8000 Update samples to .NET 6 (#932) · dotnet/machinelearning-samples@fa027d3 · GitHub
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jwood803jwood803
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Update samples to .NET 6 (#932)
* Update bike rental sample to .NET 6 * Update object detection sample to .NET 6
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‎samples/csharp/getting-started/DeepLearning_ObjectDetection_Onnx/ObjectDetectionConsoleApp/ObjectDetection.csproj

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Original file line numberDiff line numberDiff line change
@@ -2,7 +2,8 @@
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<PropertyGroup>
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<OutputType>Exe</OutputType>
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<TargetFramework>net5</TargetFramework>
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<TargetFramework>net6.0</TargetFramework>
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<ImplicitUsings>enable</ImplicitUsings>
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</PropertyGroup>
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<ItemGroup>

‎samples/csharp/getting-started/DeepLearning_ObjectDetection_Onnx/ObjectDetectionConsoleApp/Program.cs

Lines changed: 113 additions & 129 deletions
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@@ -1,148 +1,132 @@
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using System;
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using System.IO;
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using System.Collections.Generic;
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using System.Drawing;
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using System.Drawing;
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using System.Drawing.Drawing2D;
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using System.Linq;
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using Microsoft.ML;
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using ObjectDetection.YoloParser;
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using ObjectDetection.DataStructures;
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using ObjectDetection;
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using Microsoft.ML;
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var assetsRelativePath = @"../../../assets";
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string assetsPath = GetAbsolutePath(assetsRelativePath);
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var modelFilePath = Path.Combine(assetsPath, "Model", "TinyYolo2_model.onnx");
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var imagesFolder = Path.Combine(assetsPath, "images");
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var outputFolder = Path.Combine(assetsPath, "images", "output");
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namespace ObjectDetection
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// Initialize MLContext
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MLContext mlContext = new MLContext();
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try
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{
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class Program
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// Load Data
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IEnumerable<ImageNetData> images = ImageNetData.ReadFromFile(imagesFolder);
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IDataView imageDataView = mlContext.Data.LoadFromEnumerable(images);
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// Create instance of model scorer
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var modelScorer = new OnnxModelScorer(imagesFolder, modelFilePath, mlContext);
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// Use model to score data
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IEnumerable<float[]> probabilities = modelScorer.Score(imageDataView);
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// Post-process model output
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YoloOutputParser parser = new YoloOutputParser();
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var boundingBoxes =
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probabilities
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.Select(probability => parser.ParseOutputs(probability))
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.Select(boxes => parser.FilterBoundingBoxes(boxes, 5, .5F));
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// Draw bounding boxes for detected objects in each of the images
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for (var i = 0; i < images.Count(); i++)
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{
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public static void Main()
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{
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var assetsRelativePath = @"../../../assets";
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string assetsPath = GetAbsolutePath(assetsRelativePath);
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var modelFilePath = Path.Combine(assetsPath, "Model", "TinyYolo2_model.onnx");
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var imagesFolder = Path.Combine(assetsPath, "images");
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var outputFolder = Path.Combine(assetsPath, "images", "output");
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// Initialize MLContext
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MLContext mlContext = new MLContext();
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try
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{
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// Load Data
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IEnumerable<ImageNetData> images = ImageNetData.ReadFromFile(imagesFolder);
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IDataView imageDataView = mlContext.Data.LoadFromEnumerable(images);
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// Create instance of model scorer
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var modelScorer = new OnnxModelScorer(imagesFolder, modelFilePath, mlContext);
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// Use model to score data
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IEnumerable<float[]> probabilities = modelScorer.Score(imageDataView);
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// Post-process model output
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YoloOutputParser parser = new YoloOutputParser();
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var boundingBoxes =
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probabilities
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.Select(probability => parser.ParseOutputs(probability))
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.Select(boxes => parser.FilterBoundingBoxes(boxes, 5, .5F));
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// Draw bounding boxes for detected objects in each of the images
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for (var i = 0; i < images.Count(); i++)
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{
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string imageFileName = images.ElementAt(i).Label;
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IList<YoloBoundingBox> detectedObjects = boundingBoxes.ElementAt(i);
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DrawBoundingBox(imagesFolder, outputFolder, imageFileName, detectedObjects);
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LogDetectedObjects(imageFileName, detectedObjects);
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}
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}
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catch (Exception ex)
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{
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Console.WriteLine(ex.ToString());
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}
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Console.WriteLine("========= End of Process..Hit any Key ========");
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Console.ReadLine();
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}
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string imageFileName = images.ElementAt(i).Label;
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IList<YoloBoundingBox> detectedObjects = boundingBoxes.ElementAt(i);
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66-
public static string GetAbsolutePath(string relativePath)
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{
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FileInfo _dataRoot = new FileInfo(typeof(Program).Assembly.Location);
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string assemblyFolderPath = _dataRoot.Directory.FullName;
43+
DrawBoundingBox(imagesFolder, outputFolder, imageFileName, detectedObjects);
7044

71-
string fullPath = Path.Combine(assemblyFolderPath, relativePath);
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LogDetectedObjects(imageFileName, detectedObjects);
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}
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}
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catch (Exception ex)
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{
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Console.WriteLine(ex.ToString());
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}
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73-
return fullPath;
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}
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Console.WriteLine("========= End of Process..Hit any Key ========");
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76-
private static void DrawBoundingBox(string inputImageLocation, string outputImageLocation, string imageName, IList<YoloBoundingBox> filteredBoundingBoxes)
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{
78-
Image image = Image.FromFile(Path.Combine(inputImageLocation, imageName));
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var originalImageHeight = image.Height;
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var originalImageWidth = image.Width;
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foreach (var box in filteredBoundingBoxes)
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{
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// Get Bounding Box Dimensions
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var x = (uint)Math.Max(box.Dimensions.X, 0);
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var y = (uint)Math.Max(box.Dimensions.Y, 0);
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var width = (uint)Math.Min(originalImageWidth - x, box.Dimensions.Width);
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var height = (uint)Math.Min(originalImageHeight - y, box.Dimensions.Height);
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// Resize To Image
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x = (uint)originalImageWidth * x / OnnxModelScorer.ImageNetSettings.imageWidth;
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y = (uint)originalImageHeight * y / OnnxModelScorer.ImageNetSettings.imageHeight;
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width = (uint)originalImageWidth * width / OnnxModelScorer.ImageNetSettings.imageWidth;
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< F987 span class=pl-s1>height = (uint)originalImageHeight * height / OnnxModelScorer.ImageNetSettings.imageHeight;
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// Bounding Box Text
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string text = $"{box.Label} ({(box.Confidence * 100).ToString("0")}%)";
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using (Graphics thumbnailGraphic = Graphics.FromImage(image))
101-
{
102-
thumbnailGraphic.CompositingQuality = CompositingQuality.HighQuality;
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thumbnailGraphic.SmoothingMode = SmoothingMode.HighQuality;
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thumbnailGraphic.InterpolationMode = InterpolationMode.HighQualityBicubic;
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// Define Text Options
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Font drawFont = new Font("Arial", 12, FontStyle.Bold);
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SizeF size = thumbnailGraphic.MeasureString(text, drawFont);
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SolidBrush fontBrush = new SolidBrush(Color.Black);
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Point atPoint = new Point((int)x, (int)y - (int)size.Height - 1);
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// Define BoundingBox options
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Pen pen = new Pen(box.BoxColor, 3.2f);
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SolidBrush colorBrush = new SolidBrush(box.BoxColor);
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// Draw text on image
117-
thumbnailGraphic.FillRectangle(colorBrush, (int)x, (int)(y - size.Height - 1), (int)size.Width, (int)size.Height);
118-
thumbnailGraphic.DrawString(text, drawFont, fontBrush, atPoint);
119-
120-
// Draw bounding box on image
121-
thumbnailGraphic.DrawRectangle(pen, x, y, width, height);
122-
}
123-
}
124-
125-
if (!Directory.Exists(outputImageLocation))
126-
{
127-
Directory.CreateDirectory(outputImageLocation);
128-
}
129-
130-
image.Save(Path.Combine(outputImageLocation, imageName));
131-
}
55+
string GetAbsolutePath(string relativePath)
56+
{
57+
FileInfo _dataRoot = new FileInfo(typeof(Program).Assembly.Location);
58+
string assemblyFolderPath = _dataRoot.Directory.FullName;
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133-
private static void LogDetectedObjects(string imageName, IList<YoloBoundingBox> boundingBoxes)
134-
{
135-
Console.WriteLine($".....The objects in the image {imageName} are detected as below....");
60+
string fullPath = Path.Combine(assemblyFolderPath, relativePath);
13661

137-
foreach (var box in boundingBoxes)
138-
{
139-
Console.WriteLine($"{box.Label} and its Confidence score: {box.Confidence}");
140-
}
62+
return fullPath;
63+
}
14164

142-
Console.WriteLine("");
65+
void DrawBoundingBox(string inputImageLocation, string outputImageLocation, string imageName, IList<YoloBoundingBox> filteredBoundingBoxes)
66+
{
67+
Image image = Image.FromFile(Path.Combine(inputImageLocation, imageName));
68+
69+
var originalImageHeight = image.Height;
70+
var originalImageWidth = image.Width;
71+
72+
foreach (var box in filteredBoundingBoxes)
73+
{
74+
// Get Bounding Box Dimensions
75+
var x = (uint)Math.Max(box.Dimensions.X, 0);
76+
var y = (uint)Math.Max(box.Dimensions.Y, 0);
77+
var width = (uint)Math.Min(originalImageWidth - x, box.Dimensions.Width);
78+
var height = (uint)Math.Min(originalImageHeight - y, box.Dimensions.Height);
79+
80+
// Resize To Image
81+
x = (uint)originalImageWidth * x / OnnxModelScorer.ImageNetSettings.imageWidth;
82+
y = (uint)originalImageHeight * y / OnnxModelScorer.ImageNetSettings.imageHeight;
83+
width = (uint)originalImageWidth * width / OnnxModelScorer.ImageNetSettings.imageWidth;
84+
height = (uint)originalImageHeight * height / OnnxModelScorer.ImageNetSettings.imageHeight;
85+
86+
// Bounding Box Text
87+
string text = $"{box.Label} ({(box.Confidence * 100).ToString("0")}%)";
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89+
using (Graphics thumbnailGraphic = Graphics.FromImage(image))
90+
{
91+
thumbnailGraphic.CompositingQuality = CompositingQuality.HighQuality;
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thumbnailGraphic.SmoothingMode = SmoothingMode.HighQuality;
93+
thumbnailGraphic.InterpolationMode = InterpolationMode.HighQualityBicubic;
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// Define Text Options
96+
Font drawFont = new Font("Arial", 12, FontStyle.Bold);
97+
SizeF size = thumbnailGraphic.MeasureString(text, drawFont);
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SolidBrush fontBrush = new SolidBrush(Color.Black);
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Point atPoint = new Point((int)x, (int)y - (int)size.Height - 1);
100+
101+
// Define BoundingBox options
102+
Pen pen = new Pen(box.BoxColor, 3.2f);
103+
SolidBrush colorBrush = new SolidBrush(box.BoxColor);
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// Draw text on image
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thumbnailGraphic.FillRectangle(colorBrush, (int)x, (int)(y - size.Height - 1), (int)size.Width, (int)size.Height);
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thumbnailGraphic.DrawString(text, drawFont, fontBrush, atPoint);
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// Draw bounding box on image
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thumbnailGraphic.DrawRectangle(pen, x, y, width, height);
143111
}
144112
}
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114+
if (!Directory.Exists(outputImageLocation))
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{
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Directory.CreateDirectory(outputImageLocation);
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}
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119+
image.Save(Path.Combine(outputImageLocation, imageName));
145120
}
146121

122+
void LogDetectedObjects(string imageName, IList<YoloBoundingBox> boundingBoxes)
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{
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Console.WriteLine($".....The objects in the image {imageName} are detected as below....");
147125

126+
foreach (var box in boundingBoxes)
127+
{
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Console.WriteLine($"{box.Label} and its Confidence score: {box.Confidence}");
129+
}
148130

131+
Console.WriteLine("");
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}

‎samples/csharp/getting-started/Forecasting_BikeSharingDemand/BikeDemandForecasting/BikeDemandForecasting.csproj

Lines changed: 2 additions & 1 deletion
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<PropertyGroup>
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<OutputType>Exe</OutputType>
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<TargetFramework>net5</TargetFramework>
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<TargetFramework>net6.0</TargetFramework>
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<ImplicitUsings>enable</ImplicitUsings>
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</PropertyGroup>
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<ItemGroup>

‎samples/csharp/getting-started/Forecasting_BikeSharingDemand/BikeDemandForecasting/Data/DailyDemand.mdf

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