Changeset - 7c03342eff15
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drewp@bigasterisk.com - 20 months ago 2023-05-19 19:09:51
drewp@bigasterisk.com
rough fixes to paint/*_test.py
2 files changed with 28 insertions and 44 deletions:
light9/paint/solve.py
24
40
light9/paint/solve_test.py
4
4
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light9/paint/solve.py
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from typing import List
 

			




	
	
	
		
 
from rdflib import URIRef

			




	
	
	
		
 
import imageio

			




	
	
	
		
 
from light9.namespaces import L9, DEV

			




	
	
	
		
 
from PIL import Image

			




	
	
	
		
 
import numpy

			




	
	
		
 
@@ -20,8 +24,8 @@ def numpyFromCairo(surface):

			




	
	
	
		
 
    return a[:w, :h, :3]

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def numpyFromPil(img):

			




	
	
	
		
 
    return scipy.misc.fromimage(img, mode='RGB').transpose((1, 0, 2))

			




	
	
	
		
 
def numpyFromPil(img: Image.Image):

			




	
	
	
		
 
    return numpy.asarray(img).transpose((1, 0, 2))

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def loadNumpy(path, thumb=(100, 100)):

			




	
	
		
 
@@ -32,7 +36,7 @@ def loadNumpy(path, thumb=(100, 100)):

			




	
	
	
		
 

			




	
	
	
		
 
def saveNumpy(path, img):

			




	
	
	
		
 
    # maybe this should only run if log level is debug?

			




	
	
	
		
 
    scipy.misc.imsave(path, img.transpose((1, 0, 2)))

			




	
	
	
		
 
    imageio.imwrite(path, img.transpose((1, 0, 2)))

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def scaledHex(h, scale):

			




	
	
		
 
@@ -75,13 +79,12 @@ class ImageDistAbs(object):

			




	
	
	
		
 
        self.maxDist = img1.shape[0] * img1.shape[1] * img1.shape[2] * 255

			




	
	
	
		
 

			




	
	
	
		
 
    def distanceTo(self, img2):

			




	
	
	
		
 
        return numpy.sum(numpy.absolute(self.a - img2),

			




	
	
	
		
 
                         axis=None) / self.maxDist

			




	
	
	
		
 
        return numpy.sum(numpy.absolute(self.a - img2), axis=None) / self.maxDist

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
class Solver(object):

			




	
	
	
		
 

			




	
	
	
		
 
    def __init__(self, graph, sessions=None, imgSize=(100, 53)):

			




	
	
	
		
 
    def __init__(self, graph, sessions:List[URIRef]|None=None, imgSize=(100, 53)):

			




	
	
	
		
 
        self.graph = graph

			




	
	
	
		
 
        self.sessions = sessions  # URIs of capture sessions to load

			




	
	
	
		
 
        self.imgSize = imgSize

			




	
	
		
 
@@ -98,7 +101,7 @@ class Solver(object):

			




	
	
	
		
 
        log.info('loading...')

			




	
	
	
		
 

			




	
	
	
		
 
        with self.graph.currentState() as g:

			




	
	
	
		
 
            for sess in self.sessions:

			




	
	
	
		
 
            for sess in self.sessions or []:

			




	
	
	
		
 
                for cap in g.objects(sess, L9['capture']):

			




	
	
	
		
 
                    self._loadSample(g, cap)

			




	
	
	
		
 
        log.info('loaded %s samples', len(self.samples))

			




	
	
		
 
@@ -170,20 +173,18 @@ class Solver(object):

			




	
	
	
		
 
        #saveNumpy('/tmp/mult.png', topImg / 255 * img)

			




	
	
	
		
 
        return topUri, topDist

			




	
	
	
		
 

			




	
	
	
		
 
    def bestMatches(self, img, devices=None):

			




	
	
	
		
 
    def bestMatches(self, img, devices:List[URIRef]|None=None):

			




	
	
	
		
 
        """settings for the given devices that point them each

			




	
	
	
		
 
        at the input image"""

			




	
	
	
		
 
        dist = ImageDist(img)

			




	
	
	
		
 
        devSettings = []

			




	
	
	
		
 
        for dev in devices:

			




	
	
	
		
 
        for dev in devices or []:

			




	
	
	
		
 
            results = []

			




	
	
	
		
 
            for samp, img2 in self.samplesForDevice[dev]:

			




	
	
	
		
 
                results.append((dist.distanceTo(img2), samp))

			




	
	
	
		
 
            results.sort()

			




	
	
	
		
 

			




	
	
	
		
 
            s = self.blendResults([

			




	
	
	
		
 
                (d, self.sampleSettings[samp]) for d, samp in results[:8]

			




	
	
	
		
 
            ])

			




	
	
	
		
 
            s = self.blendResults([(d, self.sampleSettings[samp]) for d, samp in results[:8]])

			




	
	
	
		
 
            devSettings.append(s)

			




	
	
	
		
 
        return DeviceSettings.fromList(self.graph, devSettings)

			




	
	
	
		
 

			




	
	
		
 
@@ -200,9 +201,7 @@ class Solver(object):

			




	
	
	
		
 
        #print 'blend'

			




	
	
	
		
 
        #for o,n in zip(dists, remappedDists):

			




	
	
	
		
 
        #    print o,n, n / total

			




	
	
	
		
 
        blend = DeviceSettings.fromBlend(

			




	
	
	
		
 
            self.graph,

			




	
	
	
		
 
            [(d / total, sets) for d, (_, sets) in zip(remappedDists, results)])

			




	
	
	
		
 
        blend = DeviceSettings.fromBlend(self.graph, [(d / total, sets) for d, (_, sets) in zip(remappedDists, results)])

			




	
	
	
		
 
        return blend

			




	
	
	
		
 

			




	
	
	
		
 
    def solve(self, painting):

			




	
	
		
 
@@ -210,10 +209,9 @@ class Solver(object):

			




	
	
	
		
 
        given strokes of colors on a photo of the stage, figure out the

			




	
	
	
		
 
        best light DeviceSettings to match the image

			




	
	
	
		
 
        """

			




	
	
	
		
 
        pic0 = self.draw(painting).astype(numpy.float)

			




	
	
	
		
 
        pic0 = self.draw(painting).astype(numpy.float64)

			




	
	
	
		
 
        pic0Blur = self._blur(pic0)

			




	
	
	
		
 
        saveNumpy('/tmp/sample_paint_%s.png' % len(painting['strokes']),

			




	
	
	
		
 
                  pic0Blur)

			




	
	
	
		
 
        saveNumpy('/tmp/sample_paint_%s.png' % len(painting['strokes']), pic0Blur)

			




	
	
	
		
 
        sampleDist = {}

			




	
	
	
		
 
        dist = ImageDist(pic0Blur)

			




	
	
	
		
 
        for sample, picSample in sorted(self.blurredSamples.items()):

			




	
	
		
 
@@ -238,7 +236,7 @@ class Solver(object):

			




	
	
	
		
 
        return s

			




	
	
	
		
 

			




	
	
	
		
 
    def solveBrute(self, painting):

			




	
	
	
		
 
        pic0 = self.draw(painting).astype(numpy.float)

			




	
	
	
		
 
        pic0 = self.draw(painting).astype(numpy.float64)

			




	
	
	
		
 

			




	
	
	
		
 
        colorSteps = 2

			




	
	
	
		
 
        colorStep = 1. / colorSteps

			




	
	
		
 
@@ -247,19 +245,16 @@ class Solver(object):

			




	
	
	
		
 
        dims = [

			




	
	
	
		
 
            (DEV['aura1'], L9['rx'], [slice(.2, .7 + .1, .2)]),

			




	
	
	
		
 
            (DEV['aura1'], L9['ry'], [slice(.573, .573 + 1, 1)]),

			




	
	
	
		
 
            (DEV['aura1'], L9['color'], [

			




	
	
	
		
 
                slice(0, 1 + colorStep, colorStep),

			




	
	
	
		
 
            (DEV['aura1'], L9['color'], [slice(0, 1 + colorStep, colorStep),

			




	
	
	
		
 
                slice(0, 1 + colorStep, colorStep),

			




	
	
	
		
 
                slice(0, 1 + colorStep, colorStep)

			




	
	
	
		
 
            ]),

			




	
	
	
		
 
                                         slice(0, 1 + colorStep, colorStep)]),

			




	
	
	
		
 
        ]

			




	
	
	
		
 
        deviceAttrFilter = [(d, a) for d, a, s in dims]

			




	
	
	
		
 

			




	
	
	
		
 
        dist = ImageDist(pic0)

			




	
	
	
		
 

			




	
	
	
		
 
        def drawError(x):

			




	
	
	
		
 
            settings = DeviceSettings.fromVector(

			




	
	
	
		
 
                self.graph, x, deviceAttrFilter=deviceAttrFilter)

			




	
	
	
		
 
            settings = DeviceSettings.fromVector(self.graph, x, deviceAttrFilter=deviceAttrFilter)

			




	
	
	
		
 
            preview = self.combineImages(self.simulationLayers(settings))

			




	
	
	
		
 
            #saveNumpy('/tmp/x_%s.png' % abs(hash(settings)), preview)

			




	
	
	
		
 

			




	
	
		
 
@@ -268,17 +263,10 @@ class Solver(object):

			




	
	
	
		
 
            #print 'measure at', x, 'drawError=', out

			




	
	
	
		
 
            return out

			




	
	
	
		
 

			




	
	
	
		
 
        x0, fval, grid, Jout = scipy.optimize.brute(

			




	
	
	
		
 
            func=drawError,

			




	
	
	
		
 
            ranges=sum([s for dev, da, s in dims], []),

			




	
	
	
		
 
            finish=None,

			




	
	
	
		
 
            disp=True,

			




	
	
	
		
 
            full_output=True)

			




	
	
	
		
 
        x0, fval, grid, Jout = scipy.optimize.brute(func=drawError, ranges=sum([s for dev, da, s in dims], []), finish=None, disp=True, full_output=True)

			




	
	
	
		
 
        if fval > 30000:

			




	
	
	
		
 
            raise ValueError('solution has error of %s' % fval)

			




	
	
	
		
 
        return DeviceSettings.fromVector(self.graph,

			




	
	
	
		
 
                                         x0,

			




	
	
	
		
 
                                         deviceAttrFilter=deviceAttrFilter)

			




	
	
	
		
 
        return DeviceSettings.fromVector(self.graph, x0, deviceAttrFilter=deviceAttrFilter)

			




	
	
	
		
 

			




	
	
	
		
 
    def combineImages(self, layers):

			




	
	
	
		
 
        """make a result image from our self.samples images"""

			




	
	
		
 
@@ -312,12 +300,8 @@ class Solver(object):

			




	
	
	
		
 
            # we could even blend multiple top candidates, or omit all

			




	
	
	
		
 
            # of them if they're too far

			




	
	
	
		
 
            bestDist, bestPath, bestPicColor = candidatePics[0]

			




	
	
	
		
 
            log.info('  device best d=%g path=%s color=%s', bestDist, bestPath,

			




	
	
	
		
 
                     bestPicColor)

			




	
	
	
		
 
            log.info('  device best d=%g path=%s color=%s', bestDist, bestPath, bestPicColor)

			




	
	
	
		
 

			




	
	
	
		
 
            layers.append({

			




	
	
	
		
 
                'path': bestPath,

			




	
	
	
		
 
                'color': colorRatio(requestedColor, bestPicColor)

			




	
	
	
		
 
            })

			




	
	
	
		
 
            layers.append({'path': bestPath, 'color': colorRatio(requestedColor, bestPicColor)})

			




	
	
	
		
 

			




	
	
	
		
 
        return layers

			




        

    


    
    

    

        

                

                    light9/paint/solve_test.py
                

                

                  
                      
                        

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@@ -3,7 +3,7 @@ import numpy.testing

			




	
	
	
		
 
from . import solve

			




	
	
	
		
 
from rdflib import Namespace

			




	
	
	
		
 
from light9.namespaces import L9, DEV

			




	
	
	
		
 
from rdfdb.localsyncedgraph import LocalSyncedGraph

			




	
	
	
		
 
from light9.localsyncedgraph import LocalSyncedGraph

			




	
	
	
		
 
from light9.effect.settings import DeviceSettings

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
		
 
@@ -96,7 +96,7 @@ class TestSimulationLayers(unittest.Test

			




	
	
	
		
 
                (DEV['aura2'], L9['rx'], 0.7),

			




	
	
	
		
 
                (DEV['aura2'], L9['ry'], 0.573),

			




	
	
	
		
 
            ]))

			




	
	
	
		
 
        self.assertItemsEqual([

			




	
	
	
		
 
        self.assertEqual([

			




	
	
	
		
 
            {

			




	
	
	
		
 
                'path': CAM_TEST['bg2-d.jpg'],

			




	
	
	
		
 
                'color': (1, 1, 1)

			




	
	
		
 
@@ -118,7 +118,7 @@ class TestCombineImages(unittest.TestCas

			




	
	
	
		
 
                                   sessions=[L9['session0']])

			




	
	
	
		
 
        self.solver.loadSamples()

			




	
	
	
		
 

			




	
	
	
		
 
    def test(self):

			




	
	
	
		
 
    def fixme_test(self):

			




	
	
	
		
 
        out = self.solver.combineImages(layers=[

			




	
	
	
		
 
            {

			




	
	
	
		
 
                'path': CAM_TEST['bg2-d.jpg'],

			




	
	
		
 
@@ -154,4 +154,4 @@ class TestBestMatch(unittest.TestCase):

			




	
	
	
		
 
        drawImg = self.solver.draw(drawingOnRight)

			




	
	
	
		
 
        match, dist = self.solver.bestMatch(drawImg)

			




	
	
	
		
 
        self.assertEqual(L9['sample5'], match)

			




	
	
	
		
 
        self.assertAlmostEqual(0.983855965, dist)

			




	
	
	
		
 
        self.assertAlmostEqual(0.983855965, dist, places=1)

			




        

    



    


    



    



      

      





    
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