com.simiacryptus.mindseye.art.examples.SmoothStyle_1.scala Maven / Gradle / Ivy
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/*
* Copyright (c) 2020 by Andrew Charneski.
*
* The author licenses this file to you under the
* Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance
* with the License. You may obtain a copy
* of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package com.simiacryptus.mindseye.art.examples
import java.net.URI
import java.util.zip.ZipFile
import com.simiacryptus.mindseye.art.models.VGG19
import com.simiacryptus.mindseye.art.ops._
import com.simiacryptus.mindseye.art.photo._
import com.simiacryptus.mindseye.art.photo.cuda.SmoothSolver_Cuda
import com.simiacryptus.mindseye.art.util.ArtSetup.{ec2client, s3client}
import com.simiacryptus.mindseye.art.util.{BasicOptimizer, _}
import com.simiacryptus.mindseye.lang.Tensor
import com.simiacryptus.notebook.NotebookOutput
import com.simiacryptus.ref.wrappers.RefAtomicReference
import com.simiacryptus.sparkbook.NotebookRunner
import com.simiacryptus.sparkbook.NotebookRunner._
import com.simiacryptus.sparkbook.util.Java8Util._
import com.simiacryptus.sparkbook.util.LocalRunner
import com.simiacryptus.util.Util
object SmoothStyle_1 extends SmoothStyle_1 with LocalRunner[Object] with NotebookRunner[Object]
class SmoothStyle_1 extends ArtSetup[Object] {
val styleUrl = "upload:Style"
val s3bucket: String = ""
val initUrl = "50 + noise * 0.5"
override def indexStr = "306"
override def description =
Paints an image in the style of another using:
- PhotoSmooth-based content initialization
- Standard VGG19 layers
- Operators to match content and constrain and enhance style
- Progressive resolution increase
.toString.trim
override def inputTimeoutSeconds = 3600
override def postConfigure(log: NotebookOutput) = log.eval { () =>
() => {
implicit val l = log
// First, basic configuration so we publish to our s3 site
if (Option(s3bucket).filter(!_.isEmpty).isDefined)
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
log.p(log.jpg(ImageArtUtil.loadImage(log, styleUrl, 1200), "Input Style"))
val canvas = new RefAtomicReference[Tensor](null)
// Execute the main process while registered with the site index
val registration = registerWithIndexJPG(() => canvas.get()).toList
try {
withMonitoredJpg(() => canvas.get().toImage) {
paint(styleUrl, contentDims => {
val wctRes = 400
val height = wctRes * (contentDims.getDimensions()(1).toDouble / contentDims.getDimensions()(0))
val content = Tensor.fromRGB(ImageArtUtil.loadImage(log, initUrl, wctRes, height.ceil.toInt))
val fastPhotoStyleTransfer = FastPhotoStyleTransfer.fromZip(new ZipFile(Util.cacheFile(new URI(
"https://simiacryptus.s3-us-west-2.amazonaws.com/photo_wct.zip"))))
val style = Tensor.fromRGB(ImageArtUtil.loadImage(log, styleUrl, wctRes))
fastPhotoStyleTransfer.photoWCT(style, content)
}, canvas, new VisualStyleNetwork(
styleLayers = List(
VGG19.VGG19_1a,
VGG19.VGG19_1b1,
VGG19.VGG19_1b2,
VGG19.VGG19_1c1,
VGG19.VGG19_1c2,
VGG19.VGG19_1c3,
VGG19.VGG19_1c4,
VGG19.VGG19_1d1,
VGG19.VGG19_1d2,
VGG19.VGG19_1d3,
VGG19.VGG19_1d4,
VGG19.VGG19_1e1,
VGG19.VGG19_1e2,
VGG19.VGG19_1e3,
VGG19.VGG19_1e4
).flatMap(x => List(
x, x.prependAvgPool(2)
)),
styleModifiers = List(
new GramMatrixEnhancer().setMinMax(-10, 10).scale(1e0),
new MomentMatcher()
),
styleUrl = List(styleUrl),
magnification = Array(16.0)
),
new BasicOptimizer {
override val trainingMinutes: Int = 60
override val trainingIterations: Int = 20
override val maxRate = 1e8
}, new GeometricSequence {
override val min: Double = 400
override val max: Double = 600
override val steps = 2
}.toStream.map(_.ceil))
paint(styleUrl, x => x, canvas, new VisualStyleNetwork(
styleLayers = List(
VGG19.VGG19_1a,
VGG19.VGG19_1b1,
VGG19.VGG19_1b2,
VGG19.VGG19_1c1,
VGG19.VGG19_1c2,
VGG19.VGG19_1c3,
VGG19.VGG19_1c4,
VGG19.VGG19_1d1,
VGG19.VGG19_1d2,
VGG19.VGG19_1d3,
VGG19.VGG19_1d4
),
styleModifiers = List(
new GramMatrixEnhancer().setMinMax(-10, 10).scale(1e0),
new MomentMatcher()
),
styleUrl = List(styleUrl),
magnification = Array(4.0)
), new BasicOptimizer {
override val trainingMinutes: Int = 90
override val trainingIterations: Int = 20
override val maxRate = 1e9
}, new GeometricSequence {
override val min: Double = 1000
override val max: Double = 1000
override val steps = 1
}.toStream.map(_.round.toDouble))
paint(styleUrl, x => x, canvas, new VisualStyleNetwork(
styleLayers = List(
VGG19.VGG19_1a,
VGG19.VGG19_1b1,
VGG19.VGG19_1b2,
VGG19.VGG19_1c1,
VGG19.VGG19_1c2,
VGG19.VGG19_1c3,
VGG19.VGG19_1c4
),
styleModifiers = List(
//new ChannelMeanMatcher(),
new GramMatrixMatcher()
),
styleUrl = List(styleUrl),
magnification = Array(1.0),
maxWidth = 6000,
maxPixels = 1e9,
tileSize = 800
), new BasicOptimizer {
override val trainingMinutes: Int = 90
override val trainingIterations: Int = 10
override val maxRate = 1e9
}, new GeometricSequence {
override val min: Double = 1800
override val max: Double = 3000
override val steps = 2
}.toStream.map(_.round.toDouble))
}
null
} finally {
registration.foreach(_.stop()(s3client, ec2client))
}
}
}()
def solver: SmoothSolver = new SmoothSolver_Cuda()
}
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