Upgrade to OPENRNDR 0.4 snapshot

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

@@ -0,0 +1,98 @@
+package org.openrndr.extra.runway
+
+import com.google.gson.annotations.SerializedName
+
+// -- AttnGAN
+class AttnGANRequest(val caption: String)
+
+class AttnGANResult(val result: String)
+
+// -- BASNET
+class BASNETRequest(val image: String)
+
+class BASNETResult(val image: String)
+
+// -- BDCN
+class BdcnRequest(val input_image: String)
+
+class BdcnResult(val output_image: String)
+
+// -- BigBiGAN
+class BigBiGANQuery(@SerializedName("input_image") val inputImage: String)
+
+class BigBiGANResult(@SerializedName("output_image") val outputImage: String)
+
+// -- DensePose
+class DensePoseQuery(@SerializedName("input") val input: String)
+
+class DensePoseResult(@SerializedName("output") val output: String)
+
+// -- SPADE-COCO
+class SpadeCocoRequest(val semantic_map: String)
+
+class SpadeCocoResult(val output: String)
+
+// -- GPT-2
+class Gpt2Request(val prompt: String, val seed: Int = 0, @SerializedName("sequence_length") val sequenceLength: Int = 128)
+
+class Gpt2Result(val text: String)
+
+// -- im2txt
+class Im2txtRequest(val image: String)
+
+class Im2txtResult(val caption: String)
+
+// -- PSENet
+class PsenetRequest(@SerializedName("input_image") val inputImage: String)
+
+class PsenetResult(val bboxes: Array<Array<Double>>)
+
+// -- Face landmarks
+class FaceLandmarksRequest(val photo: String)
+
+class FaceLandmarksResponse(val points: List<List<Double>>, val labels: List<String>)
+
+// -- StyleGAN
+
+/**
+ * StyleGAN request
+ * @param z a list of 512 doubles
+ */
+class StyleGANRequest(val z: List<Double>, val truncation: Double = 1.0)
+
+class StyleGANResponse(val image: String)
+
+// -- DeOldify
+class DeOldifyRequest(val image: String, val renderFactor: Int = 20)
+
+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>)
+
+// -- Person-Segmentation
+/**
+ * Automatically detects people and extracts them from photos
+ *
+ * @property image
+ * @property threshold [0.0, 1.0]
+ */
+class PersonSegmentationRequest(val image: String, val threshold: Double)
+
+class PersonSegmentationResult(val image: String)
+
+// -- 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>)
+
+// -- U-2-Net
+class U2NetRequest(val image: String)
+
+class U2NetResult(val image: String)