Merge branch 'master' of github.com:openrndr/orx

 Conflicts:

	build.gradle

build.gradle

@@ -14,7 +14,7 @@ buildscript {
 apply plugin: 'org.jetbrains.dokka'
 
 project.ext {
-    openrndrVersion = "0.3.43-rc.10"
+    openrndrVersion = "0.3.43-rc.11"
     kotlinVersion = "1.3.72"
     spekVersion = "2.0.10"
     libfreenectVersion = "0.5.7-1.5.3"

openrndr-demos/build.gradle

@@ -13,9 +13,12 @@ def boofcvVersion = "0.34"
 dependencies {
     demoImplementation(project(":orx-mesh-generators"))
     demoImplementation(project(":orx-camera"))
+    demoImplementation(project(":orx-parameters"))
 
     demoImplementation("org.openrndr:openrndr-core:$openrndrVersion")
     demoImplementation("org.openrndr:openrndr-extensions:$openrndrVersion")
+    demoImplementation("org.openrndr:openrndr-ffmpeg:$openrndrVersion")
+    demoRuntimeOnly("org.openrndr:openrndr-ffmpeg-natives-$openrndrOS:$openrndrVersion")
     demoRuntimeOnly("org.openrndr:openrndr-gl3:$openrndrVersion")
     demoRuntimeOnly("org.openrndr:openrndr-gl3-natives-$openrndrOS:$openrndrVersion")
     demoImplementation(sourceSets.getByName("main").output)

openrndr-demos/src/demo/kotlin/DemoScreenCapture01.kt

@@ -0,0 +1,44 @@
+import org.openrndr.application
+import org.openrndr.color.ColorRGBa
+import org.openrndr.draw.DepthTestPass
+import org.openrndr.draw.DrawPrimitive
+import org.openrndr.draw.isolated
+import org.openrndr.draw.shadeStyle
+import org.openrndr.extras.meshgenerators.boxMesh
+import org.openrndr.ffmpeg.VideoPlayerFFMPEG
+import org.openrndr.math.Vector3
+
+fun main() {
+    application {
+        program {
+            val cube = boxMesh()
+            val screen = VideoPlayerFFMPEG.fromScreen(
+                frameRate = 15.0,
+                imageWidth = 300,
+                imageHeight = 300
+            )
+
+            screen.play()
+            extend {
+                screen.draw(drawer, true) // update the screen grabber
+                drawer.isolated {
+                    clear(ColorRGBa.WHITE)
+                    perspective(60.0, width * 1.0 / height, 0.01, 1000.0)
+                    depthWrite = true
+                    depthTestPass = DepthTestPass.LESS_OR_EQUAL
+                    shadeStyle = shadeStyle {
+                        fragmentTransform = "x_fill = texture(p_tex, vec2(1.0-va_texCoord0.x, va_texCoord0.y));"
+                        screen.colorBuffer?.run {
+                            parameter("tex", this)
+                        }
+                    }
+                    rotate(Vector3.UNIT_Z, 90.0)
+                    translate(0.0, 0.0, -120.0)
+                    rotate(Vector3.UNIT_X, seconds * 10)
+                    scale(90.0)
+                    vertexBuffer(cube, DrawPrimitive.TRIANGLES)
+                }
+            }
+        }
+    }
+}

orx-dnk3/README.md

@@ -54,8 +54,3 @@ Supported Gltf features
 [source code](src/demo/kotlin/DemoScene03.kt)
 
 ![DemoScene03Kt](https://raw.githubusercontent.com/openrndr/orx/media/orx-dnk3/images/DemoScene03Kt.png)
-
-### DemoSkinning01
-[source code](src/demo/kotlin/DemoSkinning01.kt)
-
-![DemoSkinning01Kt](https://raw.githubusercontent.com/openrndr/orx/media/orx-dnk3/images/DemoSkinning01Kt.png)

orx-runway/src/demo/kotlin/PoseNet01.kt

@@ -0,0 +1,44 @@
+import org.openrndr.application
+import org.openrndr.color.ColorRGBa
+import org.openrndr.draw.isolatedWithTarget
+import org.openrndr.draw.loadImage
+import org.openrndr.draw.renderTarget
+import org.openrndr.extra.runway.*
+
+/**
+ * This demonstrates the body estimation model of PoseNet
+ * This example requires a `runway/PoseNet` model active in Runway.
+ */
+fun main() = application {
+    configure {
+        width = 512
+        height = 512
+    }
+
+    program {
+        val rt = renderTarget(512, 512) {
+            colorBuffer()
+        }
+        val image = loadImage("demo-data/images/peopleCity01.jpg")
+
+        drawer.isolatedWithTarget(rt) {
+            drawer.ortho(rt)
+            drawer.clear(ColorRGBa.BLACK)
+            drawer.image(image, (rt.width - image.width) / 2.0, (rt.height - image.height) / 2.0)
+        }
+
+        extend {
+            val result: PoseNetResponse = runwayQuery("http://localhost:8000/query", PoseNetRequest(rt.colorBuffer(0).toData()))
+            val poses = result.poses
+            val scores = result.scores
+
+            drawer.image(image, 0.0, 0.0, 512.0, 512.0)
+
+            poses.forEach { poses ->
+                poses.forEach { pose ->
+                        drawer.circle(pose[0]*512.0, pose[1]*512.0, 10.0)
+                }
+            }
+        }
+    }
+}

orx-runway/src/main/kotlin/Presets.kt

@@ -65,4 +65,14 @@ class DeOldifyResponse(val image: String)
 // -- DenseCap
 
 class DenseCapRequest(val image: String, @SerializedName("max_detections") val maxDetections: Int = 10)
-class DenseCapResponse(val bboxes: List<List<Double>>, val classes: List<String>, val scores: List<Double>)
+class DenseCapResponse(val bboxes: List<List<Double>>, val classes: List<String>, val scores: List<Double>)
+
+// -- PoseNet
+class PoseNetRequest(
+        val image: String,
+        @SerializedName("estimationType") val estimationType: String = "Multi Pose",
+        @SerializedName("maxPoseDetections") val maxPoseDetections: Int = 5,
+        @SerializedName("scoreThreshold") val scoreThreshold: Double = 0.25
+        )
+class PoseNetResponse(val poses: List<List<List<Double>>>, val scores: List<Double>)
+