1. SmoothStyle
  2. Resolution 800.0
  3. Resolution 1400.0
  4. Resolution 2000.0
  5. Resolution 3000.0

SmoothStyle

Paints an image in the style of another using:
  1. PhotoSmooth-based content initialization
  2. Standard VGG16 layers
  3. Operators to match content and constrain and enhance style
  4. Progressive resolution increase

Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase

SmoothStyle.scala:65 executed in 0.00 seconds (0.000 gc):

    () => {
      implicit val implicitLog = log
      // First, basic configuration so we publish to our s3 site
      log.setArchiveHome(URI.create(s"s3://$s3bucket/$className/${log.getId}/"))
      log.onComplete(() => upload(log): Unit)
      // Fetch input images (user upload prompts) and display a rescaled copies
      ImageArtUtil.loadImages(log, styleUrl, 600).foreach(img => log.p(log.jpg(img, "Input Style")))
      log.p(log.jpg(ImageArtUtil.loadImage(log, contentUrl, 600), "Input Content"))
      val canvas = new RefAtomicReference[Tensor](null)
      // Execute the main process while registered with the site index
      val registration = registerWithIndexJPG(() => canvas.get())
      try {
        withMonitoredJpg(() => {
          val tensor = canvas.get()
          if (tensor == null) null
          else tensor.toImage
        }) {
          paint(
            contentUrl = contentUrl,
            initFn = content => {
              val fastPhotoStyleTransfer = FastPhotoStyleTransfer.fromZip(new ZipFile(Util.cacheFile(new URI(
                "https://simiacryptus.s3-us-west-2.amazonaws.com/photo_wct.zip"))))
              val style = ImageArtUtil.loadImages(log, styleUrl, 500).map(Tensor.fromRGB(_)).head
              val wctRestyled = fastPhotoStyleTransfer.photoWCT(style, content.addRef())
              fastPhotoStyleTransfer.freeRef()
              val topology = new SearchRadiusTopology(content.addRef())
              topology.setSelfRef(true)
              topology.setVerbose(true)
              var affinity = new RelativeAffinity(content, topology)
              affinity.setContrast(20)
              affinity.setGraphPower1(2)
              affinity.setMixing(0.1)
              //val wrapper = affinity.wrap((graphEdges, innerResult) => adjust(graphEdges, innerResult, degree(innerResult), 0.2))
              val operator = solver.solve(topology, affinity, 1e-4)
              val tensor = operator.apply(wctRestyled)
              operator.freeRef()
              tensor
            },
            canvas = canvas.addRef(),
            network = new VisualStyleContentNetwork(
              styleLayers = List(
                VGG16.VGG16_1a,
                VGG16.VGG16_1b1,
                VGG16.VGG16_1b2,
                VGG16.VGG16_1c1,
                VGG16.VGG16_1c2,
                VGG16.VGG16_1c3,
                VGG16.VGG16_1d1,
                VGG16.VGG16_1d2,
                VGG16.VGG16_1d3,
                VGG16.VGG16_1e1,
                VGG16.VGG16_1e2,
                VGG16.VGG16_1e3
              ).flatMap(x => List(
                x, x.prependAvgPool(2)
              )),
              styleModifiers = List(
                //new GramMatrixEnhancer().setMinMax(-0.5, 0.5),
                new MomentMatcher()
              ),
              styleUrls = Option(styleUrl),
              contentLayers = List(
                VGG16.VGG16_1c1,
                VGG16.VGG16_1c3
              ),
              contentModifiers = List(
                new ContentMatcher().scale(1e1)
              ),
              magnification = 1
            ),
            optimizer = new BasicOptimizer {
              override val trainingMinutes: Int = 90
              override val trainingIterations: Int = 20
              override val maxRate = 1e9
            }, resolutions = new GeometricSequence {
              override val min: Double = 800
              override val max: Double = 1400
              override val steps = 2
            }.toStream.map(_.round.toDouble))
          paint(
            contentUrl = contentUrl,
            initFn = x => x,
            canvas = canvas.addRef(),
            network = new VisualStyleContentNetwork(
              styleLayers = List(
                VGG16.VGG16_1a,
                VGG16.VGG16_1b1,
                VGG16.VGG16_1b2,
                VGG16.VGG16_1c1,
                VGG16.VGG16_1c2,
                VGG16.VGG16_1c3
              ),
              styleModifiers = List(
                //new GramMatrixEnhancer().setMinMax(-0.5, 0.5),
                new GramMatrixMatcher()
              ),
              styleUrls = Option(styleUrl),
              contentLayers = List(
                VGG16.VGG16_1b2,
                VGG16.VGG16_1b2
              ).map(_.prependAvgPool(2).appendMaxPool(2)),
              contentModifiers = List(
                new ContentMatcher().scale(5e-1)
              ),
              magnification = 1
            ),
            optimizer = new BasicOptimizer {
              override val trainingMinutes: Int = 180
              override val trainingIterations: Int = 10
              override val maxRate = 1e9
            },
            resolutions = new GeometricSequence {
              override val min: Double = 2000
              override val max: Double = 3000
              override val steps = 2
            }.toStream.map(_.round.toDouble))
        }
        null
      } finally {
        canvas.freeRef()
        registration.foreach(_.stop()(s3client, ec2client))
      }
    }

Returns

    { }

Input Style

Input Style

Input Content

Resolution 800.0

Subreport: Optimization

Resolution 1400.0

Subreport: Optimization

Resolution 2000.0

Subreport: Optimization

Resolution 3000.0

Subreport: Optimization