Mailman 3 February 2015 - scikit-image

Re: Distinguishable shades of grey
by Juan Nunez-Iglesias 24 Feb '15

24 Feb '15

> I reckon it would be similar to the middle colormap here http://earthobservatory.nasa.gov/blogs/elegantfigures/files/2013/08/three_p… (from the elegant figures block series linked above), which I've always found quite attractive. <3 ! It's gorgeous! I don't like the idea floating around later in the thread to compress the lightness range. At least for images, that's a terrible idea, limiting your dynamic range for no good reason. For scatterplots and other things with light backgrounds, I understand the logic, but perhaps a different range for different uses is warranted... Will comment something more complete to the mpl list directly in the morning... Thanks for the update and good night! On Tue, Feb 24, 2015 at 11:48 PM, Thomas Caswell <tcaswell(a)gmail.com> wrote: > Sorry, that is what I get for skimming emails too late at night :) > They are coming along, probably with a new color map rather than an > existing one. See > http://matplotlib.1069221.n5.nabble.com/release-strategy-and-the-color-revo… > Any feed back or suggestions on test patterns would be great. > -- > You received this message because you are subscribed to the Google Groups "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/d/optout.

1 0

Re: Distinguishable shades of grey
by Thomas Caswell 24 Feb '15

24 Feb '15

Sorry, that is what I get for skimming emails too late at night :) They are coming along, probably with a new color map rather than an existing one. See http://matplotlib.1069221.n5.nabble.com/release-strategy-and-the-color-revo… Any feed back or suggestions on test patterns would be great.

1 0

Distinguishable shades of grey
by Juan Nunez-Iglesias 24 Feb '15

24 Feb '15

>From this paper: http://rsif.royalsocietypublishing.org/content/early/2012/09/22/rsif.2012.0… The following quote (emphasis mine): Humans possess three cone visual pigments for conveying colour information that is said to allow humans to be able to detect approximately 10 million unique colours [8,9] but only distinguish about 30 shades of grey [10]. (Let's ignore recent movies of dubious merit in this discussion. =P) In the new MPL imshow plugin (which I recently wrote), we switch from grayscale to cubehelix when the dynamic range is too low to be displayed on a common monitor (1/255): https://github.com/scikit-image/scikit-image/blob/master/skimage/io/_plugin… Maybe the threshold should be when the difference is imperceptible to most humans (1/30)? Juan.

3 4

ANN: SciPy Latin América 2015 - Call for Proposals
by Raniere Silva 20 Feb '15

20 Feb '15

*Call for Proposals* *SciPy Latin América 2015*, the third annual Scientific Computing with Python Conference, will be held this *May 20-22* in *Posadas, Misiones, Argentina*. SciPy is a community dedicated to the advancement of scientific computing through open source Python software for mathematics, science, and engineering. The annual SciPy Conferences allows participants from academic, commercial, and governmental organizations to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. *Proposals are now being accepted for SciPy Latin América 2015*. Presentation content can be at a novice, intermediate or advanced level. Talks will run 30-40 min and hands-on tutorials will run 100-120 min. We also receive proposal for posters. For more information about the different types of proposal, see below the "*Different types of Communication*" section. *How to Submit?* 1. Register for an account on http://conf.scipyla.org/user/register 2. Submit your proposal at http://conf.scipyla.org/activity/propose *Important Dates* - *April 6th*: Talks, poster, tutorial submission deadline. - *April 20th*: Notification Talks / Posters / Tutorial accepted. - *May 20th-22nd*: SciPy Latin América 2015. *Different types of Communication* *Talks*: These are the traditional talk sessions given during the main conference days. They're mostly 30 minutes long with 5 min for questions. If you think you have a topic but aren't sure how to propose it, contact our program committee and we'll work with you. We'd love to help you come up with a great proposal. *Tutorials*: We are looking for tutorials that can grow this community at any level. We aim for tutorials that will advance Scientific Python, advance this community, and shape the future. They're are 100-120 minutes long, but if you think you need more than one slot, you can split the content and submit two self-contained proposals. *Posters*: The poster session provides a more interactive, attendee-driven presentation than the speaker-driven conference talks. Poster presentations have fostered extensive discussions on the topics, with many that have gone on much longer than the actual "session" called for. The idea is to present your topic on poster board and as attendees mingle through the rows, they find your topic, read through what you've written, then strike up a discussion on it. It's as simple as that. You could be doing Q&A in the first minute of the session with a group of 10 people. *Lightning Talks*: Want to give a talk, but do not have enough material for a full talk? These talks are, at max, 5 minute talks done in quick succession in the main hall. No need to fill the whole slot, though! -- *The SciPy LA 2015 Program **Committee* Q29udGVudC1UeXBlOiBhcHBsaWNhdGlvbi9wZ3Atc2lnbmF0dXJlDQoNCi0tLS0tQkVHSU4gUEdQ IFNJR05BVFVSRS0tLS0tDQpWZXJzaW9uOiBHbnVQRyB2Mg0KDQppUUljQkFFQkNBQUdCUUpVNTVy ekFBb0pFSHZNY3ZwVXBYWE5Ic01QLzN3Tk13TUk3YmdaN3F0SjVGamFtOXJJDQo1czlFTHZHQ0Nt dWVLKytHZytvcE9MblJySUoyT1JUS1dmVm1PV3lHQzA3M2F2d0o5Ykgra3luQkI5L3RzTFJ3DQo5 UUlpSmxFU0xWM2toSXErS1hBdDNERXlWWjVTY2VWQWsxaHhETk1WT2NEeE1wYTFRL3JRSUtzSk9B SE0ySXd6DQpnZnlRR1BjQ2JaYnBOdzNsQWFLQmMrcG53K0VVa01oOHNSNXhZUjM0bWsweE41K3Iy bHBTWDdyZjl3NkphN296DQpoWVlKTFpuTU54c3dBUUg3Tm10eDQvVEJLMmN0VU1zT2JmdXU3dkFl elZRa05QVjNqdGRNeFFzMWRNUUpRQUlYDQpzWm9zNlV1bmlSckJHZktLUldVcUZyRTROK3MzeXZK ekFTck1yMWlNZlQxSGpZcEdsUHNUUkhIWTljRUhyOVZSDQpEKzZGaCtHL3hzMFNERU9SbFVjbnFN N3VwNjNmNGNkUHI4YTd6M1ArUmNoaFdMTnE3QXpOR3NHYzNFS2U4REhqDQpmdGdCNFI3TmwyVGFM M3UzNVpFY1ozM3VaSDd4NnJlUk50Q1g2bVRxMnRYUXRidEovUTJ2KzZwb3U3b1lTdFZQDQpnQUlN OE1tZUZ0YThqZ084a2dBQWJuanpCSWJXNlphU0EyZGYzOUtDdDhsRWdmNXRBRFJlZDlQeGM3OFF2 STVBDQpHd014cXlGdnVGc1Bid1lNM2xvZDJjNlFRL1ViWEVKcWgvMTRUSlBXSFRza1NNT1V3aXBE dlpWbzQvSVFWWEdRDQpYdnR3SDU2OWJ2UGd2VU5QMWp3eWl5UjZTYVR5Qnk5ZTBlNHRabWVUTjZn Z0xXZnhScVdaRmZJMnNYMm1DN0orDQpienEvVmF1UzU2SGlPcVNXazh2Kw0KPUREQ0oNCi0tLS0t RU5EIFBHUCBTSUdOQVRVUkUtLS0tLQ0K

1 0

Re: Equivalent of watershed for cutting connected components of an image of particles?
by Georges H 19 Feb '15

19 Feb '15

I second the post of Juan regarding the watershed for non sparse data. As for clearing image borders you have a function from the segmentation module here : http://scikit-image.org/docs/dev/api/skimage.segmentation.html#clear-border On Thursday, 19 February 2015 01:04:10 UTC+1, Adam Hughes wrote: > > Hi, > > In ImageJ, one can select watershedding to break up connected regions of > particles. Are there any examples of using watershed in this capacity in > scikit image? All of the examples I see seem to use watershedding to do > segmentation, not to break connected particles in an already-segmented > black and white image. > > Also, is there a straightforward way to remove particles on a the edge of > an image? Sorry, googling is failing me, but I know this is possible. > > Thanks >

2 2

Google Summer of Code and NumFOCUS
by Raniere Silva 19 Feb '15

19 Feb '15

Hi, NumFOCUS has promotes and supports the ongoing research and development of open-source computing tools including scikit-image. This year NumFOCUS want to try be a Google Summer of Code "umbrella" mentoring organization, Umbrella organizations are mentoring organizations accepted into the Google Summer of Code program that have other open source organizations working "under" them. Sometime organizations that work very closely or have very similar goals or communities may get put together under an "umbrella." Google stills expects all organizations under the umbrella, whether accepted into the program under their title or not, to adhere to all the rules and regulations of the program. From https://www.google-melange.com/gsoc/document/show/gsoc_program/google/gsoc2… To help promote and support scikit-image. We encourage scikit-image to apply to Google Summer of Code under your own title and will be very happy if you can also do with us. If you are interested, please check https://github.com/swcarpentry/gsoc2015 and https://github.com/swcarpentry/gsoc2015/blob/master/CONTRIBUTING.md. If you have any question, please email me directly. Thanks in advance, Raniere Q29udGVudC1UeXBlOiBhcHBsaWNhdGlvbi9wZ3Atc2lnbmF0dXJlDQoNCi0tLS0tQkVHSU4gUEdQ IFNJR05BVFVSRS0tLS0tDQpWZXJzaW9uOiBHbnVQRyB2Mg0KDQppUUljQkFFQkNBQUdCUUpVNWRO dkFBb0pFSHZNY3ZwVXBYWE5JaVFQLzFjWmxrcE01SDVvTnBlamVIZE1ReHpMDQpPeFp5T21NOVda cHVLM2VMVVU1SXBmZi94QmpCcHZwZkEzL3lwNElFYmxkVExOMlhRQktlVFcxYk40U3dSSDJNDQpU RCthV3J4ZkMxYURjTDdwNjhIVDRNaHo2ZXBOTDFJN1lJZ3QyM0JTek1PZDFZTTl0Q0NvaVhoaEZC UmQ4dG4vDQpPYTUvVFVjMnBKSFBmMkpYcFZBM1JHNTYvb1Z4b25HTXkxNVBKNGhpVy9sY0hrZmpT cTVZTnJOcUdrbGZUUTAzDQppbFR5RHdoZVJCTWJxaTliU0h3RzZ2cjVTUkRkVlY0MHYyUTEwRWc0 R2NjKzZsclJqYUw1T1BoZFYyWHJieENnDQpsM0RBWFJnbTJDUDExZ3VyWWc5QjFGb3dMVzl6ZnBy eTR3Z3lCSkRHQXdxMzJlOVBjdWdmV0prVG9nZFdLbkVEDQp6MGZod21BMklnTnR2eFVweTlBK0U0 eXJnUTZOaHF0cURDNGxJbVZES0JaaVQvb3Y0c25EQ2FRTEZYOFJvcDZwDQovOFZxdEVFT0NKRCtJ NlZ0NThtSGszNFJVaUcwUWppYytjMWpzb1NFQlVQeUh1Z3drc2Z1cldJMCtrZXpITDlvDQpWQnhh ZEdiYjhpS2UwSThKdVVpK2V3OVNManczVVhoVGMvZzBkQTd5R2dVSnROZW5ZVVZ6QmphSlZZNW5U RVhwDQpJL2hTWWlmSzZCR3hFa0ZYVVNmWHh4MHFWNHhCY1ZwaDVLck1yVHViWmZxY2FXV2luZjhB ZE5BQkRqb3RRb2RrDQppV1NWUGNoS2RiQy9LOHVBL1dtZ0tveEQ5Y0JNcTZhRkI5VnFjWWcxTUpj ODNPMmFUNUNqdmtwUW5YM0kzeHZnDQp4T1BOZkpzYml1cm81UHE2VDk3Mg0KPWFWd3YNCi0tLS0t RU5EIFBHUCBTSUdOQVRVUkUtLS0tLQ0K

1 0

Re: Equivalent of watershed for cutting connected components of an image of particles?
by Juan Nunez-Iglesias 19 Feb '15

19 Feb '15

Hey Adam, I'm *guessing* the IJ method is: 1. compute the thresholded background image (ie background labeled "True") 2. compute the Euclidean distance transform (scipy.ndimage.distance_transform_edt) 3. compute the local maxima (find_local_max) and set them as seeds 4. compute watershed, using the foreground as mask. All of those functions are available in scipy/scikit-image. If you get good results, a gallery example of this would certainly be appreciated! =) However, my experience with such methods is that they only work well for reasonably sparse, perfectly spherical particles. As to removing particles on the edge, I would use a bool mask with only the edges selected, then np.unique(), then remove them manually in a for loop. I agree that it's a bit laborious... Perhaps a separate function to do this could be added to the API... On Thu, Feb 19, 2015 at 11:04 AM, Adam Hughes <hughesadam87(a)gmail.com> wrote: > Hi, > In ImageJ, one can select watershedding to break up connected regions of > particles. Are there any examples of using watershed in this capacity in > scikit image? All of the examples I see seem to use watershedding to do > segmentation, not to break connected particles in an already-segmented > black and white image. > Also, is there a straightforward way to remove particles on a the edge of > an image? Sorry, googling is failing me, but I know this is possible. > Thanks > -- > You received this message because you are subscribed to the Google Groups "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/d/optout.

1 0

Equivalent of watershed for cutting connected components of an image of particles?
by Adam Hughes 19 Feb '15

19 Feb '15

Hi, In ImageJ, one can select watershedding to break up connected regions of particles. Are there any examples of using watershed in this capacity in scikit image? All of the examples I see seem to use watershedding to do segmentation, not to break connected particles in an already-segmented black and white image. Also, is there a straightforward way to remove particles on a the edge of an image? Sorry, googling is failing me, but I know this is possible. Thanks

1 0

Re: Last blockers for 0.11 release
by Johannes Schoenberger 17 Feb '15

17 Feb '15

Excellent work @everyone! This will be a huge release. > On Feb 16, 2015, at 8:16 PM, Stéfan van der Walt <stefanv(a)berkeley.edu> wrote: > > Hi everyone > > We're overdue for the 0.11 release, and there are very few issues left > to close. I'd appreciate your feedback on this one: > > https://github.com/scikit-image/scikit-image/pull/1248 (peak detectors) > > And help in fixing: > > https://github.com/scikit-image/scikit-image/issues/1048 (doctest > failures on Mac OSX) > > I think this Sunday is a reasonable target for 0.11. Please get any > additional documentation updates in before then. > > Stéfan > > -- > You received this message because you are subscribed to the Google Groups "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/d/optout.

1 0

Re: PeerJ Staff Picks 2015
by Johannes Schoenberger 17 Feb '15

17 Feb '15

Awesome news! > On Feb 16, 2015, at 11:31 PM, Tony Yu <tsyu80(a)gmail.com> wrote: > > > On Mon, Feb 16, 2015 at 10:23 PM, Stefan van der Walt <stefanv(a)berkeley.edu> wrote: > Hi everyone > > Juan just informed me that our scikit-image paper appears on the > 2015 PeerJ Staff Picks: > > https://peerj.com/collections/13-peerjpicks2015/ > > Congratulations team! > > Stéfan > > > Sweet! > > > > -- > You received this message because you are subscribed to the Google Groups "scikit-image" group. > To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscribe(a)googlegroups.com. > For more options, visit https://groups.google.com/d/optout.

1 0