advancedskrald/ChessAR/Assets/OpenCVForUnity/Examples/MainModules/dnn/DnnObjectDetectionWebCamTextureExample.cs

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#if !UNITY_WSA_10_0
using System;
using System.Collections;
using System.Collections.Generic;
using System.Linq;
using UnityEngine;
using UnityEngine.UI;
using UnityEngine.SceneManagement;
using OpenCVForUnity.CoreModule;
using OpenCVForUnity.DnnModule;
using OpenCVForUnity.ImgprocModule;
using OpenCVForUnity.UnityUtils;
using OpenCVForUnity.UnityUtils.Helper;
namespace OpenCVForUnityExample
{
/// <summary>
/// Dnn ObjectDetection Example
/// Referring to https://github.com/opencv/opencv/blob/master/samples/dnn/object_detection.cpp.
/// </summary>
[RequireComponent (typeof(WebCamTextureToMatHelper))]
public class DnnObjectDetectionWebCamTextureExample : MonoBehaviour
{
[TooltipAttribute ("Path to a binary file of model contains trained weights. It could be a file with extensions .caffemodel (Caffe), .pb (TensorFlow), .t7 or .net (Torch), .weights (Darknet).")]
public string model;
[TooltipAttribute ("Path to a text file of model contains network configuration. It could be a file with extensions .prototxt (Caffe), .pbtxt (TensorFlow), .cfg (Darknet).")]
public string config;
[TooltipAttribute ("Optional path to a text file with names of classes to label detected objects.")]
public string classes;
[TooltipAttribute ("Optional list of classes to label detected objects.")]
public List<string> classesList;
[TooltipAttribute ("Confidence threshold.")]
public float confThreshold;
[TooltipAttribute ("Non-maximum suppression threshold.")]
public float nmsThreshold;
[TooltipAttribute ("Preprocess input image by multiplying on a scale factor.")]
public float scale;
[TooltipAttribute ("Preprocess input image by subtracting mean values. Mean values should be in BGR order and delimited by spaces.")]
public Scalar mean;
[TooltipAttribute ("Indicate that model works with RGB input images instead BGR ones.")]
public bool swapRB;
[TooltipAttribute ("Preprocess input image by resizing to a specific width.")]
public int inpWidth;
[TooltipAttribute ("Preprocess input image by resizing to a specific height.")]
public int inpHeight;
/// <summary>
/// The texture.
/// </summary>
Texture2D texture;
/// <summary>
/// The webcam texture to mat helper.
/// </summary>
WebCamTextureToMatHelper webCamTextureToMatHelper;
/// <summary>
/// The bgr mat.
/// </summary>
Mat bgrMat;
/// <summary>
/// The net.
/// </summary>
Net net;
/// <summary>
/// The FPS monitor.
/// </summary>
FpsMonitor fpsMonitor;
List<string> classNames;
List<string> outBlobNames;
List<string> outBlobTypes;
string classes_filepath;
string config_filepath;
string model_filepath;
#if UNITY_WEBGL && !UNITY_EDITOR
IEnumerator getFilePath_Coroutine;
#endif
// Use this for initialization
void Start ()
{
fpsMonitor = GetComponent<FpsMonitor> ();
webCamTextureToMatHelper = gameObject.GetComponent<WebCamTextureToMatHelper> ();
#if UNITY_WEBGL && !UNITY_EDITOR
getFilePath_Coroutine = GetFilePath ();
StartCoroutine (getFilePath_Coroutine);
#else
classes_filepath = Utils.getFilePath ("dnn/" + classes);
config_filepath = Utils.getFilePath ("dnn/" + config);
model_filepath = Utils.getFilePath ("dnn/" + model);
Run ();
#endif
}
#if UNITY_WEBGL && !UNITY_EDITOR
private IEnumerator GetFilePath ()
{
if (!string.IsNullOrEmpty (classes)) {
var getFilePathAsync_0_Coroutine = Utils.getFilePathAsync ("dnn/" + classes, (result) => {
classes_filepath = result;
});
yield return getFilePathAsync_0_Coroutine;
}
if (!string.IsNullOrEmpty (config)) {
var getFilePathAsync_1_Coroutine = Utils.getFilePathAsync ("dnn/" + config, (result) => {
config_filepath = result;
});
yield return getFilePathAsync_1_Coroutine;
}
if (!string.IsNullOrEmpty (model)) {
var getFilePathAsync_2_Coroutine = Utils.getFilePathAsync ("dnn/" + model, (result) => {
model_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);
if (!string.IsNullOrEmpty (classes)) {
classNames = readClassNames (classes_filepath);
#if !UNITY_WSA_10_0
if (classNames == null) {
Debug.LogError (classes_filepath + " is not loaded. Please see \"StreamingAssets/dnn/setup_dnn_module.pdf\". ");
}
#endif
} else if (classesList.Count > 0) {
classNames = classesList;
}
if (string.IsNullOrEmpty (config_filepath) || string.IsNullOrEmpty (model_filepath)) {
Debug.LogError (config_filepath + " or " + model_filepath + " is not loaded. Please see \"StreamingAssets/dnn/setup_dnn_module.pdf\". ");
} else {
//! [Initialize network]
net = Dnn.readNet (model_filepath, config_filepath);
//! [Initialize network]
outBlobNames = getOutputsNames (net);
// for (int i = 0; i < outBlobNames.Count; i++) {
// Debug.Log ("names [" + i + "] " + outBlobNames [i]);
// }
outBlobTypes = getOutputsTypes (net);
// for (int i = 0; i < outBlobTypes.Count; i++) {
// Debug.Log ("types [" + i + "] " + outBlobTypes [i]);
// }
}
#if UNITY_ANDROID && !UNITY_EDITOR
// Avoids the front camera low light issue that occurs in only some Android devices (e.g. Google Pixel, Pixel2).
webCamTextureToMatHelper.avoidAndroidFrontCameraLowLightIssue = true;
#endif
webCamTextureToMatHelper.Initialize ();
}
/// <summary>
/// Raises the webcam texture to mat helper initialized event.
/// </summary>
public void OnWebCamTextureToMatHelperInitialized ()
{
Debug.Log ("OnWebCamTextureToMatHelperInitialized");
Mat webCamTextureMat = webCamTextureToMatHelper.GetMat ();
texture = new Texture2D (webCamTextureMat.cols (), webCamTextureMat.rows (), TextureFormat.RGBA32, false);
gameObject.GetComponent<Renderer> ().material.mainTexture = texture;
gameObject.transform.localScale = new Vector3 (webCamTextureMat.cols (), webCamTextureMat.rows (), 1);
Debug.Log ("Screen.width " + Screen.width + " Screen.height " + Screen.height + " Screen.orientation " + Screen.orientation);
if (fpsMonitor != null) {
fpsMonitor.Add ("width", webCamTextureMat.width ().ToString ());
fpsMonitor.Add ("height", webCamTextureMat.height ().ToString ());
fpsMonitor.Add ("orientation", Screen.orientation.ToString ());
}
float width = webCamTextureMat.width ();
float height = webCamTextureMat.height ();
float widthScale = (float)Screen.width / width;
float heightScale = (float)Screen.height / height;
if (widthScale < heightScale) {
Camera.main.orthographicSize = (width * (float)Screen.height / (float)Screen.width) / 2;
} else {
Camera.main.orthographicSize = height / 2;
}
bgrMat = new Mat (webCamTextureMat.rows (), webCamTextureMat.cols (), CvType.CV_8UC3);
}
/// <summary>
/// Raises the webcam texture to mat helper disposed event.
/// </summary>
public void OnWebCamTextureToMatHelperDisposed ()
{
Debug.Log ("OnWebCamTextureToMatHelperDisposed");
if (bgrMat != null)
bgrMat.Dispose ();
if (texture != null) {
Texture2D.Destroy (texture);
texture = null;
}
}
/// <summary>
/// Raises the webcam texture to mat helper error occurred event.
/// </summary>
/// <param name="errorCode">Error code.</param>
public void OnWebCamTextureToMatHelperErrorOccurred (WebCamTextureToMatHelper.ErrorCode errorCode)
{
Debug.Log ("OnWebCamTextureToMatHelperErrorOccurred " + errorCode);
}
// Update is called once per frame
void Update ()
{
if (webCamTextureToMatHelper.IsPlaying () && webCamTextureToMatHelper.DidUpdateThisFrame ()) {
Mat rgbaMat = webCamTextureToMatHelper.GetMat ();
if (net == null) {
Imgproc.putText (rgbaMat, "model file is not loaded.", new Point (5, rgbaMat.rows () - 30), Imgproc.FONT_HERSHEY_SIMPLEX, 0.7, new Scalar (255, 255, 255, 255), 2, Imgproc.LINE_AA, false);
Imgproc.putText (rgbaMat, "Please read console message.", new Point (5, rgbaMat.rows () - 10), Imgproc.FONT_HERSHEY_SIMPLEX, 0.7, new Scalar (255, 255, 255, 255), 2, Imgproc.LINE_AA, false);
} else {
Imgproc.cvtColor (rgbaMat, bgrMat, Imgproc.COLOR_RGBA2BGR);
// Create a 4D blob from a frame.
Size inpSize = new Size (inpWidth > 0 ? inpWidth : bgrMat.cols (),
inpHeight > 0 ? inpHeight : bgrMat.rows ());
Mat blob = Dnn.blobFromImage (bgrMat, scale, inpSize, mean, swapRB, false);
// Run a model.
net.setInput (blob);
if (net.getLayer (new DictValue (0)).outputNameToIndex ("im_info") != -1) { // Faster-RCNN or R-FCN
Imgproc.resize (bgrMat, bgrMat, inpSize);
Mat imInfo = new Mat (1, 3, CvType.CV_32FC1);
imInfo.put (0, 0, new float[] {
(float)inpSize.height,
(float)inpSize.width,
1.6f
});
net.setInput (imInfo, "im_info");
}
TickMeter tm = new TickMeter ();
tm.start ();
List<Mat> outs = new List<Mat> ();
net.forward (outs, outBlobNames);
tm.stop ();
// Debug.Log ("Inference time, ms: " + tm.getTimeMilli ());
postprocess (rgbaMat, outs, net);
for (int i = 0; i < outs.Count; i++) {
outs [i].Dispose ();
}
blob.Dispose ();
}
Utils.fastMatToTexture2D (rgbaMat, texture);
}
}
/// <summary>
/// Raises the destroy event.
/// </summary>
void OnDestroy ()
{
webCamTextureToMatHelper.Dispose ();
if (net != null)
net.Dispose ();
Utils.setDebugMode (false);
#if UNITY_WEBGL && !UNITY_EDITOR
if (getFilePath_Coroutine != null) {
StopCoroutine (getFilePath_Coroutine);
((IDisposable)getFilePath_Coroutine).Dispose ();
}
#endif
}
/// <summary>
/// Raises the back button click event.
/// </summary>
public void OnBackButtonClick ()
{
SceneManager.LoadScene ("OpenCVForUnityExample");
}
/// <summary>
/// Raises the play button click event.
/// </summary>
public void OnPlayButtonClick ()
{
webCamTextureToMatHelper.Play ();
}
/// <summary>
/// Raises the pause button click event.
/// </summary>
public void OnPauseButtonClick ()
{
webCamTextureToMatHelper.Pause ();
}
/// <summary>
/// Raises the stop button click event.
/// </summary>
public void OnStopButtonClick ()
{
webCamTextureToMatHelper.Stop ();
}
/// <summary>
/// Raises the change camera button click event.
/// </summary>
public void OnChangeCameraButtonClick ()
{
webCamTextureToMatHelper.requestedIsFrontFacing = !webCamTextureToMatHelper.IsFrontFacing ();
}
/// <summary>
/// Reads the class names.
/// </summary>
/// <returns>The class names.</returns>
/// <param name="filename">Filename.</param>
private List<string> readClassNames (string filename)
{
List<string> classNames = new List<string> ();
System.IO.StreamReader cReader = null;
try {
cReader = new System.IO.StreamReader (filename, System.Text.Encoding.Default);
while (cReader.Peek () >= 0) {
string name = cReader.ReadLine ();
classNames.Add (name);
}
} catch (System.Exception ex) {
Debug.LogError (ex.Message);
return null;
} finally {
if (cReader != null)
cReader.Close ();
}
return classNames;
}
/// <summary>
/// Postprocess the specified frame, outs and net.
/// </summary>
/// <param name="frame">Frame.</param>
/// <param name="outs">Outs.</param>
/// <param name="net">Net.</param>
private void postprocess (Mat frame, List<Mat> outs, Net net)
{
string outLayerType = outBlobTypes [0];
List<int> classIdsList = new List<int> ();
List<float> confidencesList = new List<float> ();
List<OpenCVForUnity.CoreModule.Rect> boxesList = new List<OpenCVForUnity.CoreModule.Rect> ();
if (net.getLayer (new DictValue (0)).outputNameToIndex ("im_info") != -1) { // Faster-RCNN or R-FCN
// Network produces output blob with a shape 1x1xNx7 where N is a number of
// detections and an every detection is a vector of values
// [batchId, classId, confidence, left, top, right, bottom]
if (outs.Count == 1) {
outs [0] = outs [0].reshape (1, (int)outs [0].total () / 7);
// Debug.Log ("outs[i].ToString() " + outs [0].ToString ());
float[] data = new float[7];
for (int i = 0; i < outs [0].rows (); i++) {
outs [0].get (i, 0, data);
float confidence = data [2];
if (confidence > confThreshold) {
int class_id = (int)(data [1]);
int left = (int)(data [3] * frame.cols ());
int top = (int)(data [4] * frame.rows ());
int right = (int)(data [5] * frame.cols ());
int bottom = (int)(data [6] * frame.rows ());
int width = right - left + 1;
int height = bottom - top + 1;
classIdsList.Add ((int)(class_id) - 0);
confidencesList.Add ((float)confidence);
boxesList.Add (new OpenCVForUnity.CoreModule.Rect (left, top, width, height));
}
}
}
} else if (outLayerType == "DetectionOutput") {
// Network produces output blob with a shape 1x1xNx7 where N is a number of
// detections and an every detection is a vector of values
// [batchId, classId, confidence, left, top, right, bottom]
if (outs.Count == 1) {
outs [0] = outs [0].reshape (1, (int)outs [0].total () / 7);
// Debug.Log ("outs[i].ToString() " + outs [0].ToString ());
float[] data = new float[7];
for (int i = 0; i < outs [0].rows (); i++) {
outs [0].get (i, 0, data);
float confidence = data [2];
if (confidence > confThreshold) {
int class_id = (int)(data [1]);
int left = (int)(data [3] * frame.cols ());
int top = (int)(data [4] * frame.rows ());
int right = (int)(data [5] * frame.cols ());
int bottom = (int)(data [6] * frame.rows ());
int width = right - left + 1;
int height = bottom - top + 1;
classIdsList.Add ((int)(class_id) - 0);
confidencesList.Add ((float)confidence);
boxesList.Add (new OpenCVForUnity.CoreModule.Rect (left, top, width, height));
}
}
}
} else if (outLayerType == "Region") {
for (int i = 0; i < outs.Count; ++i) {
// Network produces output blob with a shape NxC where N is a number of
// detected objects and C is a number of classes + 4 where the first 4
// numbers are [center_x, center_y, width, height]
// Debug.Log ("outs[i].ToString() "+outs[i].ToString());
float[] positionData = new float[5];
float[] confidenceData = new float[outs [i].cols () - 5];
for (int p = 0; p < outs [i].rows (); p++) {
outs [i].get (p, 0, positionData);
outs [i].get (p, 5, confidenceData);
int maxIdx = confidenceData.Select ((val, idx) => new { V = val, I = idx }).Aggregate ((max, working) => (max.V > working.V) ? max : working).I;
float confidence = confidenceData [maxIdx];
if (confidence > confThreshold) {
int centerX = (int)(positionData [0] * frame.cols ());
int centerY = (int)(positionData [1] * frame.rows ());
int width = (int)(positionData [2] * frame.cols ());
int height = (int)(positionData [3] * frame.rows ());
int left = centerX - width / 2;
int top = centerY - height / 2;
classIdsList.Add (maxIdx);
confidencesList.Add ((float)confidence);
boxesList.Add (new OpenCVForUnity.CoreModule.Rect (left, top, width, height));
}
}
}
} else {
Debug.Log ("Unknown output layer type: " + outLayerType);
}
MatOfRect boxes = new MatOfRect ();
boxes.fromList (boxesList);
MatOfFloat confidences = new MatOfFloat ();
confidences.fromList (confidencesList);
MatOfInt indices = new MatOfInt ();
Dnn.NMSBoxes (boxes, confidences, confThreshold, nmsThreshold, indices);
// Debug.Log ("indices.dump () "+indices.dump ());
// Debug.Log ("indices.ToString () "+indices.ToString());
for (int i = 0; i < indices.total (); ++i) {
int idx = (int)indices.get (i, 0) [0];
OpenCVForUnity.CoreModule.Rect box = boxesList [idx];
drawPred (classIdsList [idx], confidencesList [idx], box.x, box.y,
box.x + box.width, box.y + box.height, frame);
}
indices.Dispose ();
boxes.Dispose ();
confidences.Dispose ();
}
/// <summary>
/// Draws the pred.
/// </summary>
/// <param name="classId">Class identifier.</param>
/// <param name="conf">Conf.</param>
/// <param name="left">Left.</param>
/// <param name="top">Top.</param>
/// <param name="right">Right.</param>
/// <param name="bottom">Bottom.</param>
/// <param name="frame">Frame.</param>
private void drawPred (int classId, float conf, int left, int top, int right, int bottom, Mat frame)
{
Imgproc.rectangle (frame, new Point (left, top), new Point (right, bottom), new Scalar (0, 255, 0, 255), 2);
string label = conf.ToString ();
if (classNames != null && classNames.Count != 0) {
if (classId < (int)classNames.Count) {
label = classNames [classId] + ": " + label;
}
}
int[] baseLine = new int[1];
Size labelSize = Imgproc.getTextSize (label, Imgproc.FONT_HERSHEY_SIMPLEX, 0.5, 1, baseLine);
top = Mathf.Max (top, (int)labelSize.height);
Imgproc.rectangle (frame, new Point (left, top - labelSize.height),
new Point (left + labelSize.width, top + baseLine [0]), Scalar.all (255), Core.FILLED);
Imgproc.putText (frame, label, new Point (left, top), Imgproc.FONT_HERSHEY_SIMPLEX, 0.5, new Scalar (0, 0, 0, 255));
}
/// <summary>
/// Gets the outputs names.
/// </summary>
/// <returns>The outputs names.</returns>
/// <param name="net">Net.</param>
private List<string> getOutputsNames (Net net)
{
List<string> names = new List<string> ();
MatOfInt outLayers = net.getUnconnectedOutLayers ();
for (int i = 0; i < outLayers.total (); ++i) {
names.Add (net.getLayer (new DictValue ((int)outLayers.get (i, 0) [0])).get_name ());
}
outLayers.Dispose ();
return names;
}
/// <summary>
/// Gets the outputs types.
/// </summary>
/// <returns>The outputs types.</returns>
/// <param name="net">Net.</param>
private List<string> getOutputsTypes (Net net)
{
List<string> types = new List<string> ();
MatOfInt outLayers = net.getUnconnectedOutLayers ();
for (int i = 0; i < outLayers.total (); ++i) {
types.Add (net.getLayer (new DictValue ((int)outLayers.get (i, 0) [0])).get_type ());
}
outLayers.Dispose ();
return types;
}
}
}
#endif