[orx-runway] Comment out demos that do not compile
This commit is contained in:
Edwin Jakobs
@@ -1,46 +1,46 @@
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import org.openrndr.application
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import org.openrndr.color.ColorRGBa
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import org.openrndr.draw.ColorBuffer
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import org.openrndr.draw.isolatedWithTarget
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import org.openrndr.draw.loadFont
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import org.openrndr.draw.renderTarget
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import org.openrndr.extra.runway.*
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import org.openrndr.math.smoothstep
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/**
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* This demonstrates an image reinterpretation effect.
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* This example requires a `runway/BigBiGAN` model to be active in Runway.
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*/
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fun main() = application {
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configure {
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width = 512
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height = 256
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}
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program {
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val rt = renderTarget(256, 256) {
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colorBuffer()
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}
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val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 256.0)
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val alphabet = "ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
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extend {
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drawer.isolatedWithTarget(rt) {
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drawer.clear(ColorRGBa.BLACK)
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drawer.ortho(rt)
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val it = seconds.toInt()
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val t = seconds - it
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drawer.fill = ColorRGBa.PINK.shade(smoothstep(0.0, 0.2, t) * smoothstep(1.0, 0.8, t))
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drawer.fontMap = font
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drawer.text("" + alphabet[seconds.toInt()], 64.0, 128.0 + 64)
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}
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val result: BigBiGANResult =
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runwayQuery("http://localhost:8000/query", BigBiGANQuery(rt.colorBuffer(0).toData()))
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val image = ColorBuffer.fromData(result.outputImage)
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drawer.image(rt.colorBuffer(0))
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drawer.image(image, 256.0, 0.0)
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image.destroy()
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}
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}
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}
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//import org.openrndr.application
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//import org.openrndr.color.ColorRGBa
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//import org.openrndr.draw.ColorBuffer
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//import org.openrndr.draw.isolatedWithTarget
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//import org.openrndr.draw.loadFont
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//import org.openrndr.draw.renderTarget
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//import org.openrndr.extra.runway.*
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//import org.openrndr.math.smoothstep
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//
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///**
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// * This demonstrates an image reinterpretation effect.
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// * This example requires a `runway/BigBiGAN` model to be active in Runway.
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// */
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//
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//fun main() = application {
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// configure {
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// width = 512
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// height = 256
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// }
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//
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// program {
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// val rt = renderTarget(256, 256) {
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// colorBuffer()
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// }
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// val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 256.0)
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// val alphabet = "ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
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// extend {
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// drawer.isolatedWithTarget(rt) {
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// drawer.clear(ColorRGBa.BLACK)
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// drawer.ortho(rt)
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// val it = seconds.toInt()
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// val t = seconds - it
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// drawer.fill = ColorRGBa.PINK.shade(smoothstep(0.0, 0.2, t) * smoothstep(1.0, 0.8, t))
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// drawer.fontMap = font
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// drawer.text("" + alphabet[seconds.toInt()], 64.0, 128.0 + 64)
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// }
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// val result: BigBiGANResult =
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// runwayQuery("http://localhost:8000/query", BigBiGANQuery(rt.colorBuffer(0).toData()))
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//
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// val image = ColorBuffer.fromData(result.outputImage)
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// drawer.image(rt.colorBuffer(0))
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// drawer.image(image, 256.0, 0.0)
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// image.destroy()
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// }
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// }
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//}
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@@ -1,49 +1,49 @@
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import org.openrndr.application
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import org.openrndr.color.ColorRGBa
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import org.openrndr.draw.*
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import org.openrndr.extra.runway.*
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/**
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* This demonstrates an image feedback effect. It starts from a single image.
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* The BigBiGAN generates a new image from the input, this program feeds the
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* generated image back into the model (with an additional distortion).
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* This example requires a `runway/BigBiGAN` model to be active in Runway.
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*/
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fun main() = application {
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configure {
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width = 512
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height = 512
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}
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program {
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val rt = renderTarget(256, 256) {
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colorBuffer()
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}
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val startImage = loadImage("demo-data/images/portrait.jpg")
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drawer.isolatedWithTarget(rt) {
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drawer.ortho(rt)
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drawer.clear(ColorRGBa.BLACK)
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drawer.image(startImage, (rt.width - startImage.width) / 2.0, (rt.height - startImage.height) / 2.0)
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}
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extend {
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val result: BigBiGANResult =
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runwayQuery("http://localhost:8000/query", BigBiGANQuery(rt.colorBuffer(0).toData()))
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val image = ColorBuffer.fromData(result.outputImage)
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drawer.image(image, 0.0, 0.0, 512.0, 512.0)
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drawer.isolatedWithTarget(rt) {
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drawer.ortho(rt)
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drawer.translate(image.width / 2.0, image.height / 2.0)
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drawer.rotate(10.0)
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drawer.translate(-image.width / 2.0, -image.height / 2.0)
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drawer.drawStyle.colorMatrix = tint(ColorRGBa.WHITE.opacify(0.5))
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drawer.image(image)
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}
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image.destroy()
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}
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}
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}
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//import org.openrndr.application
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//import org.openrndr.color.ColorRGBa
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//import org.openrndr.draw.*
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//import org.openrndr.extra.runway.*
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//
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///**
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// * This demonstrates an image feedback effect. It starts from a single image.
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// * The BigBiGAN generates a new image from the input, this program feeds the
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// * generated image back into the model (with an additional distortion).
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// * This example requires a `runway/BigBiGAN` model to be active in Runway.
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// */
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//fun main() = application {
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// configure {
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// width = 512
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// height = 512
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// }
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//
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// program {
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// val rt = renderTarget(256, 256) {
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// colorBuffer()
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// }
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// val startImage = loadImage("demo-data/images/portrait.jpg")
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//
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// drawer.isolatedWithTarget(rt) {
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// drawer.ortho(rt)
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// drawer.clear(ColorRGBa.BLACK)
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// drawer.image(startImage, (rt.width - startImage.width) / 2.0, (rt.height - startImage.height) / 2.0)
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// }
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//
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// extend {
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// val result: BigBiGANResult =
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// runwayQuery("http://localhost:8000/query", BigBiGANQuery(rt.colorBuffer(0).toData()))
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//
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// val image = ColorBuffer.fromData(result.outputImage)
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// drawer.image(image, 0.0, 0.0, 512.0, 512.0)
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//
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// drawer.isolatedWithTarget(rt) {
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// drawer.ortho(rt)
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// drawer.translate(image.width / 2.0, image.height / 2.0)
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// drawer.rotate(10.0)
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// drawer.translate(-image.width / 2.0, -image.height / 2.0)
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// drawer.drawStyle.colorMatrix = tint(ColorRGBa.WHITE.opacify(0.5))
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// drawer.image(image)
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// }
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// image.destroy()
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// }
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// }
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//}
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//
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@@ -1,36 +1,36 @@
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import org.openrndr.application
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import org.openrndr.color.ColorRGBa
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import org.openrndr.draw.ColorBuffer
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import org.openrndr.draw.loadFont
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import org.openrndr.extra.runway.AttnGANRequest
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import org.openrndr.extra.runway.AttnGANResult
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import org.openrndr.extra.runway.runwayQuery
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import java.io.File
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/**
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* This demonstrates a text to image network. It generates images from single words.
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* This example requires a `runway/AttnGAN` model to be active in Runway.
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*/
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fun main() = application {
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configure {
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width = 768
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height = 576
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}
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program {
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val runwayHost = "http://localhost:8000/query"
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val words = File("demo-data/words/words.txt").readText().split("\n")
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val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 72.0)
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extend {
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val text = words.random()
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val result: AttnGANResult = runwayQuery(runwayHost, AttnGANRequest(text))
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val image = ColorBuffer.fromUrl(result.result)
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drawer.fontMap = font
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drawer.image(image, (width - image.width) / 2.0, (height - image.height) / 2.0)
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drawer.fill = ColorRGBa.PINK
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drawer.text(text, 40.0, height / 2.0)
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image.destroy()
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}
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}
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}
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//import org.openrndr.application
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//import org.openrndr.color.ColorRGBa
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//import org.openrndr.draw.ColorBuffer
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//import org.openrndr.draw.loadFont
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//import org.openrndr.extra.runway.AttnGANRequest
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//import org.openrndr.extra.runway.AttnGANResult
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//import org.openrndr.extra.runway.runwayQuery
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//import java.io.File
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//
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///**
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// * This demonstrates a text to image network. It generates images from single words.
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// * This example requires a `runway/AttnGAN` model to be active in Runway.
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// */
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//
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//fun main() = application {
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// configure {
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// width = 768
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// height = 576
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// }
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//
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// program {
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// val runwayHost = "http://localhost:8000/query"
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// val words = File("demo-data/words/words.txt").readText().split("\n")
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// val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 72.0)
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// extend {
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// val text = words.random()
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// val result: AttnGANResult = runwayQuery(runwayHost, AttnGANRequest(text))
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// val image = ColorBuffer.fromUrl(result.result)
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// drawer.fontMap = font
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// drawer.image(image, (width - image.width) / 2.0, (height - image.height) / 2.0)
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// drawer.fill = ColorRGBa.PINK
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// drawer.text(text, 40.0, height / 2.0)
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// image.destroy()
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// }
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// }
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//}
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@@ -1,39 +1,39 @@
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import org.openrndr.application
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import org.openrndr.color.ColorRGBa
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import org.openrndr.draw.ColorBuffer
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import org.openrndr.draw.loadFont
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import org.openrndr.extra.runway.AttnGANRequest
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import org.openrndr.extra.runway.AttnGANResult
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import org.openrndr.extra.runway.runwayQuery
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import java.io.File
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/**
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* This demonstrates a text to image network. It generates images from simple sentences.
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* This example requires a `runway/AttnGAN` model to be active in Runway.
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*/
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fun main() = application {
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configure {
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width = 768
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height = 576
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}
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program {
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val runwayHost = "http://localhost:8000/query"
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val nouns = File("demo-data/words/nouns.txt").readText().split("\n")
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val prepositions = File("demo-data/words/prepositions.txt").readText().split("\n")
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val adjectives = File("demo-data/words/adjectives.txt").readText().split("\n")
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val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 36.0)
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extend {
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val text = "a ${adjectives.random()} ${nouns.random()} ${prepositions.random()} a ${adjectives.random()} ${nouns.random()}"
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val result: AttnGANResult = runwayQuery(runwayHost, AttnGANRequest(text))
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val image = ColorBuffer.fromUrl(result.result)
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drawer.fontMap = font
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drawer.image(image, (width - image.width) / 2.0, (height - image.height) / 2.0)
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drawer.fill = ColorRGBa.PINK
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drawer.text(text, 40.0, height - 40.0)
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image.destroy()
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}
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}
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}
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//import org.openrndr.application
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//import org.openrndr.color.ColorRGBa
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//import org.openrndr.draw.ColorBuffer
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//import org.openrndr.draw.loadFont
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//import org.openrndr.extra.runway.AttnGANRequest
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//import org.openrndr.extra.runway.AttnGANResult
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//import org.openrndr.extra.runway.runwayQuery
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//import java.io.File
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//
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///**
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// * This demonstrates a text to image network. It generates images from simple sentences.
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// * This example requires a `runway/AttnGAN` model to be active in Runway.
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// */
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//
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//fun main() = application {
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// configure {
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// width = 768
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// height = 576
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// }
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//
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// program {
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// val runwayHost = "http://localhost:8000/query"
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// val nouns = File("demo-data/words/nouns.txt").readText().split("\n")
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// val prepositions = File("demo-data/words/prepositions.txt").readText().split("\n")
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// val adjectives = File("demo-data/words/adjectives.txt").readText().split("\n")
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// val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 36.0)
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//
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// extend {
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// val text = "a ${adjectives.random()} ${nouns.random()} ${prepositions.random()} a ${adjectives.random()} ${nouns.random()}"
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// val result: AttnGANResult = runwayQuery(runwayHost, AttnGANRequest(text))
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// val image = ColorBuffer.fromUrl(result.result)
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// drawer.fontMap = font
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// drawer.image(image, (width - image.width) / 2.0, (height - image.height) / 2.0)
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// drawer.fill = ColorRGBa.PINK
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// drawer.text(text, 40.0, height - 40.0)
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// image.destroy()
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// }
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// }
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//}
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@@ -1,40 +1,40 @@
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import org.openrndr.application
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import org.openrndr.color.ColorRGBa
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import org.openrndr.draw.ColorBuffer
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import org.openrndr.draw.isolatedWithTarget
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import org.openrndr.draw.loadImage
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import org.openrndr.draw.renderTarget
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import org.openrndr.extra.runway.*
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/**
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* This demonstrates the body estimation model of DensePose
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* This example requires a `runway/DensePose` model active in Runway.
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*/
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fun main() = application {
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configure {
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width = 512
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height = 512
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}
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program {
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val rt = renderTarget(512, 512) {
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colorBuffer()
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}
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val startImage = loadImage("demo-data/images/peopleCity01.jpg")
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drawer.isolatedWithTarget(rt) {
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drawer.ortho(rt)
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drawer.clear(ColorRGBa.BLACK)
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drawer.image(startImage, (rt.width - startImage.width) / 2.0, (rt.height - startImage.height) / 2.0)
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}
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extend {
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val result: DensePoseResult =
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runwayQuery("http://localhost:8000/query", DensePoseQuery(rt.colorBuffer(0).toData()))
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val image = ColorBuffer.fromData(result.output)
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drawer.image(image, 0.0, 0.0, 512.0, 512.0)
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image.destroy()
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}
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}
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}
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//import org.openrndr.application
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//import org.openrndr.color.ColorRGBa
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//import org.openrndr.draw.ColorBuffer
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//import org.openrndr.draw.isolatedWithTarget
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//import org.openrndr.draw.loadImage
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//import org.openrndr.draw.renderTarget
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//import org.openrndr.extra.runway.*
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//
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///**
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// * This demonstrates the body estimation model of DensePose
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// * This example requires a `runway/DensePose` model active in Runway.
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// */
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//fun main() = application {
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// configure {
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// width = 512
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// height = 512
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// }
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//
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// program {
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// val rt = renderTarget(512, 512) {
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// colorBuffer()
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// }
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// val startImage = loadImage("demo-data/images/peopleCity01.jpg")
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//
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// drawer.isolatedWithTarget(rt) {
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// drawer.ortho(rt)
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// drawer.clear(ColorRGBa.BLACK)
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// drawer.image(startImage, (rt.width - startImage.width) / 2.0, (rt.height - startImage.height) / 2.0)
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// }
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//
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// extend {
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// val result: DensePoseResult =
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// runwayQuery("http://localhost:8000/query", DensePoseQuery(rt.colorBuffer(0).toData()))
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// val image = ColorBuffer.fromData(result.output)
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//
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// drawer.image(image, 0.0, 0.0, 512.0, 512.0)
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// image.destroy()
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// }
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// }
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//}
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@@ -1,41 +1,41 @@
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import org.openrndr.application
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import org.openrndr.draw.ColorBuffer
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import org.openrndr.draw.colorBuffer
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import org.openrndr.extra.fx.transform.FlipVertically
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import org.openrndr.extra.runway.DeOldifyRequest
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import org.openrndr.extra.runway.DeOldifyResponse
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import org.openrndr.extra.runway.runwayQuery
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import org.openrndr.ffmpeg.VideoPlayerFFMPEG
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/**
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* This demonstrates the Deoldify model, which colors grayscale images
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* This example requires a `reiinakano/DeOldify` model active in Runway.
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*/
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|
||||
fun main() = application {
|
||||
configure {
|
||||
width = 1280
|
||||
height = 360
|
||||
}
|
||||
|
||||
program {
|
||||
val image = colorBuffer(640, 360)
|
||||
val camera = VideoPlayerFFMPEG.fromDevice(imageWidth = 640, imageHeight = 360)
|
||||
camera.play()
|
||||
val flip = FlipVertically()
|
||||
|
||||
camera.newFrame.listen {
|
||||
flip.apply(it.frame, image)
|
||||
}
|
||||
|
||||
extend {
|
||||
camera.draw(drawer)
|
||||
val response: DeOldifyResponse =
|
||||
runwayQuery("http://localhost:8000/query", DeOldifyRequest(image.toDataUrl()))
|
||||
|
||||
val image = ColorBuffer.fromUrl(response.image)
|
||||
drawer.image(image, 640.0, 0.0)
|
||||
image.destroy()
|
||||
}
|
||||
}
|
||||
}
|
||||
//import org.openrndr.application
|
||||
//import org.openrndr.draw.ColorBuffer
|
||||
//import org.openrndr.draw.colorBuffer
|
||||
//import org.openrndr.extra.fx.transform.FlipVertically
|
||||
//import org.openrndr.extra.runway.DeOldifyRequest
|
||||
//import org.openrndr.extra.runway.DeOldifyResponse
|
||||
//import org.openrndr.extra.runway.runwayQuery
|
||||
//import org.openrndr.ffmpeg.VideoPlayerFFMPEG
|
||||
//
|
||||
///**
|
||||
// * This demonstrates the Deoldify model, which colors grayscale images
|
||||
// * This example requires a `reiinakano/DeOldify` model active in Runway.
|
||||
// */
|
||||
//
|
||||
//fun main() = application {
|
||||
// configure {
|
||||
// width = 1280
|
||||
// height = 360
|
||||
// }
|
||||
//
|
||||
// program {
|
||||
// val image = colorBuffer(640, 360)
|
||||
// val camera = VideoPlayerFFMPEG.fromDevice(imageWidth = 640, imageHeight = 360)
|
||||
// camera.play()
|
||||
// val flip = FlipVertically()
|
||||
//
|
||||
// camera.newFrame.listen {
|
||||
// flip.apply(it.frame, image)
|
||||
// }
|
||||
//
|
||||
// extend {
|
||||
// camera.draw(drawer)
|
||||
// val response: DeOldifyResponse =
|
||||
// runwayQuery("http://localhost:8000/query", DeOldifyRequest(image.toDataUrl()))
|
||||
//
|
||||
// val image = ColorBuffer.fromUrl(response.image)
|
||||
// drawer.image(image, 640.0, 0.0)
|
||||
// image.destroy()
|
||||
// }
|
||||
// }
|
||||
//}
|
||||
@@ -1,50 +1,50 @@
|
||||
import org.openrndr.application
|
||||
import org.openrndr.draw.ColorBuffer
|
||||
import org.openrndr.draw.colorBuffer
|
||||
import org.openrndr.extra.fx.transform.FlipVertically
|
||||
import org.openrndr.extra.runway.DeOldifyRequest
|
||||
import org.openrndr.extra.runway.DeOldifyResponse
|
||||
import org.openrndr.extra.runway.runwayQuery
|
||||
import org.openrndr.ffmpeg.ScreenRecorder
|
||||
import org.openrndr.ffmpeg.VideoPlayerConfiguration
|
||||
import org.openrndr.ffmpeg.VideoPlayerFFMPEG
|
||||
|
||||
/**
|
||||
* This demonstrates the Deoldify model, which colors grayscale images
|
||||
* This example requires a `reiinakano/DeOldify` model active in Runway.
|
||||
*/
|
||||
|
||||
fun main() = application {
|
||||
configure {
|
||||
width = 1280
|
||||
height = 480
|
||||
}
|
||||
|
||||
program {
|
||||
val image = colorBuffer(640, 480)
|
||||
val vc = VideoPlayerConfiguration().apply {
|
||||
allowFrameSkipping = false
|
||||
}
|
||||
// -- you will have to supply your own video here
|
||||
val video = VideoPlayerFFMPEG.fromFile("data/videos/night_of_the_living_dead_512kb.mp4", configuration = vc)
|
||||
video.play()
|
||||
val flip = FlipVertically()
|
||||
|
||||
video.newFrame.listen {
|
||||
flip.apply(it.frame, image)
|
||||
}
|
||||
extend(ScreenRecorder()) {
|
||||
frameRate = 30
|
||||
}
|
||||
extend {
|
||||
video.draw(drawer, 0.0, 0.0, 640.0, 480.0)
|
||||
val response: DeOldifyResponse =
|
||||
runwayQuery("http://localhost:8000/query", DeOldifyRequest(image.toDataUrl()))
|
||||
|
||||
val image = ColorBuffer.fromUrl(response.image)
|
||||
|
||||
drawer.image(image, 640.0, 0.0)
|
||||
image.destroy()
|
||||
}
|
||||
}
|
||||
}
|
||||
//import org.openrndr.application
|
||||
//import org.openrndr.draw.ColorBuffer
|
||||
//import org.openrndr.draw.colorBuffer
|
||||
//import org.openrndr.extra.fx.transform.FlipVertically
|
||||
//import org.openrndr.extra.runway.DeOldifyRequest
|
||||
//import org.openrndr.extra.runway.DeOldifyResponse
|
||||
//import org.openrndr.extra.runway.runwayQuery
|
||||
//import org.openrndr.ffmpeg.ScreenRecorder
|
||||
//import org.openrndr.ffmpeg.VideoPlayerConfiguration
|
||||
//import org.openrndr.ffmpeg.VideoPlayerFFMPEG
|
||||
//
|
||||
///**
|
||||
// * This demonstrates the Deoldify model, which colors grayscale images
|
||||
// * This example requires a `reiinakano/DeOldify` model active in Runway.
|
||||
// */
|
||||
//
|
||||
//fun main() = application {
|
||||
// configure {
|
||||
// width = 1280
|
||||
// height = 480
|
||||
// }
|
||||
//
|
||||
// program {
|
||||
// val image = colorBuffer(640, 480)
|
||||
// val vc = VideoPlayerConfiguration().apply {
|
||||
// allowFrameSkipping = false
|
||||
// }
|
||||
// // -- you will have to supply your own video here
|
||||
// val video = VideoPlayerFFMPEG.fromFile("data/videos/night_of_the_living_dead_512kb.mp4", configuration = vc)
|
||||
// video.play()
|
||||
// val flip = FlipVertically()
|
||||
//
|
||||
// video.newFrame.listen {
|
||||
// flip.apply(it.frame, image)
|
||||
// }
|
||||
// extend(ScreenRecorder()) {
|
||||
// frameRate = 30
|
||||
// }
|
||||
// extend {
|
||||
// video.draw(drawer, 0.0, 0.0, 640.0, 480.0)
|
||||
// val response: DeOldifyResponse =
|
||||
// runwayQuery("http://localhost:8000/query", DeOldifyRequest(image.toDataUrl()))
|
||||
//
|
||||
// val image = ColorBuffer.fromUrl(response.image)
|
||||
//
|
||||
// drawer.image(image, 640.0, 0.0)
|
||||
// image.destroy()
|
||||
// }
|
||||
// }
|
||||
//}
|
||||
@@ -1,53 +1,53 @@
|
||||
import org.openrndr.application
|
||||
import org.openrndr.color.ColorRGBa
|
||||
import org.openrndr.draw.ColorBuffer
|
||||
import org.openrndr.draw.loadFont
|
||||
import org.openrndr.extra.runway.*
|
||||
import org.openrndr.ffmpeg.ScreenRecorder
|
||||
import java.io.File
|
||||
|
||||
/**
|
||||
* This demonstrates a feedback loop
|
||||
* This example requires:
|
||||
* a `runway/im2txt` model active in Runway on port 8000
|
||||
* a `runway/AttnGAN` model active in Runway on port 8001
|
||||
*/
|
||||
|
||||
fun main() = application {
|
||||
configure {
|
||||
width = 768
|
||||
height = 576
|
||||
}
|
||||
|
||||
program {
|
||||
|
||||
val attnHost = "http://localhost:8001/query"
|
||||
val im2txtHost = "http://localhost:8000/query"
|
||||
|
||||
val nouns = File("demo-data/words/nouns.txt").readText().split("\n")
|
||||
val prepositions = File("demo-data/words/prepositions.txt").readText().split("\n")
|
||||
val adjectives = File("demo-data/words/adjectives.txt").readText().split("\n")
|
||||
|
||||
val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 36.0)
|
||||
|
||||
var text = "a ${adjectives.random()} ${nouns.random()} ${prepositions.random()} a ${adjectives.random()} ${nouns.random()}"
|
||||
|
||||
extend(ScreenRecorder()) {
|
||||
frameRate = 1
|
||||
}
|
||||
|
||||
extend {
|
||||
val result: AttnGANResult = runwayQuery(attnHost, AttnGANRequest(text))
|
||||
val image = ColorBuffer.fromUrl(result.result)
|
||||
drawer.fontMap = font
|
||||
drawer.image(image, (width - image.width)/2.0, (height - image.height)/2.0)
|
||||
|
||||
val result2:Im2txtResult = runwayQuery(im2txtHost, Im2txtRequest(image.toDataUrl()))
|
||||
text = result2.caption
|
||||
|
||||
drawer.fill = ColorRGBa.PINK
|
||||
drawer.text(text, 40.0, height - 40.0)
|
||||
image.destroy()
|
||||
}
|
||||
}
|
||||
}
|
||||
//import org.openrndr.application
|
||||
//import org.openrndr.color.ColorRGBa
|
||||
//import org.openrndr.draw.ColorBuffer
|
||||
//import org.openrndr.draw.loadFont
|
||||
//import org.openrndr.extra.runway.*
|
||||
//import org.openrndr.ffmpeg.ScreenRecorder
|
||||
//import java.io.File
|
||||
//
|
||||
///**
|
||||
// * This demonstrates a feedback loop
|
||||
// * This example requires:
|
||||
// * a `runway/im2txt` model active in Runway on port 8000
|
||||
// * a `runway/AttnGAN` model active in Runway on port 8001
|
||||
// */
|
||||
//
|
||||
//fun main() = application {
|
||||
// configure {
|
||||
// width = 768
|
||||
// height = 576
|
||||
// }
|
||||
//
|
||||
// program {
|
||||
//
|
||||
// val attnHost = "http://localhost:8001/query"
|
||||
// val im2txtHost = "http://localhost:8000/query"
|
||||
//
|
||||
// val nouns = File("demo-data/words/nouns.txt").readText().split("\n")
|
||||
// val prepositions = File("demo-data/words/prepositions.txt").readText().split("\n")
|
||||
// val adjectives = File("demo-data/words/adjectives.txt").readText().split("\n")
|
||||
//
|
||||
// val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 36.0)
|
||||
//
|
||||
// var text = "a ${adjectives.random()} ${nouns.random()} ${prepositions.random()} a ${adjectives.random()} ${nouns.random()}"
|
||||
//
|
||||
// extend(ScreenRecorder()) {
|
||||
// frameRate = 1
|
||||
// }
|
||||
//
|
||||
// extend {
|
||||
// val result: AttnGANResult = runwayQuery(attnHost, AttnGANRequest(text))
|
||||
// val image = ColorBuffer.fromUrl(result.result)
|
||||
// drawer.fontMap = font
|
||||
// drawer.image(image, (width - image.width)/2.0, (height - image.height)/2.0)
|
||||
//
|
||||
// val result2:Im2txtResult = runwayQuery(im2txtHost, Im2txtRequest(image.toDataUrl()))
|
||||
// text = result2.caption
|
||||
//
|
||||
// drawer.fill = ColorRGBa.PINK
|
||||
// drawer.text(text, 40.0, height - 40.0)
|
||||
// image.destroy()
|
||||
// }
|
||||
// }
|
||||
//}
|
||||
@@ -1,66 +1,66 @@
|
||||
import org.openrndr.application
|
||||
import org.openrndr.color.ColorRGBa
|
||||
import org.openrndr.draw.Writer
|
||||
import org.openrndr.draw.colorBuffer
|
||||
import org.openrndr.draw.loadFont
|
||||
import org.openrndr.extra.fx.transform.FlipVertically
|
||||
import org.openrndr.extra.runway.DenseCapRequest
|
||||
import org.openrndr.extra.runway.DenseCapResponse
|
||||
import org.openrndr.extra.runway.runwayQuery
|
||||
import org.openrndr.ffmpeg.ScreenRecorder
|
||||
import org.openrndr.ffmpeg.VideoPlayerFFMPEG
|
||||
import org.openrndr.shape.Rectangle
|
||||
|
||||
|
||||
/**
|
||||
* This demonstrates an object to text network. It generates caption texts from objects detected in
|
||||
* the camera image
|
||||
* This example requires a `runway/DenseCap` model to be active in Runway.
|
||||
*/
|
||||
|
||||
fun main() = application {
|
||||
configure {
|
||||
width = 768
|
||||
height = 576
|
||||
}
|
||||
|
||||
program {
|
||||
val image = colorBuffer(640, 360)
|
||||
val camera = VideoPlayerFFMPEG.fromDevice(imageWidth = 640, imageHeight = 360)
|
||||
camera.play()
|
||||
val flip = FlipVertically()
|
||||
|
||||
val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 24.0)
|
||||
camera.newFrame.listen {
|
||||
flip.apply(it.frame, image)
|
||||
}
|
||||
extend(ScreenRecorder()) {
|
||||
frameRate = 1
|
||||
}
|
||||
extend {
|
||||
camera.draw(drawer)
|
||||
drawer.fontMap = font
|
||||
val response: DenseCapResponse =
|
||||
runwayQuery("http://localhost:8000/query", DenseCapRequest(image.toDataUrl(), maxDetections = 1))
|
||||
|
||||
drawer.fontMap = font
|
||||
drawer.image(image)
|
||||
|
||||
for (i in response.bboxes.indices) {
|
||||
val width = (response.bboxes[i][2] - response.bboxes[i][0]) * image.width
|
||||
val height = (response.bboxes[i][3] - response.bboxes[i][1]) * image.height
|
||||
val x = response.bboxes[i][0] * image.width
|
||||
val y = response.bboxes[i][1] * image.height
|
||||
drawer.fill = null
|
||||
drawer.stroke = ColorRGBa.PINK
|
||||
drawer.rectangle(x, y, width, height)
|
||||
drawer.stroke = null
|
||||
drawer.fill = ColorRGBa.PINK
|
||||
val w = Writer(drawer)
|
||||
w.box = Rectangle(x + 10.0, y + 10.0, width - 20.0, height - 20.0)
|
||||
w.newLine()
|
||||
w.text(response.classes[i])
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
//import org.openrndr.application
|
||||
//import org.openrndr.color.ColorRGBa
|
||||
//import org.openrndr.draw.Writer
|
||||
//import org.openrndr.draw.colorBuffer
|
||||
//import org.openrndr.draw.loadFont
|
||||
//import org.openrndr.extra.fx.transform.FlipVertically
|
||||
//import org.openrndr.extra.runway.DenseCapRequest
|
||||
//import org.openrndr.extra.runway.DenseCapResponse
|
||||
//import org.openrndr.extra.runway.runwayQuery
|
||||
//import org.openrndr.ffmpeg.ScreenRecorder
|
||||
//import org.openrndr.ffmpeg.VideoPlayerFFMPEG
|
||||
//import org.openrndr.shape.Rectangle
|
||||
//
|
||||
//
|
||||
///**
|
||||
// * This demonstrates an object to text network. It generates caption texts from objects detected in
|
||||
// * the camera image
|
||||
// * This example requires a `runway/DenseCap` model to be active in Runway.
|
||||
// */
|
||||
//
|
||||
//fun main() = application {
|
||||
// configure {
|
||||
// width = 768
|
||||
// height = 576
|
||||
// }
|
||||
//
|
||||
// program {
|
||||
// val image = colorBuffer(640, 360)
|
||||
// val camera = VideoPlayerFFMPEG.fromDevice(imageWidth = 640, imageHeight = 360)
|
||||
// camera.play()
|
||||
// val flip = FlipVertically()
|
||||
//
|
||||
// val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 24.0)
|
||||
// camera.newFrame.listen {
|
||||
// flip.apply(it.frame, image)
|
||||
// }
|
||||
// extend(ScreenRecorder()) {
|
||||
// frameRate = 1
|
||||
// }
|
||||
// extend {
|
||||
// camera.draw(drawer)
|
||||
// drawer.fontMap = font
|
||||
// val response: DenseCapResponse =
|
||||
// runwayQuery("http://localhost:8000/query", DenseCapRequest(image.toDataUrl(), maxDetections = 1))
|
||||
//
|
||||
// drawer.fontMap = font
|
||||
// drawer.image(image)
|
||||
//
|
||||
// for (i in response.bboxes.indices) {
|
||||
// val width = (response.bboxes[i][2] - response.bboxes[i][0]) * image.width
|
||||
// val height = (response.bboxes[i][3] - response.bboxes[i][1]) * image.height
|
||||
// val x = response.bboxes[i][0] * image.width
|
||||
// val y = response.bboxes[i][1] * image.height
|
||||
// drawer.fill = null
|
||||
// drawer.stroke = ColorRGBa.PINK
|
||||
// drawer.rectangle(x, y, width, height)
|
||||
// drawer.stroke = null
|
||||
// drawer.fill = ColorRGBa.PINK
|
||||
// val w = Writer(drawer)
|
||||
// w.box = Rectangle(x + 10.0, y + 10.0, width - 20.0, height - 20.0)
|
||||
// w.newLine()
|
||||
// w.text(response.classes[i])
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
//}
|
||||
@@ -1,26 +1,26 @@
|
||||
import org.openrndr.application
|
||||
import org.openrndr.draw.*
|
||||
import org.openrndr.extra.runway.*
|
||||
|
||||
/**
|
||||
* This example requires a `runway/Person-Segmentation` model to be active in Runway.
|
||||
*/
|
||||
fun main() = application {
|
||||
configure {
|
||||
width = 331
|
||||
height = 400
|
||||
}
|
||||
|
||||
program {
|
||||
val image = loadImage("demo-data/images/life-cover.jpg")
|
||||
|
||||
val result: PersonSegmentationResult =
|
||||
runwayQuery("http://localhost:8000/query", PersonSegmentationRequest(image.toData(), 0.2))
|
||||
|
||||
val segmentImage = ColorBuffer.fromData(result.image)
|
||||
|
||||
extend {
|
||||
drawer.image(segmentImage, 0.0, 0.0)
|
||||
}
|
||||
}
|
||||
}
|
||||
//import org.openrndr.application
|
||||
//import org.openrndr.draw.*
|
||||
//import org.openrndr.extra.runway.*
|
||||
//
|
||||
///**
|
||||
// * This example requires a `runway/Person-Segmentation` model to be active in Runway.
|
||||
// */
|
||||
//fun main() = application {
|
||||
// configure {
|
||||
// width = 331
|
||||
// height = 400
|
||||
// }
|
||||
//
|
||||
// program {
|
||||
// val image = loadImage("demo-data/images/life-cover.jpg")
|
||||
//
|
||||
// val result: PersonSegmentationResult =
|
||||
// runwayQuery("http://localhost:8000/query", PersonSegmentationRequest(image.toData(), 0.2))
|
||||
//
|
||||
// val segmentImage = ColorBuffer.fromData(result.image)
|
||||
//
|
||||
// extend {
|
||||
// drawer.image(segmentImage, 0.0, 0.0)
|
||||
// }
|
||||
// }
|
||||
//}
|
||||
@@ -1,36 +1,36 @@
|
||||
import org.openrndr.application
|
||||
import org.openrndr.draw.ColorBuffer
|
||||
import org.openrndr.extra.runway.StyleGANRequest
|
||||
import org.openrndr.extra.runway.StyleGANResponse
|
||||
import org.openrndr.extra.runway.runwayQuery
|
||||
/**
|
||||
* This demonstrates an image synthesizer.
|
||||
* StyleGAN accepts a 512 dimensional vector from which it generates images.
|
||||
* This example requires a `runway/StyleGAN` model to be active in Runway.
|
||||
* This also works with `eryksalvaggio/Ascinte_Seated`
|
||||
*/
|
||||
fun main() = application {
|
||||
configure {
|
||||
width = 512
|
||||
height = 512
|
||||
}
|
||||
|
||||
program {
|
||||
val latentSpaceVector = MutableList(512) { Math.random() }
|
||||
|
||||
extend {
|
||||
val result: StyleGANResponse =
|
||||
runwayQuery("http://localhost:8000/query", StyleGANRequest(latentSpaceVector, 0.2))
|
||||
|
||||
val image = ColorBuffer.fromUrl(result.image)
|
||||
|
||||
drawer.image(image, 0.0, 0.0, 512.0, 512.0)
|
||||
|
||||
for (i in latentSpaceVector.indices) {
|
||||
latentSpaceVector[i] += (Math.random() - 0.5) * 0.1
|
||||
}
|
||||
|
||||
image.destroy()
|
||||
}
|
||||
}
|
||||
}
|
||||
//import org.openrndr.application
|
||||
//import org.openrndr.draw.ColorBuffer
|
||||
//import org.openrndr.extra.runway.StyleGANRequest
|
||||
//import org.openrndr.extra.runway.StyleGANResponse
|
||||
//import org.openrndr.extra.runway.runwayQuery
|
||||
///**
|
||||
// * This demonstrates an image synthesizer.
|
||||
// * StyleGAN accepts a 512 dimensional vector from which it generates images.
|
||||
// * This example requires a `runway/StyleGAN` model to be active in Runway.
|
||||
// * This also works with `eryksalvaggio/Ascinte_Seated`
|
||||
// */
|
||||
//fun main() = application {
|
||||
// configure {
|
||||
// width = 512
|
||||
// height = 512
|
||||
// }
|
||||
//
|
||||
// program {
|
||||
// val latentSpaceVector = MutableList(512) { Math.random() }
|
||||
//
|
||||
// extend {
|
||||
// val result: StyleGANResponse =
|
||||
// runwayQuery("http://localhost:8000/query", StyleGANRequest(latentSpaceVector, 0.2))
|
||||
//
|
||||
// val image = ColorBuffer.fromUrl(result.image)
|
||||
//
|
||||
// drawer.image(image, 0.0, 0.0, 512.0, 512.0)
|
||||
//
|
||||
// for (i in latentSpaceVector.indices) {
|
||||
// latentSpaceVector[i] += (Math.random() - 0.5) * 0.1
|
||||
// }
|
||||
//
|
||||
// image.destroy()
|
||||
// }
|
||||
// }
|
||||
//}
|
||||
@@ -1,55 +1,55 @@
|
||||
import org.openrndr.application
|
||||
import org.openrndr.color.ColorRGBa
|
||||
import org.openrndr.draw.Writer
|
||||
import org.openrndr.draw.loadFont
|
||||
import org.openrndr.extra.runway.Gpt2Request
|
||||
import org.openrndr.extra.runway.Gpt2Result
|
||||
import org.openrndr.extra.runway.runwayQuery
|
||||
import org.openrndr.shape.Rectangle
|
||||
|
||||
import java.io.File
|
||||
|
||||
/**
|
||||
* This demonstrates a prompt to text model. It generates a longer text sequence from a prompt.
|
||||
* This example requires a `runway/GPT-2` model to be active in Runway.
|
||||
*/
|
||||
|
||||
fun main() = application {
|
||||
configure {
|
||||
width = 768
|
||||
height = 768
|
||||
}
|
||||
|
||||
program {
|
||||
|
||||
val runwayHost = "http://localhost:8000/query"
|
||||
|
||||
val nouns = File("demo-data/words/nouns.txt").readText().split("\n")
|
||||
val prepositions = File("demo-data/words/prepositions.txt").readText().split("\n")
|
||||
val adjectives = File("demo-data/words/adjectives.txt").readText().split("\n")
|
||||
|
||||
val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 36.0)
|
||||
|
||||
val promptFont = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 24.0)
|
||||
|
||||
extend {
|
||||
val prompt = "a ${adjectives.random()} ${nouns.random()} ${prepositions.random()} a ${adjectives.random()} ${nouns.random()}"
|
||||
drawer.fontMap = promptFont
|
||||
val wp = Writer(drawer)
|
||||
wp.box = Rectangle(20.0, 0.0, width - 40.0, height - 40.0)
|
||||
wp.newLine()
|
||||
wp.text(prompt)
|
||||
|
||||
|
||||
val result: Gpt2Result = runwayQuery(runwayHost, Gpt2Request(prompt, sequenceLength = 128))
|
||||
|
||||
drawer.fill = ColorRGBa.PINK
|
||||
drawer.fontMap = font
|
||||
|
||||
val w = Writer(drawer)
|
||||
w.box = Rectangle(20.0, 60.0, width - 40.0, height - 80.0)
|
||||
w.newLine()
|
||||
w.text(result.text)
|
||||
}
|
||||
}
|
||||
}
|
||||
//import org.openrndr.application
|
||||
//import org.openrndr.color.ColorRGBa
|
||||
//import org.openrndr.draw.Writer
|
||||
//import org.openrndr.draw.loadFont
|
||||
//import org.openrndr.extra.runway.Gpt2Request
|
||||
//import org.openrndr.extra.runway.Gpt2Result
|
||||
//import org.openrndr.extra.runway.runwayQuery
|
||||
//import org.openrndr.shape.Rectangle
|
||||
//
|
||||
//import java.io.File
|
||||
//
|
||||
///**
|
||||
// * This demonstrates a prompt to text model. It generates a longer text sequence from a prompt.
|
||||
// * This example requires a `runway/GPT-2` model to be active in Runway.
|
||||
// */
|
||||
//
|
||||
//fun main() = application {
|
||||
// configure {
|
||||
// width = 768
|
||||
// height = 768
|
||||
// }
|
||||
//
|
||||
// program {
|
||||
//
|
||||
// val runwayHost = "http://localhost:8000/query"
|
||||
//
|
||||
// val nouns = File("demo-data/words/nouns.txt").readText().split("\n")
|
||||
// val prepositions = File("demo-data/words/prepositions.txt").readText().split("\n")
|
||||
// val adjectives = File("demo-data/words/adjectives.txt").readText().split("\n")
|
||||
//
|
||||
// val font = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 36.0)
|
||||
//
|
||||
// val promptFont = loadFont("demo-data/fonts/IBMPlexMono-Regular.ttf", 24.0)
|
||||
//
|
||||
// extend {
|
||||
// val prompt = "a ${adjectives.random()} ${nouns.random()} ${prepositions.random()} a ${adjectives.random()} ${nouns.random()}"
|
||||
// drawer.fontMap = promptFont
|
||||
// val wp = Writer(drawer)
|
||||
// wp.box = Rectangle(20.0, 0.0, width - 40.0, height - 40.0)
|
||||
// wp.newLine()
|
||||
// wp.text(prompt)
|
||||
//
|
||||
//
|
||||
// val result: Gpt2Result = runwayQuery(runwayHost, Gpt2Request(prompt, sequenceLength = 128))
|
||||
//
|
||||
// drawer.fill = ColorRGBa.PINK
|
||||
// drawer.fontMap = font
|
||||
//
|
||||
// val w = Writer(drawer)
|
||||
// w.box = Rectangle(20.0, 60.0, width - 40.0, height - 80.0)
|
||||
// w.newLine()
|
||||
// w.text(result.text)
|
||||
// }
|
||||
// }
|
||||
//}
|
||||
@@ -1,26 +1,26 @@
|
||||
import org.openrndr.application
|
||||
import org.openrndr.draw.*
|
||||
import org.openrndr.extra.runway.*
|
||||
|
||||
/**
|
||||
* This example requires a `runway/U-2-Net` model to be active in Runway.
|
||||
*/
|
||||
fun main() = application {
|
||||
configure {
|
||||
width = 305
|
||||
height = 400
|
||||
}
|
||||
|
||||
program {
|
||||
val image = loadImage("demo-data/images/vw-beetle.jpg")
|
||||
|
||||
val result: U2NetResult =
|
||||
runwayQuery("http://localhost:8000/query", U2NetRequest(image.toData()))
|
||||
|
||||
val segmentImage = ColorBuffer.fromData(result.image)
|
||||
|
||||
extend {
|
||||
drawer.image(segmentImage, 0.0, 0.0)
|
||||
}
|
||||
}
|
||||
}
|
||||
//import org.openrndr.application
|
||||
//import org.openrndr.draw.*
|
||||
//import org.openrndr.extra.runway.*
|
||||
//
|
||||
///**
|
||||
// * This example requires a `runway/U-2-Net` model to be active in Runway.
|
||||
// */
|
||||
//fun main() = application {
|
||||
// configure {
|
||||
// width = 305
|
||||
// height = 400
|
||||
// }
|
||||
//
|
||||
// program {
|
||||
// val image = loadImage("demo-data/images/vw-beetle.jpg")
|
||||
//
|
||||
// val result: U2NetResult =
|
||||
// runwayQuery("http://localhost:8000/query", U2NetRequest(image.toData()))
|
||||
//
|
||||
// val segmentImage = ColorBuffer.fromData(result.image)
|
||||
//
|
||||
// extend {
|
||||
// drawer.image(segmentImage, 0.0, 0.0)
|
||||
// }
|
||||
// }
|
||||
//}
|
||||
Reference in New Issue
Block a user