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