331 lines
13 KiB
C#
331 lines
13 KiB
C#
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#if !UNITY_WSA_10_0
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using UnityEngine;
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using UnityEngine.SceneManagement;
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using System;
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using System.Collections;
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using System.Collections.Generic;
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using OpenCVForUnity.CoreModule;
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using OpenCVForUnity.ImgcodecsModule;
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using OpenCVForUnity.DnnModule;
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using OpenCVForUnity.ImgprocModule;
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using OpenCVForUnity.UnityUtils;
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namespace OpenCVForUnityExample
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{
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/// <summary>
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/// OpenPose Example
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/// This example uses OpenPose human pose estimation network.
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/// Referring to https://github.com/opencv/opencv/blob/master/samples/dnn/openpose.py.
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/// </summary>
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public class OpenPoseExample : MonoBehaviour
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{
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const float inWidth = 368;
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const float inHeight = 368;
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//COCO
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// Dictionary<string, int> BODY_PARTS
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// = new Dictionary<string, int> () {
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// { "Nose", 0 }, { "Neck", 1 }, { "RShoulder", 2 }, { "RElbow", 3 }, {
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// "RWrist",
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// 4
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// },
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// { "LShoulder",5 }, { "LElbow", 6 }, { "LWrist", 7 }, { "RHip", 8 }, {
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// "RKnee",
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// 9
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// },
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// { "RAnkle", 10 }, { "LHip", 11 }, { "LKnee", 12 }, { "LAnkle", 13 }, {
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// "REye",
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// 14
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// },
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// { "LEye", 15 }, { "REar", 16 }, { "LEar", 17 }, {
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// "Background",
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// 18
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// }
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// };
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//
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// string[,] POSE_PAIRS
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// = new string[,] {
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// { "Neck", "RShoulder" }, { "Neck", "LShoulder" }, {
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// "RShoulder",
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// "RElbow"
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// },
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// { "RElbow", "RWrist" }, { "LShoulder", "LElbow" }, {
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// "LElbow",
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// "LWrist"
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// },
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// { "Neck", "RHip" }, { "RHip", "RKnee" }, { "RKnee", "RAnkle" }, {
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// "Neck",
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// "LHip"
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// },
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// { "LHip", "LKnee" }, { "LKnee", "LAnkle" }, { "Neck", "Nose" }, {
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// "Nose",
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// "REye"
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// },
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// { "REye", "REar" }, { "Nose", "LEye" }, { "LEye", "LEar" }
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// };
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//MPI
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Dictionary<string, int> BODY_PARTS
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= new Dictionary<string, int> () { { "Head", 0 }, { "Neck", 1 }, {
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"RShoulder",
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2
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}, {
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"RElbow",
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3
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}, {
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"RWrist",
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4
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},
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{ "LShoulder", 5 }, { "LElbow", 6 }, { "LWrist", 7 }, { "RHip", 8 }, {
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"RKnee",
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9
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},
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{ "RAnkle", 10 }, { "LHip", 11 }, { "LKnee", 12 }, { "LAnkle", 13 }, {
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"Chest",
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14
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},
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{ "Background", 15 }
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};
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string[,] POSE_PAIRS = new string[,] {
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{ "Head", "Neck" }, {
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"Neck",
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"RShoulder"
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}, {
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"RShoulder",
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"RElbow"
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},
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{ "RElbow", "RWrist" },
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{ "Neck", "LShoulder" }, {
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"LShoulder",
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"LElbow"
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},
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{ "LElbow", "LWrist" },
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{ "Neck", "Chest" },
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{ "Chest", "RHip" }, {
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"RHip",
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"RKnee"
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},
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{ "RKnee", "RAnkle" },
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{ "Chest", "LHip" },
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{ "LHip", "LKnee" }, {
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"LKnee",
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"LAnkle"
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}
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};
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string COCO_val2014_000000000589_jpg_filepath;
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string pose_iter_160000_caffemodel_filepath;
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string openpose_pose_mpi_faster_4_stages_prototxt_filepath;
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#if UNITY_WEBGL && !UNITY_EDITOR
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IEnumerator getFilePath_Coroutine;
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#endif
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// Use this for initialization
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void Start ()
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{
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#if UNITY_WEBGL && !UNITY_EDITOR
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getFilePath_Coroutine = GetFilePath ();
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StartCoroutine (getFilePath_Coroutine);
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#else
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COCO_val2014_000000000589_jpg_filepath = Utils.getFilePath ("dnn/COCO_val2014_000000000589.jpg");
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pose_iter_160000_caffemodel_filepath = Utils.getFilePath ("dnn/pose_iter_160000.caffemodel");
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openpose_pose_mpi_faster_4_stages_prototxt_filepath = Utils.getFilePath ("dnn/openpose_pose_mpi_faster_4_stages.prototxt");
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Run ();
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#endif
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}
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#if UNITY_WEBGL && !UNITY_EDITOR
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private IEnumerator GetFilePath ()
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{
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var getFilePathAsync_0_Coroutine = Utils.getFilePathAsync ("dnn/COCO_val2014_000000000589.jpg", (result) => {
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COCO_val2014_000000000589_jpg_filepath = result;
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});
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yield return getFilePathAsync_0_Coroutine;
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var getFilePathAsync_1_Coroutine = Utils.getFilePathAsync ("dnn/pose_iter_160000.caffemodel", (result) => {
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pose_iter_160000_caffemodel_filepath = result;
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});
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yield return getFilePathAsync_1_Coroutine;
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var getFilePathAsync_2_Coroutine = Utils.getFilePathAsync ("dnn/openpose_pose_mpi_faster_4_stages.prototxt", (result) => {
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openpose_pose_mpi_faster_4_stages_prototxt_filepath = result;
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});
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yield return getFilePathAsync_2_Coroutine;
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getFilePath_Coroutine = null;
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Run ();
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}
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#endif
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// Use this for initialization
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void Run ()
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{
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//if true, The error log of the Native side OpenCV will be displayed on the Unity Editor Console.
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Utils.setDebugMode (true);
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Mat img = Imgcodecs.imread (COCO_val2014_000000000589_jpg_filepath);
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#if !UNITY_WSA_10_0
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if (img.empty ()) {
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Debug.LogError ("dnn/COCO_val2014_000000000589.jpg is not loaded.The image file can be downloaded here: \"https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/examples/media/COCO_val2014_000000000589.jpg\" folder. ");
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img = new Mat (368, 368, CvType.CV_8UC3, new Scalar (0, 0, 0));
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}
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#endif
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//Adust Quad.transform.localScale.
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gameObject.transform.localScale = new Vector3 (img.width (), img.height (), 1);
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Debug.Log ("Screen.width " + Screen.width + " Screen.height " + Screen.height + " Screen.orientation " + Screen.orientation);
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float imageWidth = img.width ();
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float imageHeight = img.height ();
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float widthScale = (float)Screen.width / imageWidth;
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float heightScale = (float)Screen.height / imageHeight;
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if (widthScale < heightScale) {
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Camera.main.orthographicSize = (imageWidth * (float)Screen.height / (float)Screen.width) / 2;
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} else {
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Camera.main.orthographicSize = imageHeight / 2;
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}
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Net net = null;
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if (string.IsNullOrEmpty (pose_iter_160000_caffemodel_filepath) || string.IsNullOrEmpty (openpose_pose_mpi_faster_4_stages_prototxt_filepath)) {
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Debug.LogError ("model file is not loaded. The model and prototxt file can be downloaded here: \"http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/mpi/pose_iter_160000.caffemodel\",\"https://github.com/opencv/opencv_extra/blob/master/testdata/dnn/openpose_pose_mpi_faster_4_stages.prototxt\". Please copy to “Assets/StreamingAssets/dnn/” folder. ");
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} else {
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net = Dnn.readNetFromCaffe (openpose_pose_mpi_faster_4_stages_prototxt_filepath, pose_iter_160000_caffemodel_filepath);
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//Intel's Deep Learning Inference Engine backend is supported on Windows 64bit platform only. Please refer to ReadMe.pdf for the setup procedure.
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//net.setPreferableBackend (Dnn.DNN_BACKEND_INFERENCE_ENGINE);
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}
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if (net == null) {
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Imgproc.putText (img, "model file is not loaded.", new Point (5, img.rows () - 30), Imgproc.FONT_HERSHEY_SIMPLEX, 0.7, new Scalar (255, 255, 255), 2, Imgproc.LINE_AA, false);
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Imgproc.putText (img, "Please read console message.", new Point (5, img.rows () - 10), Imgproc.FONT_HERSHEY_SIMPLEX, 0.7, new Scalar (255, 255, 255), 2, Imgproc.LINE_AA, false);
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} else {
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float frameWidth = img.cols ();
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float frameHeight = img.rows ();
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Mat input = Dnn.blobFromImage (img, 1.0 / 255, new Size (inWidth, inHeight), new Scalar (0, 0, 0), false, false);
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net.setInput (input);
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// TickMeter tm = new TickMeter ();
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// tm.start ();
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Mat output = net.forward ();
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// tm.stop ();
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// Debug.Log ("Inference time, ms: " + tm.getTimeMilli ());
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output = output.reshape (1, 16);
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float[] data = new float[46 * 46];
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List<Point> points = new List<Point> ();
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for (int i = 0; i < BODY_PARTS.Count; i++) {
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output.get (i, 0, data);
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Mat heatMap = new Mat (1, data.Length, CvType.CV_32FC1);
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heatMap.put (0, 0, data);
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//Originally, we try to find all the local maximums. To simplify a sample
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//we just find a global one. However only a single pose at the same time
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//could be detected this way.
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Core.MinMaxLocResult result = Core.minMaxLoc (heatMap);
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heatMap.Dispose ();
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double x = (frameWidth * (result.maxLoc.x % 46)) / 46;
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double y = (frameHeight * (result.maxLoc.x / 46)) / 46;
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if (result.maxVal > 0.1) {
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points.Add (new Point (x, y));
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} else {
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points.Add (null);
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}
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}
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for (int i = 0; i < POSE_PAIRS.GetLength (0); i++) {
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string partFrom = POSE_PAIRS [i, 0];
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string partTo = POSE_PAIRS [i, 1];
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int idFrom = BODY_PARTS [partFrom];
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int idTo = BODY_PARTS [partTo];
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if (points [idFrom] != null && points [idTo] != null) {
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Imgproc.line (img, points [idFrom], points [idTo], new Scalar (0, 255, 0), 3);
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Imgproc.ellipse (img, points [idFrom], new Size (3, 3), 0, 0, 360, new Scalar (0, 0, 255), Core.FILLED);
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Imgproc.ellipse (img, points [idTo], new Size (3, 3), 0, 0, 360, new Scalar (0, 0, 255), Core.FILLED);
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}
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}
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MatOfDouble timings = new MatOfDouble ();
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long t = net.getPerfProfile (timings);
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Debug.Log ("t: " + t);
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Debug.Log ("timings.dump(): " + timings.dump ());
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double freq = Core.getTickFrequency () / 1000;
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Debug.Log ("freq: " + freq);
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Imgproc.putText (img, (t / freq) + "ms", new Point (10, img.height () - 10), Imgproc.FONT_HERSHEY_SIMPLEX, 0.6, new Scalar (0, 0, 255), 2);
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}
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Imgproc.cvtColor (img, img, Imgproc.COLOR_BGR2RGB);
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Texture2D texture = new Texture2D (img.cols (), img.rows (), TextureFormat.RGBA32, false);
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Utils.matToTexture2D (img, texture);
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gameObject.GetComponent<Renderer> ().material.mainTexture = texture;
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Utils.setDebugMode (false);
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}
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// Update is called once per frame
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void Update ()
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{
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}
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/// <summary>
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/// Raises the disable event.
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/// </summary>
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void OnDisable ()
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{
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#if UNITY_WEBGL && !UNITY_EDITOR
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if (getFilePath_Coroutine != null) {
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StopCoroutine (getFilePath_Coroutine);
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((IDisposable)getFilePath_Coroutine).Dispose ();
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}
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#endif
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}
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/// <summary>
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/// Raises the back button click event.
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/// </summary>
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public void OnBackButtonClick ()
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{
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SceneManager.LoadScene ("OpenCVForUnityExample");
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}
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}
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}
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#endif
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