GIMP and dithering color reductions for B/W “portraits”

The many faces of Rocco: my 2013 tests in Gimp, the image is 150 pixels wide by 154 pixels high  The image is used with the kind permission of Rocco’s owner. I have used this image before, when I posted previously on some ways to reduce colored images to B/W for possible knitting using a Mac computer, please see post on 013/03/14/ color-reduction- conversions-mac-os/. Gimp offers some alternatives to the familiar dithers and is available, free, for both PC and Mac platforms. Tutorial links on Gimp edge detection available online as of May 2019 are listed at bottom of the post.

Image_Mode_Indexed_ one bit black: immediate result, too dark

Threshold adjustments may not be made in indexed images to alter the above image, so it’s back to greyscale. Reductions to greyscale may be achieved through Image_ Mode_ Greyscale or choosing Colors_Desaturate_OK options. Desaturation offers additional choices

Image_Mode_GreyscaleColors_Desaturate_OKRocco desaturated, in “knittable portrait size”using edge detection and its algorithmsDifference of Gaussians

what happens if in addition color_ invert is used with Robertsadjusting B/W with Thresholdafter a bit of “tweaking”Image_Mode_Indexed, rendering it “knittable in 2 colors”getting silly with filling the ground with pattern behind the floating head

2021: the latest, December 2020 updated version of Gimp for Mac OS
Gimp dithering controls easily accessible with mode changes to indexedI found I got the best results adjusting the contranst in the original grey scale image prior to changing its mode to indexed and dithering (Floyd_Steinberg, normal)Hyperdither : options offered  defautlt Jarvis
default Stucki
online, options https://ditherit.com it is possible to choose from multiple palettes Sierra dither

5/4/2019 Other than GIMP: after straightforward load, convert, save, with no other adjustments, images shown in approximate 150 pixels/sts in width, no significant change results with conversion to color B/W indexed
http://gazs.github.io/canvas-atkinson-dither/
online, default settings https://29a.ch/2016/08/04/ditherlicious-1-bit-image-dithering
Check dithered results, downloaded images may be in RGB Mode. Prior to any knitting, they will need to be converted to B/W indexed.
Looking for ways to reduce the noise in dithered images I tried this conversion in XnSketch, using the photocopy effect,  beginning with the colored image of Rocco, the results:imported the result into Gimp and saved it in indexed  2 color BW and in turn 3 color indexed mode, no color adjustments, finding the result pleasantly simple beginning with the greyscale generated image followed by Mode changes in Gimp, indexed 2 color BW, then indexed 3 color, there appear to be very subtle differences with a bit more detail: Another online resource with an extensive array of dithering options https://app.dithermark.com. Here are 2 conversions using the app, the images are 2 color B/W. The presence of a third color is an illusion created by the difference in the distribution of BW color pixels, they loaded fine as viewed for knitting in Ayab, and in img2track, once I remembered to change its setting to 2 color knitting from the last used one at 4 colors It is possible to reduce images to 4 or 3 colors using the program as well: a slider for color count is used to choose the final number of colors in the reduction. Again, these instances have no added manipulation A series of dithers:
To retain the quality and size of the dithered image, download it, rather than using a screen grab. The software used to separate the chosen dither may alter the result somewhat. I am writing my posts using an iMac M1 with OS 12.0.1. At this point Ayab is not operable, img2track does open images, but in this case, with interesting distortions, and it does not download any files at all. 11/2021 A member of the FB img2track group, Amy Szczepanski, suggested this as a possible explanation “My hunch, from having looked at the source code for older software on which img2track is based, is that the new Macs are not correctly processing the data in the PDD emulation step. The PDD step relies on a module called pyserial to interact with the serial port. Based on the age of the software, I suspect that much of it needs a certain amount of housekeeping to get it to work with the newest versions of the other modules that it depends on. (Broader tech context: a lot of the original work on hacking knitting machines was written in Python 2.5, and I’d be surprised if much of it had yet been ported to Python3.) Another suggestion was that a new FTDI driver may do the trick. Drivers may be found @https://ftdichip.com/drivers/vcp-drivers/. Presently, their latest MacOS one is a beta version, for up to Mac OS 11

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