#if !UNITY_WSA_10_0 using OpenCVForUnity.CoreModule; using OpenCVForUnity.DnnModule; using OpenCVForUnity.ImgprocModule; using OpenCVForUnity.ObjdetectModule; using System; using System.Text; using UnityEngine; namespace OpenCVForUnityExample.DnnModel { /// <summary> /// Referring to https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet /// </summary> public class YuNetV2FaceDetector { Size input_size; float conf_threshold; float nms_threshold; int topK; int backend; int target; protected Scalar bBoxColor = new Scalar(0, 255, 0, 255); protected Scalar[] keyPointsColors = new Scalar[] { new Scalar(0, 0, 255, 255), // # right eye new Scalar(255, 0, 0, 255), // # left eye new Scalar(255, 255, 0, 255), // # nose tip new Scalar(0, 255, 255, 255), // # mouth right new Scalar(0, 255, 0, 255), // # mouth left new Scalar(255, 255, 255, 255) }; FaceDetectorYN detection_model; Mat input_sizeMat; public YuNetV2FaceDetector(string modelFilepath, string configFilepath, Size inputSize, float confThreshold = 0.6f, float nmsThreshold = 0.3f, int topK = 5000, int backend = Dnn.DNN_BACKEND_OPENCV, int target = Dnn.DNN_TARGET_CPU) { // initialize if (!string.IsNullOrEmpty(modelFilepath)) { detection_model = FaceDetectorYN.create(modelFilepath, configFilepath, inputSize, confThreshold, nmsThreshold, topK, backend, target); } input_size = new Size(inputSize.width > 0 ? inputSize.width : 320, inputSize.height > 0 ? inputSize.height : 320); conf_threshold = Mathf.Clamp01(confThreshold); nms_threshold = Mathf.Clamp01(nmsThreshold); this.topK = topK; this.backend = backend; this.target = target; } protected virtual Mat preprocess(Mat image) { int h = (int)input_size.height; int w = (int)input_size.width; if (input_sizeMat == null) input_sizeMat = new Mat(new Size(w, h), CvType.CV_8UC3);// [h, w] Imgproc.resize(image, input_sizeMat, new Size(w, h)); return input_sizeMat;// [h, w, 3] } public virtual Mat infer(Mat image) { // cheack if (image.channels() != 3) { Debug.Log("The input image must be in BGR format."); return new Mat(); } // Preprocess Mat input_blob = preprocess(image); // Forward Mat results = new Mat(); detection_model.detect(input_blob, results); // Postprocess // scale_boxes float x_factor = image.width() / (float)input_size.width; float y_factor = image.height() / (float)input_size.height; for (int i = 0; i < results.rows(); ++i) { float[] results_arr = new float[14]; results.get(i, 0, results_arr); for (int j = 0; j < 14; ++j) { if (j % 2 == 0) { results_arr[j] = results_arr[j] * x_factor; } else { results_arr[j] = results_arr[j] * y_factor; } } results.put(i, 0, results_arr); } return results; } protected virtual Mat postprocess(Mat output_blob) { return output_blob; } public virtual void visualize(Mat image, Mat results, bool print_results = false, bool isRGB = false) { if (image.IsDisposed) return; if (results.empty() || results.cols() < 15) return; for (int i = results.rows() - 1; i >= 0; --i) { float[] box = new float[4]; results.get(i, 0, box); float[] conf = new float[1]; results.get(i, 14, conf); float[] landmarks = new float[10]; results.get(i, 4, landmarks); float left = box[0]; float top = box[1]; float right = box[0] + box[2]; float bottom = box[1] + box[3]; Scalar bbc = bBoxColor; Scalar bbcolor = isRGB ? bbc : new Scalar(bbc.val[2], bbc.val[1], bbc.val[0], bbc.val[3]); Imgproc.rectangle(image, new Point(left, top), new Point(right, bottom), bbcolor, 2); string label = String.Format("{0:0.0000}", conf[0]); int[] baseLine = new int[1]; Size labelSize = Imgproc.getTextSize(label, Imgproc.FONT_HERSHEY_SIMPLEX, 0.5, 1, baseLine); top = Mathf.Max((float)top, (float)labelSize.height); Imgproc.rectangle(image, new Point(left, top - labelSize.height), new Point(left + labelSize.width, top + baseLine[0]), bbcolor, Core.FILLED); Imgproc.putText(image, label, new Point(left, top), Imgproc.FONT_HERSHEY_SIMPLEX, 0.5, new Scalar(0, 0, 0, 255), 1, Imgproc.LINE_AA); // draw landmark points for (int j = 0; j < 10; j += 2) { Scalar c = keyPointsColors[(j / 2) % keyPointsColors.Length]; Scalar color = isRGB ? c : new Scalar(c.val[2], c.val[1], c.val[0], c.val[3]); Imgproc.circle(image, new Point(landmarks[j], landmarks[j + 1]), 2, color, 2); } } // Print results if (print_results) { StringBuilder sb = new StringBuilder(); for (int i = 0; i < results.rows(); ++i) { float[] box = new float[4]; results.get(i, 0, box); float[] conf = new float[1]; results.get(i, 14, conf); float[] landmarks = new float[10]; results.get(i, 4, landmarks); sb.AppendLine(String.Format("-----------face {0}-----------", i + 1)); sb.AppendLine(String.Format("conf: {0:0.0000}", conf[0])); sb.AppendLine(String.Format("box: {0:0} {1:0} {2:0} {3:0}", box[0], box[1], box[2], box[3])); sb.Append("landmarks: "); foreach (var p in landmarks) { sb.Append(String.Format("{0:0} ", p)); } sb.AppendLine(); } Debug.Log(sb); } } public virtual void dispose() { if (detection_model != null) detection_model.Dispose(); if (input_sizeMat != null) input_sizeMat.Dispose(); input_sizeMat = null; } } } #endif