Automatically detect - remove shapes on more images (and inpaint them)

prawnsushi · May 9, 2023, 6:49pm

Hi, i was just wondering… Will this work if the coin is ( maybe just slightly) rotated in the original picture? Maybe it could just recognize a round object?

Reptorian · May 9, 2023, 7:01pm

I think @grosgood gave me a idea.

Here is what I have for now, and I know it’s not ideal:

rep_tool_for_silvio_grosso_detect_and_inpaint_and_insert_2_cm:

number_of_images:=$!

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

radius={(w>>1)+2}

store. coin

foreach {
 $coin
 
 +matchpatch[0] [1],16,16,1,10,0,0,1
 channels[-1] 2
 top_left_coordinates={[xm,ym]}
 remove[-1]
 echo $top_left_coordinates
 
 eval radiuses=vector(#2,$radius);coordinates=[$top_left_coordinates];coordinates+=radiuses>>1;ellipse(#0,coordinates+[3,3],radiuses,0,1,255,0,255);
}

For [0] image:

Next step is to inpaint, then insert that 2 cm thingie.

grosgood · May 9, 2023, 7:10pm

Features on the coin face get buried in the noise. For the terminally curious, alternate the pipeline with ‘display’ stops (d , between every command) and single step through the pipeline. The score channel in the correspondence map produced by matchpatch (blue: channel 2) mainly have pel values in the millions, except around the coin, where scores drop by an order of magnitude (see comparison in the fill pel processor). But there is too much noise to distinguish coin features. Noise could be a big problem with this approach; that’s why I am interested in @Silvio_Grosso playing around with other images. This particular image may be the lucky one. But if some of his botanicals are black-eyed susans, this approach might detect all their eyes and run off the road with a dozen matches.

snibgo · May 9, 2023, 7:38pm

I expect this can be done entirely with a G’MIC script.

G’MIC includes programming constructs (loops, conditionals, etc) that ImageMagick (IM) does not include. Doing the job with IM also needs some work in a shell script (eg bash or Windows BAT). However, I know IM better than G’MIC, so that is how I would do it.

As usual, there are many possible methods. Overall, we need to (a) find the coin, (b) infill the coin, (c) make a 2cm scale slightly smaller than the coin and (d) composite that over the image.

(Wikipedia says a 5 euro cent coin is 21.25mm diameter.)

What visually distinguishes the coin? It is a dark circle on a white background. In the OP example, it is also a distinct colour. I won’t rely on that, because an image might have dark brown twigs the same colour as the coin.

So I assume the coin is the only dark roughly circular object. I also assume the coin never overlaps with plants.

I threshold the image so we get black objects on a white background. Then I list each black object, the “connected components”. The bounding box of the coin will be roughly square. I will assume that only one bounding box is roughly square. If there are many, we could also compare the size (in pixels) of the component with the area of the bounding box; if the component is roughly pi * r^2 then we assume it is circular.

The -morphology denoises.

For inpainting, we expand the bounding box by 10 pixels in each dimension, so we include the shadow of the coin.

Windows BAT script:

set Infile=coinPlant.jpeg
set Outfile=coin2cm.jpeg

set NumSq=0

for /F "usebackq tokens=1-5 delims=: " %%A in (`%IMG7%magick ^
  %Infile% ^
  -threshold 50%% ^
  -morphology open disk ^
+write x1.png ^
  -define "connected-components:verbose=true" ^
  -define "connected-components:area-threshold=1000" ^
  -connected-components 8 ^
  info:`) do (
  if "%%E"=="srgb(0,0,0)" (
    for /F "tokens=1-4 delims=x+" %%G in ("%%B") do (
      set WW=%%G
      set HH=%%H
      set XX=%%I
      set YY=%%J
      echo GHIJ= %%G %%H %%I %%J
      echo WHXY= !WW! !HH! !XX! !YY!
      set /A HHlo=!HH!*90/100
      set /A HHhi=!HH!*110/100
      if !WW! gtr !HHlo! if !WW! lss !HHhi! (
        echo Squarish
        set /A NumSq+=1
        set /A coinXX=!XX!
        set /A coinYY=!YY!
        set /A sqWW=!WW!+20
        set /A sqHH=!HH!+20
        set /A sqXX=!XX!-10
        set /A sqYY=!YY!-10
        set /A twoCm=!WW!*2000/2125
      )
    )
    echo %%A %%B %%C %%D %%E %%F
  )
)

echo NumSq=%NumSq%

if not %NumSq%==1 (
  echo %0: %Infile% found %NumSq% squarish components.
  exit /B 1
)

echo Found one squarish bounding box: %sqWW% x %sqHH% + %sqXX% + %sqYY%
echo twoCm = %twoCm%

rem Make the coin transparent.

%IMG7%magick ^
  %Infile% ^
  ( +clone ^
    -fill White -colorize 100 ^
    -fill Black -draw "translate +%sqXX%+%sqYY% rectangle 0,0,%sqWW%,%sqHH%" ^
+write x2.png ^
  ) ^
  -alpha off ^
  -compose CopyOpacity -composite ^
  coinTrans.png

rem Fill the hole

%IM7DEV%magick ^
  coinTrans.png ^
  -process 'fillholes wr 3 lsr 50 cp onepixel auto_repeat verbose' ^
  -process 'fillholes wr 3 lsr 50 cp onepixel auto_repeat verbose' ^
+write x3.png ^
  ( -size %twoCm%x30 xc:None ^
    -fill Black ^
    -draw "rectangle 0,2,%%[fx:w-1],4" ^
    -draw "rectangle 0,0,0,6" ^
    -draw "rectangle %%[fx:w-1],0,%%[fx:w-1],6" ^
    -draw "rectangle %%[fx:w/2],0,%%[fx:w/2],6" ^
    -pointsize 20 ^
    -gravity Center -annotate +0+0 "2 cm" ^
+write x4.png ^
  ) ^
  +gravity ^
  -geometry +%coinXX%+%coinYY% ^
  -compose Over -composite ^
  %Outfile%

Each line like “+write xN.png” is only for debugging, and can be removed.

This uses my Process module fillholes, which needs IM to be rebuilt. If you don’t want to rebuild IM, my page Filling holes shows alternative methods.

The result, coin2cm.png, is:

prawnsushi · May 9, 2023, 7:45pm

I see. Could it detect if pixels around the “supposed coin” are the same color as the background? ( Didn’t want to say white here, it could be a very light grey, or any color, or noisy). I guess it would still lead to false positives…

Silvio_Grosso · May 9, 2023, 8:22pm

Hello @grosgood

Just tried on Windows 10 (powershell) - gmic-3.2.4-cli-win64
With a different jpg image (apple1.jpg)

With GIMP I have cropped the coin from this image (apple1.jpg) and exported and renamed as coins.png

Unfortunately, It throws up an error:
PS C:\Users\gross\Downloads\gmic_3.2.4_cli_win64\gmic-3.2.4-cli-win64> .\gmic.exe apple1.jpg coins.png +matchpatch[0] [1],16,16,1,10,0,0,1 channels. 2 fill. ‘i(x,y)<200000?1:0’ +barycenter. e ‘{@0,1}’
[gmic]-0./ Start G’MIC interpreter.
[gmic]-0./ Input file ‘apple1.jpg’ at position 0 (1 image 800x533x1x3).
[gmic]-1./ Input file ‘coins.png’ at position 1 (1 image 141x126x1x4).
[gmic]-2./ Estimate correspondence map between image [0] and patch image [1], using 16x16x1 patches, 10 iterations, 0 randomizations and occurrence penalization 0 (score returned).
[gmic]-2./ *** Error *** Command ‘matchpatch’: [instance(800,533,1,3,000001b0d6987040,non-shared)] gmic::matchpatch(): Instance image and specified patch image (141,126,1,4,000001b0d6706a70) have different spectrums.

To sum up.
From my understanding of this command:

At present, with GIMP, I should add manually the graduated scale (2 cm) on every image present in a folder.
Afterwards, with your G’mic script, I can automatically remove the coins from all the images.
Is it correct?

Silvio_Grosso · May 9, 2023, 8:27pm

Hello @snibgo

Just installed ImageMagick on my computer with Windows 10 (ImageMagick-7.1.1-8-Q16-HDRI-x64-dll.exe).

Thanks a lot.
I am going to try your .bat script
If I understand it correctly it should even automatically add the graduated scale (2 cm)

Silvio_Grosso · May 9, 2023, 8:28pm

Hello everyone,

In case you are interested here are 4 .jpg images to test (zip folder - Dropbox):
images

There is one (coins.jpg) which might be tricky because there are plenty of coins

grosgood · May 9, 2023, 8:58pm

Remove the alpha channel from coins.png. That’s the ‘different spectrums’ error. G’MIC, in its charming way, calls the aggregate number of channels the image’s spectrum.

Here’s the rough workflow

devise a mask of your ‘benchmark euro’ Use that for the entire batch. It could look something like my 64,64,1,3 mask of your euro. I just cropped it from your botanical.
Iterate over the batch, using something like my pipeline . For each image:
The third image in the list has been derived from the correspondence map to isolate the coin. Let us call it the ‘correspondence mask’
Use one copy of the correspondence mask as a mask for inpaint_morpho. to blot out the coin in your botanic image - select the botanic, pass the mask as an argument.
-input your centimeter scale from wherever you stash your centimeter scales. That, having an alpha channel, can be alpha-composed onto the botanical image. The barycenter coordinates identify the center of the coin, Or look at @Reptorian 's script: he locates the upper left corner of the image (he doesn’t use barycenter)
Use image to composite the scale and the botanical image. The centimeter scale would be the ‘sprite’ image and the botanical the selected image. The x,y coordinate arguments to image locates the upper-lefthand corner of the sprite. depth, z, and channel, c, are zero and opacity is = 1.
Output the composite botanical+centimeter scale and move onto the next botanical, reusing the coin mask. -remove any other intermediary image (correspondence mask and such)

I think 1-7 can be wholly automatic; but NB my black-eye susan comment made to @prawnsushi. Some images may break. When I get home and after the puppy walk, I think I can script this out.

That’s it for now. Hope this helps.

Silvio_Grosso · May 9, 2023, 9:15pm

@grosgood

Remove the alpha channel from coins.png

Thanks. Somewhat, It did the trick

Reptorian · May 9, 2023, 9:17pm

I have an approach that may work for all cases in context of selection.

apple1.jpg apple2.jpg blueberry.jpg foreach { rgb2lch split c keep[1] gt 20 }

Here’s the problem. Filling those little holes that shows up. After that, it’s just a matter of detecting circle with matchpatch or by area-size selection, and using inpaint, and then using image command to do the 2cm thing.

Right now, I don’t feel like finishing this up, so I will give pointers instead.

grosgood · May 9, 2023, 9:38pm

Tee, Hee. Did a rather better job of picking the apple rather than the euro, no? I expected that contrary cases could arise; am hoping that contrary cases could be small in number or constrained (ever the optimist). Leaving the office now. Thanks for something to ponder on whilst riding on the subway and walking The Little Mutt…

And thank you for the interesting problem!

Reptorian · May 9, 2023, 10:48pm

Here’s the code:

rep_tool_for_silvio_grosso_detect_and_inpaint_and_insert_2_cm:

foreach {
 +rgb2lch split[-1] c keep[0,-2] gt[-1] 15
 +area[-1] 0,0 
 lt[-1] 900
 if iv
  inpaint_pde[-2] [-1],0,0,0
 fi
 rm[-1]
 area_fg[-1] 0,1
 +gt[-1] 1000 *[-2] [-1] rm.
 +colormap[-1] 0
 for w#-1>4 {
  +gt. {ia} *[-2] [-1] rm. colormap. 0 
 }
 eq[-2] {i(#-1,1)} rm.
 dilate[-1] 6
 inpaint_pde[-2] [-1],100%,2,1
}

Not really a good result, but oh well.

David_Tschumperle · May 10, 2023, 6:14am

@Silvio_Grosso , what you need here is clearly a circle detector (usually implemented with the Circle Hough Transform (CHT)), as the coins in your images have different sizes and colors.

CHT is not already implemented in G’MIC, but 100% sure it can be done (the classical hough transform for detecting lines is implemented and works as expected).
It could be a nice addition TBH.

Once the coin is detected, using one of the inpaint method of G’MIC should be OK to remove it.

Silvio_Grosso · May 10, 2023, 8:16am

Hello David,

Thanks a lot for your reply: you certainly know where the problem lies

Luckily for me, pretty much all my images have a white background.
Some of them, which I can fix manually, have a black one (because the white would not be fitting)

I suppose that, once the coin in every jpg image is detected, in-painting AND adding automatically the 2 cm graduated scale should be “trivial”

Btw, many of my images have more perfect “circles” on them (petri dish for plant pathology…)

Anyway, once again, thanks a lot indeed for your work on G’MIC over the years

David_Tschumperle · May 10, 2023, 8:53am

Even if your have other circle-shaped structures in your image, it should not be that hard to avoid detecting them as coins, because of the constraint we can put on the circle radius that should lie within a particular range.

I’m really busy at the moment (I have an audition in Paris tomorrow), but I might try to implement the Circle Hough Transform in G’MIC by the end of May, if I have some time.

I’m pretty sure that it could be a fun challenge for @grosgood or @garagecoder too

Silvio_Grosso · May 10, 2023, 9:04am

Hello @David_Tschumperle

I’m really busy at the moment (I have an audition in Paris tomorrow), but I might try to implement the Circle Hough Transform in G’MIC by the end of May, if I have some time.

Sure. No problem at all

samj · May 10, 2023, 10:42am

@David_Tschumperle

Bonjour,

It’s a good idea to create this function to detect circles.
I saw that this function existed in the OpenCV library : HoughCircles()
In the examples found on the internet this function is very simple to use.
I await the equivalent in G’MIC with great interest :o)

Silvio_Grosso · May 10, 2023, 11:09am

Hello @samj

I saw that this function existed in the OpenCV library : HoughCircles()

A colleague of mine, told me it could perhaps be available within R as well (https://www.r-project.org/).

In the long past, 10 years ago or so, at work, we had some petri dish where we need to measure the area of the fungi growing on them.
A researcher wrote a script to detect them from my jpeg pictures and It worked extremely well. Unfortunately, he doesn’t work with us anymore

grosgood · May 10, 2023, 11:18am

CHT - Was reading up on it in the wee hours. Alas! @Silvio_Grosso has shot — what, ten million? — botanicals already with five euro pieces; otherwise suggesting using a square target was on my lips, and the present hough would handle squares in a straightforward way.

Remarks on using matchpatch to follow. Not a total failure, but not 100% success either.