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Update fasterrcnn_csharp.md (#11513)

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adapted according to https://github.com/microsoft/onnxruntime/pull/11420
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andife 2022-06-06 22:28:32 +02:00 committed by GitHub
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19
docs/tutorials/fasterrcnn_csharp.md
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@ -67,16 +67,19 @@ var paddedHeight = (int)(Math.Ceiling(image.Height / 32f) * 32f);
var paddedWidth = (int)(Math.Ceiling(image.Width / 32f) * 32f);
Tensor<float> input = new DenseTensor<float>(new[] { 3, paddedHeight, paddedWidth });
var mean = new[] { 102.9801f, 115.9465f, 122.7717f };
for (int y = paddedHeight - image.Height; y < image.Height; y++)
image.ProcessPixelRows(accessor =>
{
Span<Rgb24> pixelSpan = image.GetPixelRowSpan(y);
for (int x = paddedWidth - image.Width; x < image.Width; x++)
for (int y = paddedHeight - accessor.Height; y < accessor.Height; y++)
{
input[0, y, x] = pixelSpan[x].B - mean[0];
input[1, y, x] = pixelSpan[x].G - mean[1];
input[2, y, x] = pixelSpan[x].R - mean[2];
Span<Rgb24> pixelSpan = accessor.GetRowSpan(y);
for (int x = paddedWidth - accessor.Width; x < accessor.Width; x++)
{
input[0, y, x] = pixelSpan[x].B - mean[0];
input[1, y, x] = pixelSpan[x].G - mean[1];
input[2, y, x] = pixelSpan[x].R - mean[2];
}
}
}
});
```
Here, we're creating a Tensor of the required size `(channels, paddedHeight, paddedWidth)`, accessing the pixel values, preprocessing them and finally assigning them to the tensor at the appropriate indicies.
@ -180,4 +183,4 @@ dotnet run ~/Downloads/FasterRCNN-10.onnx ~/Downloads/demo.jpg ~/Downloads/out.j
detects the following objects in the image:
![](/images/out.jpg)
![](/images/out.jpg)