Upgrade to OPENRNDR 0.4 snapshot

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

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+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)

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

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+package org.openrndr.extra.runway
+
+import com.google.gson.Gson
+import org.openrndr.draw.ColorBuffer
+import org.openrndr.draw.ImageFileFormat
+import java.io.ByteArrayInputStream
+import java.io.File
+import java.net.*
+import java.util.*
+
+/**
+ * Construct a base64 representation of an encoded image
+ */
+fun ColorBuffer.toData(format: ImageFileFormat = ImageFileFormat.JPG): String {
+    val tempFile = File.createTempFile("orx-runway", null)
+    saveToFile(tempFile, format, async = false)
+    val ref = File(tempFile.absolutePath)
+    val imageBytes = ref.readBytes()
+    val encoder = Base64.getEncoder()
+    val base64Data = encoder.encodeToString(imageBytes)
+    tempFile.delete()
+    return "data:image/jpeg;base64,$base64Data"
+}
+
+/**
+ * Construct a color buffer from a base64 data string
+ */
+fun ColorBuffer.Companion.fromData(data: String): ColorBuffer {
+    val decoder = Base64.getDecoder()
+    val commaIndex = data.indexOf(",")
+    val imageData = decoder.decode(data.drop(commaIndex + 1))
+
+    ByteArrayInputStream(imageData).use {
+        return ColorBuffer.fromStream(it)
+    }
+}
+
+/**
+ * Perform a Runway query
+ * @param target url string e.g. http://localhost:8000/query
+ */
+inline fun <Q, reified R> runwayQuery(target: String, query: Q): R {
+
+    try {
+        val queryJson = Gson().toJson(query)
+        val connection = URL(target).openConnection() as HttpURLConnection
+
+        connection.doOutput = true
+        connection.connectTimeout = 1_000
+        connection.readTimeout = 200_000
+        connection.requestMethod = "POST"
+        connection.setRequestProperty("Content-Type", "application/json")
+        connection.setRequestProperty("Accept", "application/json")
+
+        val outputStream = connection.outputStream
+        outputStream.write(queryJson.toByteArray())
+        outputStream.flush()
+
+        val inputStream = connection.inputStream
+        val responseJson = String(inputStream.readBytes())
+
+        inputStream.close()
+        connection.disconnect()
+
+        return Gson().fromJson(responseJson, R::class.java)
+    } catch (e: SocketTimeoutException) {
+        error("RunwayML connection timed out '$target'. Check if Runway and model are running.")
+    } catch (e: ConnectException) {
+        error("RunwayML connection refused '$target'. Check if Runway and model are running.")
+    } catch (e: UnknownHostException) {
+        error("Runway host not found '$target'. Check if Runway and model are running.")
+    }
+
+}