Coords/edge detect 2 colour image

cvp

@mikael long since we haven't seen you here, welcome back

mikael

@rb, if we are talking something like a photo with rectangles, you could also use the iOS Vision framework, see here.

I have a Python implementation lying around somewhere, let me know if that seems interesting.

mikael

@cvp, thanks! Have been hacking more on the laptop lately.

rb

Hiya
So I don’t have an image it’s just in my head but initially yes I’m thinking rectangles black on white or white on black.They could be arbitrary sizes I’m thinking - I just want use them to create edges that I can repurpose as coordinates for building other elements with.

rb

Vision iOS framework looks perfect actually so yes please would be interested in how to implement such a thing in Pythonista for sure.

rb

I found another post regarding text recognition and iOS vision and recognise rectangle is mentioned there so cut out the text aspect and adapted it: (thanks jonb)

But I can’t get what I need from this - I have tried altering the VNDetectRectanglesRequest properties.
Basic issue is even though it’s a very simple image = seems to struggle identifying accurately the edges.

from objc_util import *
import ui


ui_image=ui.Image.named('test:Gray21')
ui_image.show()

load_framework('Vision')
VNDetectRectanglesRequest = ObjCClass('VNDetectRectanglesRequest')
VNImageRequestHandler = ObjCClass('VNImageRequestHandler')

handler = VNImageRequestHandler.alloc().initWithData_options_(ui_image.to_png(), None).autorelease()

req = VNDetectRectanglesRequest.alloc().init().autorelease()

req.maximumObservations=0
req.minimumSize=0.01
req.minimumAspectRatio=0.0
req.maximumAspectRatio=1.0
req.quadratureTolerance=10

success = handler.performRequests_error_([req], None)
with ui.ImageContext(*tuple(ui_image.size) ) as ctx:
   ui_image.draw()
   for result in req.results():
      cgpts=[result.bottomLeft(),
                                        result.topLeft(),
                                        result.topRight(),
                                        result.bottomRight(),
                                        result.bottomLeft()] 
      verts = [(p.x*ui_image.size.w, (1-p.y)*ui_image.size.h) for p in cgpts]
      pth = ui.Path()
      pth.move_to(*verts[0]) 
      for p in verts[1:]:
         pth.line_to(*p)  
      ui.set_color('red')
      pth.stroke()
      x,y = verts[0]
      w,h =(verts[2][0]-x), (verts[2][1]-y)
     
   marked_img = ctx.get_image()
   marked_img.show()

cvp

@rb not so bad with

rb

Hmm ok so your saying 2 colour works better - I only used that test image as I couldn’t work out how to upload an image here…
this is more like the kind of images I want to use though, ie long thin horizontal rectangles mostly - seems to struggle, try :

iow:drag_256

It creates extra rectangles at top and bottom bounds- how can I remove these?

cvp

@rb try with this, it works

with ui.ImageContext(400,300) as ctx:
	pth = ui.Path.rect(0,0,400,300)
	ui.set_color('black')
	pth.fill()
	pthr = ui.Path.rect(100,100,200,50)
	ui.set_color('white')
	pthr.fill()
	ui_image = ctx.get_image() 


#ui_image=ui.Image.named('iow:drag_256')

cvp

@rb said:

I couldn’t work out how to upload an image here…

I use

import pyimgur,photos,clipboard,os,console
i=photos.pick_image()
if i:
	print(i.format)
	format = 'gif' if (i.format == 'GIF') else 'jpg'
	i.save('img.'+format)
	clipboard.set(pyimgur.Imgur("303d632d723a549").upload_image('img.'+format, title="Uploaded-Image").link)
	console.hud_alert("link copied!")
	os.remove('img.'+format)

With pyImgur from here

JonB

Fwiw
https://forum.omz-software.com/topic/6016/recognize-text-from-picture/43?page=3

Had a rectangle recognizer.

You might play with the quadratureTolerance -- you are only allowing rectangles with angles within 10 degrees -- you might increase that to the default of 30 to allow perspective.

Try adjusting minimumConfidence -- lower will allow more detections, at lower quality.

rb

Cheers everyone, Jon that’s where I nabbed that snippet from in first place! The issue is the proximity to the edge of the image I think, mine were very close to the edge so I tried a bigger black border and I did try messing with the numbers a bit on properties.Seems to work better but still not perfect.