using UnityEngine; using Unity.Sentis; using UnityEngine.Video; using UnityEngine.UI; using Lays = Unity.Sentis.Layers; using System.Collections.Generic; /* * Iris Inference * ============== * * Basic inference script for Iris * * Put this script on the Main Camera * Put iris_landmark.sentis in the Assets/StreamingAssets folder * Create a RawImage of in the scene * Put a link to that image in previewUI * Put a video in Assets/StreamingAssets folder and put the name of it int videoName * Or put a test image in inputImage * Set inputType to appropriate input */ public class RunIris : MonoBehaviour { //Drag a link to a raw image here: public RawImage previewUI = null; public enum InputType { Image, Video, Webcam }; public string videoName = "chatting.mp4"; // Input image for neural network public Texture2D inputImage; public InputType inputType = InputType.Video; Vector2Int resolution = new Vector2Int(640, 640); WebCamTexture webcam; VideoPlayer video; const BackendType backend = BackendType.GPUCompute; RenderTexture targetTexture; Texture2D canvasTexture; const int markerWidth = 5; Color32[] markerPixels; IWorker worker; //Holds image size const int size = 64; Ops ops; ITensorAllocator allocator; Model model; //webcam device name: const string deviceName = ""; bool closing = false; void Start() { allocator = new TensorCachingAllocator(); //(Note: if using a webcam on mobile get permissions here first) SetupTextures(); SetupInput(); SetupModel(); SetupEngine(); SetupMarkers(); } void SetupModel() { model = ModelLoader.Load(Application.streamingAssetsPath + "/iris_landmark.sentis"); } public void SetupEngine() { worker = WorkerFactory.CreateWorker(backend, model); ops = WorkerFactory.CreateOps(backend, allocator); } void SetupTextures() { targetTexture = new RenderTexture(resolution.x, resolution.y, 0); canvasTexture = new Texture2D(targetTexture.width, targetTexture.height); previewUI.texture = targetTexture; } void SetupMarkers() { markerPixels = new Color32[markerWidth * markerWidth]; for (int n = 0; n < markerWidth * markerWidth; n++) { markerPixels[n] = Color.white; } int center = markerWidth / 2; markerPixels[center * markerWidth + center] = Color.black; } void SetupInput() { switch (inputType) { case InputType.Webcam: { webcam = new WebCamTexture(deviceName, resolution.x, resolution.y); webcam.requestedFPS = 30; webcam.Play(); break; } case InputType.Video: { video = gameObject.AddComponent();//new VideoPlayer(); video.renderMode = VideoRenderMode.APIOnly; video.source = VideoSource.Url; video.url = Application.streamingAssetsPath + "/"+videoName; video.isLooping = true; video.Play(); break; } default: { Graphics.Blit(inputImage, targetTexture); } break; } } void Update() { if (inputType == InputType.Webcam) { // Format video input if (!webcam.didUpdateThisFrame) return; var aspect1 = (float)webcam.width / webcam.height; var aspect2 = (float)resolution.x / resolution.y; var gap = aspect2 / aspect1; var vflip = webcam.videoVerticallyMirrored; var scale = new Vector2(gap, vflip ? -1 : 1); var offset = new Vector2((1 - gap) / 2, vflip ? 1 : 0); Graphics.Blit(webcam, targetTexture, scale, offset); } if (inputType == InputType.Video) { var aspect1 = (float)video.width / video.height; var aspect2 = (float)resolution.x / resolution.y; var gap = aspect2 / aspect1; var vflip = false; var scale = new Vector2(gap, vflip ? -1 : 1); var offset = new Vector2((1 - gap) / 2, vflip ? 1 : 0); Graphics.Blit(video.texture, targetTexture, scale, offset); } if (inputType == InputType.Image) { Graphics.Blit(inputImage, targetTexture); } if (Input.GetKeyDown(KeyCode.Escape)) { closing = true; Application.Quit(); } if (Input.GetKeyDown(KeyCode.P)) { previewUI.enabled = !previewUI.enabled; } } void LateUpdate() { if (!closing) { RunInference(targetTexture); } } void RunInference(Texture source) { var transform = new TextureTransform(); transform.SetDimensions(size, size, 3); transform.SetTensorLayout(0, 1, 2, 3); using var image0 = TextureConverter.ToTensor(source, transform); // Pre-process the image to make input in range (-1..1) using var image = ops.Mad(image0, 2f, -1f); worker.Execute(image); using var eyeLandmarks = worker.PeekOutput("output_eyes_contours_and_brows") as TensorFloat; using var irisLandmarks = worker.PeekOutput("output_iris") as TensorFloat; float scaleX = targetTexture.width * 1f / size; float scaleY = targetTexture.height * 1f / size; eyeLandmarks.MakeReadable(); irisLandmarks.MakeReadable(); //Draw the markers RenderTexture.active = targetTexture; canvasTexture.ReadPixels(new Rect(0, 0, targetTexture.width, targetTexture.height), 0, 0); DrawLandmarks(irisLandmarks, scaleX, scaleY); DrawLandmarks(eyeLandmarks, scaleX, scaleY); canvasTexture.Apply(); Graphics.Blit(canvasTexture, targetTexture); RenderTexture.active = null; } void DrawLandmarks(TensorFloat landmarks, float scaleX, float scaleY) { int numLandmarks = landmarks.shape[1] / 3; for (int n = 0; n < numLandmarks; n++) { int px = (int)(landmarks[ 0, n * 3 + 0] * scaleX) - (markerWidth - 1) / 2; int py = (int)(landmarks[ 0, n * 3 + 1] * scaleY) - (markerWidth - 1) / 2; int pz = (int)(landmarks[ 0, n * 3 + 2] * scaleX); int destX = Mathf.Clamp(px, 0, targetTexture.width - 1 - markerWidth); int destY = Mathf.Clamp(targetTexture.height - 1 - py, 0, targetTexture.height - 1 - markerWidth); canvasTexture.SetPixels32(destX, destY, markerWidth, markerWidth, markerPixels); } } void CleanUp() { closing = true; ops?.Dispose(); allocator?.Dispose(); if (webcam) Destroy(webcam); if (video) Destroy(video); RenderTexture.active = null; targetTexture.Release(); worker?.Dispose(); worker = null; } void OnDestroy() { CleanUp(); } }