faster) 日期：2017年09月10日 11点29分 Hi, YXDragon On Fri, Sep 8, 2017, at 21:25, imagepy(a)sina.com wrote: So I wrote h_minma/maxma and watershed myself (as a sub package of my project imagepy). My watershed now only support 2D, But the h_minma now is OK, works on nd. I had test one image: scikit-image's h_minma runs in 15s, and mine runs in 0.3s, 45times. I tested on my machine and can confirm the slowness. Would you be willing to help profile the code, to find out why it is so slow? Best regards Stéfan _______________________________________________ scikit-image mailing list scikit-image(a)python.org https://mail.python.org/mailman/listinfo/scikit-image

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回复：Re: 转发：some question about_h_minma_(need_a_paremeter,_and_can_run_faster)
by imagepy＠sina.com 10 Sep '17

10 Sep '17

sorry! Perhaps I wrote mixed and disorderly, I want to say, I had improve or wrote some function, I want to contribute them when we support numba. ----- 原始邮件 ----- 发件人：Stefan van der Walt <stefanv(a)berkeley.edu> 收件人：scikit-image(a)python.org 主题：Re: [scikit-image] 转发：some question about_h_minma_(need_a_paremeter,_and_can_run_faster) 日期：2017年09月10日 11点29分 Hi, YXDragon On Fri, Sep 8, 2017, at 21:25, imagepy(a)sina.com wrote: So I wrote h_minma/maxma and watershed myself (as a sub package of my project imagepy). My watershed now only support 2D, But the h_minma now is OK, works on nd. I had test one image: scikit-image's h_minma runs in 15s, and mine runs in 0.3s, 45times. I tested on my machine and can confirm the slowness. Would you be willing to help profile the code, to find out why it is so slow? Best regards Stéfan _______________________________________________ scikit-image mailing list scikit-image(a)python.org https://mail.python.org/mailman/listinfo/scikit-image

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Re: [scikit-image] HOGDescriptor
by Stefan van der Walt 09 Sep '17

09 Sep '17

Hi Peter On Sat, Sep 9, 2017, at 07:28, Peter Balazovic wrote: > I see there is HOG descriptor implemented within scikit image, I > wonder how can I reused or compare exmples given > http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_hog.…> with OpenCV where I can find > http://docs.opencv.org/3.1.0/d5/d33/structcv_1_1HOGDescriptor.html.> I want to intialize and compute HoG descriptor with both same > parametrs. How and which the hog paramerts from scikit relates to > OpenCV one? Anyone can help? The API reference for HoG might help: http://scikit-image.org/docs/dev/api/skimage.feature.html?highlight=hog#ski… Best regards Stéfan

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HOGDescriptor
by Peter Balazovic 09 Sep '17

09 Sep '17

Hello. I see there is HOG descriptor implemented within scikit image, I wonder how can I reused or compare exmples given http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_hog.… with OpenCV where I can find http://docs.opencv.org/3.1.0/d5/d33/structcv_1_1HOGDescriptor.html. I want to intialize and compute HoG descriptor with both same parametrs. How and which the hog paramerts from scikit relates to OpenCV one? Anyone can help? Thank you very much.

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some question about h_minma (need a paremeter, and can run faster)
by imagepy＠sina.com 08 Sep '17

08 Sep '17

Hi every one: As I mentioned befor, In the official example, use watershed to segment two circle, In this example, use pick_local_max to find the seed. But When I try on other binary images, there always are two local_max nearby, then the segment be too trivial. And I use the h_maxma and h_minma, I have some trouble: 1. when a region has more than one min value(same but not nearby), the result will mark them all. (I want to use them as seed to watershed, So I need any one, else the region will be broken, can we add a parameter to control?)2. h_minma run too slowly, (what more, the watershed run more slowly... so my program crashed! I had heard Juan will improve it in the next version) So I wrote h_minma/maxma and watershed myself (as a sub package of my project imagepy). My watershed now only support 2D, But the h_minma now is OK, works on nd. I had test one image: scikit-image's h_minma runs in 15s, and mine runs in 0.3s, 45times. I will attach my code and test image. If any one can have a look, and improve the h_minma function? I will write a issue on github soon. YXDragon

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GLCM for non-rectangular image
by NASAHARA Kenlo 06 Sep '17

06 Sep '17

Dear scikit-image community: I am trying GLCM functions in scikit-image. http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_glcm… I wonder whether they can treat images with irregular shapes, such as a circle, an oval, or some more complex forms (not only rectagle). In the "greycomatrix", function: def greycomatrix(image, distances, angles, levels=None, symmetric=False, normed=False): image : array_like Integer typed input image. Only positive valued images are supported. If type is other than uint8, the argument `levels` needs to be set. the "image" seems to be required to be a rectangle. If NAN or NULL values are allowed in the "image", and the function skips treating those "no-data" pixels assigned with NAN or NULL, then we may be able to treat any shapes of image, by filling the pixels outside the boudary with NAN or NULL. However, in the source code of "_glcm_loop" function (https://searchcode.com/codesearch/view/83509141/), all the pixels within the rectangular image are scanned, without permitting "no-data". My questions: 1. Do you know how to treat GLCM in non-rectangular image with scikit-image? 2. If not, do you know any other ways to do that instead of scikit-image? 3. Do you think it is a reasonable idea to change GLCM functions in scikit-image so that they can treat no-data (allowing NAN or NULL)? -- Kenlo Nishida Nasahara Faculty of Life and Environmental Sciences University of Tsukuba, Japan 305-8572 24dakenlo(a)gmail.com

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Re: [scikit-image] Release date for 0.14
by Stefan van der Walt 01 Sep '17

01 Sep '17

Hi Egor On Fri, Sep 1, 2017, at 02:30, Egor Panfilov wrote: > I propose to set a release date for scikit-image 0.14 on the mid of > October (15th should do). Also, I'd volunteer to be a release manager > for the release.> Please, let me know if you agree. If so, I kindly ask you to take a > deep breath and try to review some of the scheduled PRs in the > coming month. That's a fantastic offer; we'll take it! :) October is also difficult to me, so let's aim for mid-November? Stéfan

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回复：Re: Release date for 0.14
by imagepy＠sina.com 01 Sep '17

01 Sep '17

Hi Juan:What do you mean "undoing the speed regression of watershed"? I found watershed run very slowly with large image, and I am writting one with numba. YXDragon ----- 原始邮件 ----- 发件人：Juan Nunez-Iglesias <jni.soma(a)gmail.com> 收件人：scikit-image List Mailing <scikit-image(a)python.org>, "Mailing_list_for_scikit-image_(http://scikit-image.org)" <scikit-image(a)python.org> 主题：Re: [scikit-image] Release date for 0.14 日期：2017年09月01日 21点48分 Hi Egor, Thanks for your support! I would prefer Nov 15 because I know for a fact that I will struggle to finish some of the major PRs that I need to get in before 0.14, including undoing the speed regression of watershed, and nd moments. (For the first one I don’t even know where to start currently.) Juan. On 1 Sep 2017, 12:31 PM +0300, Egor Panfilov <egor.v.panfilov(a)gmail.com>, wrote: Dear all, I propose to set a release date for scikit-image 0.14 on the mid of October (15th should do). Also, I'd volunteer to be a release manager for the release. Please, let me know if you agree. If so, I kindly ask you to take a deep breath and try to review some of the scheduled PRs in the coming month. Thanks in advance, and have a nice we! Regards, Egor Panfilov _______________________________________________ scikit-image mailing list scikit-image(a)python.org https://mail.python.org/mailman/listinfo/scikit-image _______________________________________________ scikit-image mailing list scikit-image(a)python.org https://mail.python.org/mailman/listinfo/scikit-image

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Re: [scikit-image] Release date for 0.14
by Juan Nunez-Iglesias 01 Sep '17

01 Sep '17

Hi Egor, Thanks for your support! I would prefer Nov 15 because I know for a fact that I will struggle to finish some of the major PRs that I need to get in before 0.14, including undoing the speed regression of watershed, and nd moments. (For the first one I don’t even know where to start currently.) Juan. On 1 Sep 2017, 12:31 PM +0300, Egor Panfilov <egor.v.panfilov(a)gmail.com>, wrote: > Dear all, > > I propose to set a release date for scikit-image 0.14 on the mid of October (15th should do). Also, I'd volunteer to be a release manager for the release. > Please, let me know if you agree. If so, I kindly ask you to take a deep breath and try to review some of the scheduled PRs in the coming month. > > Thanks in advance, and have a nice we! > > Regards, > Egor Panfilov > _______________________________________________ > scikit-image mailing list > scikit-image(a)python.org > https://mail.python.org/mailman/listinfo/scikit-image

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Release date for 0.14
by Egor Panfilov 01 Sep '17

01 Sep '17

Dear all, I propose to set a release date for scikit-image 0.14 on the mid of October (15th should do). Also, I'd volunteer to be a release manager for the release. Please, let me know if you agree. If so, I kindly ask you to take a deep breath and try to review some of the scheduled PRs in the coming month. Thanks in advance, and have a nice we! Regards, Egor Panfilov

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