private async Task LoadModelAsync()
{
StorageFile modelFile = await StorageFile.GetFileFromApplicationUriAsync(new Uri(fileName));
_model = new ObjectDetection(new string[] { "AceOfHearts" });
await _model.Init(modelFile);
}
private async void InitModel()
{
_objectDetection = new ObjectDetection();
var modelFile = await StorageFile.GetFileFromApplicationUriAsync(new Uri($"ms-appx:///Assets/model.onnx"));
await _objectDetection.Init(modelFile);
}
static void Main(string[] args)
{
AppDomain domain = Startup();
ImageStitching stitcher = new ImageStitching();
Barcode decoder = new Barcode();
ObjectDetection detector = new ObjectDetection();
string cpu_folder_name;
/* Stitch Image and decode barcode: */
var img_list = stitcher.Load_images(SolutionDir.ToString(), Data.Constants.Seg_R, Data.Constants.Seg_R, Data.Constants.filename_top);
var img = stitcher.Stitch(img_list);
var barcode = decoder.Barcode_finding_run(img);
/* Create file and save Image: */
cpu_folder_name = "ACIS_" + DateTime.Now.ToString("yyyy-MM-dd-hh-mm-ss");
string save_path = SolutionDir.ToString() + "\\" + cpu_folder_name;
Directory.CreateDirectory(Path.Combine(SolutionDir.ToString(), cpu_folder_name));
String fileName = "BarcodeInfo_" + Data.Constants.filename_top + ".xml";
new XDocument(new XElement("ACIS", new XElement("barcode", barcode))).Save(Path.Combine(save_path, fileName));
img.Save(Path.Combine(save_path, Data.Constants.filename_top + ".jpg"));
/* Defect Detection: */
Cleanup(domain, stitcher);
Console.WriteLine("\n\n");
Console.WriteLine("The stitched image and xml file holding the barcode has been saved");
Console.WriteLine("The save location is in the ACIS_Showcase solution directory under Images");
Console.WriteLine("Defect Detection Will be added shortly.");
Console.WriteLine("Thank you. Hit Enter to continue:");
Console.ReadLine();
}
void Start()
{
characterController = GetComponent <CharacterController>();
objectDetection = GetComponent <ObjectDetection>();
holder = GetComponent <Holder>();
animator = GetComponentInChildren <Animator>();
}
private void Awake()
{
foxCharacter = GetComponent <Fox>();
modelMesh = GetComponentInChildren <MeshRenderer>();
movementController = GetComponentInChildren <Movement>();
detectorFood = GetComponentInChildren <ObjectDetection>();
boxCollider = GetComponentInChildren <BoxCollider>();
}
public ProcessWithONNX()
{
List <String> labels = new List <String> {
"box"
};
objectDetection = new ObjectDetection(labels, 20, 0.4F, 0.45F);
}
private async void InitONNX()
{
var modelFile = await StorageFile.GetFileFromApplicationUriAsync(new Uri($"ms-appx:///Model/{ModelFilename}"));
objectDetection = new ObjectDetection(new List <string>()
{
"Mask", "No Mask"
});
await objectDetection.Init(modelFile);
}
void Start()
{
anim = GetComponent <Animator>();
playerCam = Camera.main.transform;
targetTransform = new GameObject().transform;
targetTransform.name = "targetTransform";
objectDetection = GetComponent <ObjectDetection>();
}
static void Main(string[] args)
{
try
{
//Setting global device
Logging.OnWriteLog += Logging_OnWriteLog;
//XOR Example
XORExample.LoadData();
XORExample.BuildModel();
XORExample.Train();
//Housing regression example
HousingRegression.LoadData();
HousingRegression.BuildModel();
HousingRegression.Train();
//MNIST Classification example
MNISTClassifier.LoadData();
MNISTClassifier.BuildModel();
MNISTClassifier.Train();
//LSTM Time series example
TimeSeriesPrediction.LoadData();
TimeSeriesPrediction.BuildModel();
TimeSeriesPrediction.Train();
//Multi variate time series prediction
MiltiVariateTimeSeriesPrediction.LoadData();
MiltiVariateTimeSeriesPrediction.BuildModel();
MiltiVariateTimeSeriesPrediction.Train();
//Cifar - 10 Classification example
//Cifar10Classification.LoadData();
//Cifar10Classification.BuildModel();
//Cifar10Classification.Train();
//Image classification example
Console.WriteLine("ResNet50 Prediction: " + ImageClassification.ImagenetTest(SiaNet.Common.ImageNetModel.ResNet50)[0].Name);
//Console.WriteLine("Cifar 10 Prediction: " + ImageClassification.Cifar10Test(SiaNet.Common.Cifar10Model.ResNet110)[0].Name);
//Object Detection
ObjectDetection.PascalDetection();
//ObjectDetection.GroceryDetection();
Console.ReadLine();
}
catch (Exception ex)
{
Console.WriteLine(ex.ToString());
Console.ReadLine();
}
}
static void Main(string[] args)
{
var templates = new List <Mat>();
AppDomain domain = Startup();
ObjectDetection detector = new ObjectDetection();
var img_path = Path.Combine(SolutionDir.ToString(), Data.Constants.filename_bot + ".jpg");
var img = CvInvoke.Imread(img_path, ImreadModes.AnyColor);
templates = detector.Load_tempaltes(SolutionDir.ToString());
detector.Init_detection(0.96);
detector.Match_templates(img, templates);
}
private async void Page_Loaded(object sender, RoutedEventArgs e)
{
StorageFile modelFile =
await StorageFile.GetFileFromApplicationUriAsync(
new Uri("ms-appx:///Assets/model.onnx"));
string labelsString =
await File.ReadAllTextAsync("Assets/labels.txt");
var labels = labelsString.Split("\r\n");
model = new ObjectDetection(labels);
await model.Init(modelFile);
}
async void Start()
{
try
{
// Get components
_user = GetComponent <UserInput>();
// Load model
StatusBlock.text = $"Loading ONNX ...";
#if ENABLE_WINMD_SUPPORT
_file = await Package.Current.InstalledLocation.GetFileAsync("model.onnx");
_dnnModel = new ObjectDetection(new[] { "Arc Mouse", "Surface Book", "Surface Pro" });
await _dnnModel.Init(_file);
StatusBlock.text = $"Loaded model. Starting camera...";
// Configure camera to return frames fitting the model input size
_mediaCapturer = new MediaCapturer();
await _mediaCapturer.StartCapturing(416, 416);
StatusBlock.text = $"Camera started. Running!";
// Run processing loop in separate parallel Task
_isRunning = true;
await Task.Run(async() =>
{
while (_isRunning)
{
using (var videoFrame = _mediaCapturer.GetLatestFrame())
{
if (videoFrame != null)
{
await EvaluateFrame(videoFrame);
}
}
}
});
#endif
}
catch (Exception ex)
{
#if ENABLE_WINMD_SUPPORT
string filename = _file != null ? _file.Name : "nofile";
StatusBlock.text = $"File: {filename}, Error init: {ex.Message}";
#endif
Debug.LogError(ex);
}
}
public async Task LoadModelAsync(string modelName = "", int maxDetections = 20, float probabilityThreshold = 0.1f, float iouThreshold = 0.45f)
{
if (maxDetections > 0 && maxDetections <= 20)
{
this.maxDetections = maxDetections;
}
if (probabilityThreshold > 0 && probabilityThreshold <= 1)
{
this.probabilityThreshold = probabilityThreshold;
}
if (iouThreshold > 0 && iouThreshold <= 1)
{
this.iouThreshold = iouThreshold;
}
if (!string.IsNullOrWhiteSpace(modelName))
{
ModelFilename = modelName;
}
ModifyText($"Loading {ModelFilename}...");
#if UNITY_WSA && !UNITY_EDITOR
try
{
TimeRecorder = Stopwatch.StartNew();
var modelFile = await StorageFile.GetFileFromApplicationUriAsync(new Uri($"ms-appx:///Data/StreamingAssets/{ModelFilename}"));
var labelFile = await StorageFile.GetFileFromApplicationUriAsync(new Uri($"ms-appx:///Data/StreamingAssets/labels.txt"));
var labels = await FileIO.ReadLinesAsync(labelFile);
Model = new ObjectDetection(labels, maxDetections, probabilityThreshold, iouThreshold);
await Model.InitAsync(modelFile);
TimeRecorder.Stop();
ModifyText($"Loaded {ModelFilename} in {TimeRecorder.ElapsedMilliseconds}ms");
}
catch (Exception ex)
{
ModifyText($"Error: {ex.Message}");
Model = null;
}
#endif
}
// Use this for initialization
void Start()
{
#if UNITY_UWP
Task.Run(async() =>
{
var modelFile = await
StorageFile.GetFileFromApplicationUriAsync(
new Uri("ms-appx:///Assets/LearningModel.onnx"));
_objectDetection = new ObjectDetection(new List <string>(new[] { "AngelPie", "ChocoPie" }), 20, .3f, .45f);
await _objectDetection.Init(modelFile);
IsReady = true;
});
#endif
}
// Use this for initialization
void Start()
{
#if UNITY_UWP
Task.Run(async() =>
{
var modelFile = await
StorageFile.GetFileFromApplicationUriAsync(
new Uri("ms-appx:///Assets/LearningModel.onnx"));
//学習させた内容に合わせてタグは適宜変更する
_objectDetection = new ObjectDetection(new List <string>(new[] { "curry", "gyoza", "meat", "pizza", "sushi" }), 20, .3f, .45f);
await _objectDetection.Init(modelFile);
IsReady = true;
});
#endif
}
private async Task LoadCurrentModelAsync(CustomVisionModelData currentProject)
{
try
{
this.deleteBtn.Visibility = currentProject.IsPrebuiltModel ? Visibility.Collapsed : Visibility.Visible;
LoadSupportedClasses(currentProject);
StorageFile modelFile = await GetModelFileAsync(currentProject);
this.objectDetectionModel = new ObjectDetection(this.allModelObjects, probabilityThreshold: MinProbabilityValue);
await this.objectDetectionModel.Init(modelFile);
}
catch (Exception ex)
{
await Util.GenericApiCallExceptionHandler(ex, "Failure loading current project");
}
}
private void ProcessImage()
{
switch (currentStep)
{
case 0:
this.Text = "GrayValue";
this.image = new Image(InputImage);
break;
case 1:
this.Text = "Smoothing";
image.Apply(Operation.Operations.Smoothing);
break;
case 2:
this.Text = "Edges + subtraction";
Image temp = new Image(image.GetPixels(), image.Size);
image.Apply(Operation.Operations.Edges);
//image = Addition.Apply(image, temp);
image = new Image(image.GetPixels(), image.Size);
image = Minval.Apply(image, temp);
break;
case 3:
<< << << < HEAD
this.Text = "Opening";
image.Apply(Operation.Operations.Opening);
break;
case 4:
this.Text = "Closing";
image.Apply(Operation.Operations.Closing);
break;
case 5:
this.Text = "Colouring";
ObjectDetection od = new ObjectDetection(image);
od.Apply();
ObjectFiltering of = new ObjectFiltering(od.objects);
of.Apply();
image = new Coloring(of.coffeeMugObjectList).ConstructNewImage(image.Size);
== == == =
this.Text = "Negative Threshold";
image.Apply(Operation.Operations.NegativeThreshold);
private async void Instance_SDKRegistrationStateChanged(SDKRegistrationState state, SDKError errorCode)
{
var isReg = state == SDKRegistrationState.Succeeded && errorCode == SDKError.NO_ERROR;
if (_isRunning)
{
return;
}
if (isReg)
{
List <String> labels = new List <String> {
"Box", "Nobox"
};
objectDetection = new ObjectDetection(labels, 10, 0.45F, 0.45F);
await init_onnx();
var gimbal = await DJISDKManager.Instance.ComponentManager.GetGimbalHandler(0, 0).GetGimbalAttitudeAsync();
if (gimbal.value == null || gimbal.value.Value.pitch == 0)
{
//for (; ; )
//{
var err0r1 = DJISDKManager.Instance.ComponentManager.GetGimbalHandler(0, 0).RotateByAngleAsync(new GimbalAngleRotation
{
mode = GimbalAngleRotationMode.ABSOLUTE_ANGLE,
pitch = -16.9,
roll = 0,
yaw = 0,
pitchIgnored = false,
rollIgnored = true,
yawIgnored = true,
duration = 1.0
});
// if (err0r1.Result == SDKError.NO_ERROR)
// {
// break;
// }
//}
}
_isRunning = true;
Thread.Sleep(2000);
workerThread.Start();
}
}
private async void Page_Loaded(object sender, RoutedEventArgs e)
{
var maximumObjects = 5; //maximum number of Objects that can be detected
StorageFile labelsFile =
await StorageFile.GetFileFromApplicationUriAsync(
new Uri("ms-appx:///Assets/labels.txt"));
IList <string> data = await FileIO.ReadLinesAsync(labelsFile);
List <string> labelsList = data.ToList();
od = new ObjectDetection(labelsList, maximumObjects);
StorageFile modelFile =
await StorageFile.GetFileFromApplicationUriAsync(
new Uri("ms-appx:///Assets/model.onnx"));
await od.Init(modelFile);
}
/// <summary>
/// Main function.
/// </summary>
/// <param name="args"><c>--clientSecret</c> and <c>--clientId</c> are required arguments, <c>--baseUrl</c> is optional.</param>
private static void Main(string[] args)
{
string clientSecret, clientId, baseUrl;
ProcessArguments(args, out clientSecret, out clientId, out baseUrl);
try
{
var api = new ImagingApi(clientSecret, clientId, baseUrl);
PrepareOutput();
Console.WriteLine("Running Imaging Cloud examples:");
Console.WriteLine();
// Update parameters of existing BMP image
var bmpImage = new UpdateBmpImage(api);
bmpImage.ModifyBmpFromStorage();
bmpImage.ModifyBmpAndUploadToStorage();
bmpImage.CreateModifiedBmpFromRequestBody();
// Crop an existing image
var cropImage = new CropImage(api);
cropImage.CropImageFromStorage();
cropImage.CropImageAndUploadToStorage();
cropImage.CreateCroppedImageFromRequestBody();
// Deskew an existing image
var deskewImage = new DeskewImage(api);
deskewImage.DeskewImageFromStorage();
deskewImage.DeskewImageAndUploadToStorage();
deskewImage.CreateDeskewedImageFromRequestBody();
// grayscale an existing image
var grayscaleImage = new GrayscaleImage(api);
grayscaleImage.GrayscaleImageFromStorage();
grayscaleImage.GrayscaleImageAndUploadToStorage();
grayscaleImage.CreateGrayscaledImageFromRequestBody();
// Process existing EMF imaging using given parameters
var updateEmfImage = new UpdateEmfImage(api);
updateEmfImage.ModifyEmfFromStorage();
updateEmfImage.ModifyEmfAndUploadToStorage();
updateEmfImage.CreateModifiedEmfFromRequestBody();
// Export existing image to another format
var exportImage = new ExportImage(api);
exportImage.SaveImageAsFromStorage();
exportImage.SaveImageAsAndUploadToStorage();
exportImage.CreateSavedImageAsFromRequestBody();
// Apply a filtering effect to an image
var filterImage = new FilterImage(api);
filterImage.FilterImageFromStorage();
filterImage.FilterImageAndUploadToStorage();
// Get properties of an image
var imageProperties = new ImageProperties(api);
imageProperties.GetImagePropertiesFromStorage();
imageProperties.ExtractImagePropertiesFromRequestBody();
// Resize an existing image
var resizeImage = new ResizeImage(api);
resizeImage.ResizeImageFromStorage();
resizeImage.ResizeImageAndUploadToStorage();
resizeImage.CreateResizedImageFromRequestBody();
// Rotate and/or flip an existing image
var rotateFlipImage = new RotateFlipImage(api);
rotateFlipImage.RotateFlipImageFromStorage();
rotateFlipImage.RotateFlipImageAndUploadToStorage();
rotateFlipImage.CreateRotateFlippedImageFromRequestBody();
// TIFF Frames
var multiframeImage = new MultiframeImage(api);
multiframeImage.GetImageFrameFromStorage();
multiframeImage.GetImageFrameAndUploadToStorage();
multiframeImage.CreateImageFrameFromRequestBody();
multiframeImage.GetImageFrameRangeFromStorage();
multiframeImage.GetImageFrameRangeAndUploadToStorage();
multiframeImage.CreateImageFrameRangeFromRequestBody();
multiframeImage.GetImageFramePropertiesFromStorage();
multiframeImage.ExtractImageFramePropertiesFromRequestBody();
// Update parameters of existing TIFF image
var tiffImage = new TiffImage(api);
tiffImage.ModifyTiffFromStorage();
tiffImage.ModifyTiffAndUploadToStorage();
tiffImage.CreateModifiedTiffFromRequestBody();
tiffImage.ConvertTiffToFaxFromStorage();
tiffImage.AppendTiffFromStorage();
// Update parameters of existing GIF image
var updateGifImage = new UpdateGifImage(api);
updateGifImage.ModifyGifFromStorage();
updateGifImage.ModifyGifAndUploadToStorage();
updateGifImage.CreateModifiedGifFromRequestBody();
// Perform scaling, cropping and flipping of an existing image in a single request
var updateImage = new UpdateImage(api);
updateImage.UpdateImageFromStorage();
updateImage.UpdateImageAndUploadToStorage();
updateImage.CreateUpdatedImageFromRequestBody();
// Update parameters of existing JPEG2000 image
var updateJpeg2000Image = new UpdateJpeg2000Image(api);
updateJpeg2000Image.ModifyJpeg2000FromStorage();
updateJpeg2000Image.ModifyJpeg2000AndUploadToStorage();
updateJpeg2000Image.CreateModifiedJpeg2000FromRequestBody();
// Update parameters of existing JPEG image
var updateJpegImage = new UpdateJpegImage(api);
updateJpegImage.ModifyJpegFromStorage();
updateJpegImage.ModifyJpegAndUploadToStorage();
updateJpegImage.CreateModifiedJpegFromRequestBody();
// Update parameters of existing PSD image
var updatePsdImage = new UpdatePsdImage(api);
updatePsdImage.ModifyPsdFromStorage();
updatePsdImage.ModifyPsdAndUploadToStorage();
updatePsdImage.CreateModifiedPsdFromRequestBody();
// Update parameters of existing WEBP image
var webpImage = new UpdateWebPImage(api);
webpImage.ModifyWebPFromStorage();
webpImage.ModifyWebPAndUploadToStorage();
webpImage.CreateModifiedWebPFromRequestBody();
// Process existing WMF image using given parameters
var wmfImage = new UpdateWmfImage(api);
wmfImage.ModifyWmfFromStorage();
wmfImage.ModifyWmfAndUploadToStorage();
wmfImage.CreateModifiedWmfFromRequestBody();
// AI APIs
Console.WriteLine("Running AI examples:");
Console.WriteLine();
// Compare two images
var compareImages = new CompareImages(api);
compareImages.PrepareSearchContext();
compareImages.CompareTwoImagesInCloud();
compareImages.CompareLoadedImageToImageInCloud();
compareImages.DeleteSearchContext();
// Find Duplicate Images
var findDuplicateImages = new FindDuplicateImages(api);
findDuplicateImages.PrepareSearchContext();
findDuplicateImages.FindImageDuplicates();
findDuplicateImages.DeleteSearchContext();
// Find Similar Images
var findImages = new FindSimilarImages(api);
findImages.PrepareSearchContext();
findImages.FindImagesSimilar();
findImages.FindImagesByTag();
findImages.SearchImageFromWebSource();
findImages.DeleteSearchContext();
//object detection
var objectDetection = new ObjectDetection(api);
objectDetection.DetectObjectsImageFromStorage();
objectDetection.DetectedObjectsImageFromRequestBody();
objectDetection.VisualiizeDetectObjectsAndUploadToStorage();
objectDetection.VisualizeDetectedObjectsImageFromRequestBody();
// custom fonts
var customFonts = new LoadCustomFonts(api);
customFonts.UsingCustomFontsForVectorImageConversion();
}
catch (Exception ex)
{
Console.WriteLine($"Something goes wrong: {ex}");
Environment.Exit(1);
}
Environment.Exit(0);
}
static void Main(string[] args)
{
ObjectDetection objectDetection = new ObjectDetection("assets/images", "assets/images/output");
objectDetection.Detect();
}
private async void InitModel()
{
_objectDetection = new ObjectDetection();
await _objectDetection.Init();
}
public async Task SendAndSaveNotifications(IEnumerable <UplinkMessage> uplinkMessageEnumerable)
{
List <UplinkMessage> uplinkMessages = uplinkMessageEnumerable.ToList();
List <Notification> notifications = uplinkMessages.Select(async uplinkMessage =>
{
NotificationType notificationType;
ObjectDetectionNotification objectDetectionNotification = null;
if (uplinkMessage.Data.Length == 0)
{
notificationType = NotificationType.Heartbeat;
}
else
{
notificationType = NotificationType.ObjectDetection;
ushort?widthCentimeters = ushort.Parse(uplinkMessage.Data, NumberStyles.HexNumber);
ObjectDetection objectDetection = widthCentimeters switch
{
0 => ObjectDetection.Removed,
ushort.MaxValue => ObjectDetection.Detected,
_ => ObjectDetection.DetectedWithSize
};
if (objectDetection != ObjectDetection.DetectedWithSize)
{
widthCentimeters = null;
}
objectDetectionNotification = new ObjectDetectionNotification
{
ObjectDetection = objectDetection,
WidthCentimeters = widthCentimeters,
SentToKommune = false
};
}
string address = (await _storage.GetDevice(uplinkMessage.DeviceEui))?.Address ?? "";
return(new Notification
{
Address = address,
Timestamp = uplinkMessage.Timestamp,
Type = notificationType,
DeviceEui = uplinkMessage.DeviceEui,
ObjectDetectionNotification = objectDetectionNotification
});
})
.Select(task => task.Result)
.ToList();
_logger.LogInformation("Saving notifications: " + JsonSerializer.Serialize(notifications));
await _storage.AddNotifications(notifications);
List <NotificationToKommune> notificationsToKommune = DetectionSystemServiceUtil.NotificationsToKommuneNotifications(notifications);
try
{
await _kommuneService.SendNotifications(notificationsToKommune);
foreach (Notification notification in notifications)
{
notification.ObjectDetectionNotification.SentToKommune = true;
}
}
catch (Exception e)
{
_logger.LogWarning("Kommune communication exception", e);
foreach (Notification notification in notifications)
{
notification.ObjectDetectionNotification.SentToKommune = false;
}
}
}
void Start()
{
playerCam = Camera.main.GetComponent <ThirdPersonCamera>();
playerMove = GetComponent <PlayerMove>();
objectDetection = GetComponent <ObjectDetection>();
}
void Start()
{
characterController = GetComponent <CharacterController>();
objectDetection = GetComponent <ObjectDetection>();
holder = GetComponent <Holder>();
}
