Add PoseNet presets and example (#124)

* PoseNet presets and example

* Update description

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>)
+