ImageEstimatorsCatalog.ResizeImages Methode

Definition

Namespace:

Microsoft.ML

Assembly:

Microsoft.ML.ImageAnalytics.dll

Paket:

Microsoft.ML.ImageAnalytics v3.0.1

Erstellen Sie einen ImageResizingEstimator, der die Größe des Bilds von der in angegebenen Spalte in inputColumnName eine neue Spalte ändert: outputColumnName.

public static Microsoft.ML.Transforms.Image.ImageResizingEstimator ResizeImages (this Microsoft.ML.TransformsCatalog catalog, string outputColumnName, int imageWidth, int imageHeight, string inputColumnName = default, Microsoft.ML.Transforms.Image.ImageResizingEstimator.ResizingKind resizing = Microsoft.ML.Transforms.Image.ImageResizingEstimator+ResizingKind.IsoCrop, Microsoft.ML.Transforms.Image.ImageResizingEstimator.Anchor cropAnchor = Microsoft.ML.Transforms.Image.ImageResizingEstimator+Anchor.Center);

static member ResizeImages : Microsoft.ML.TransformsCatalog * string * int * int * string * Microsoft.ML.Transforms.Image.ImageResizingEstimator.ResizingKind * Microsoft.ML.Transforms.Image.ImageResizingEstimator.Anchor -> Microsoft.ML.Transforms.Image.ImageResizingEstimator

<Extension()>
Public Function ResizeImages (catalog As TransformsCatalog, outputColumnName As String, imageWidth As Integer, imageHeight As Integer, Optional inputColumnName As String = Nothing, Optional resizing As ImageResizingEstimator.ResizingKind = Microsoft.ML.Transforms.Image.ImageResizingEstimator+ResizingKind.IsoCrop, Optional cropAnchor As ImageResizingEstimator.Anchor = Microsoft.ML.Transforms.Image.ImageResizingEstimator+Anchor.Center) As ImageResizingEstimator

Parameter

catalog

TransformsCatalog

Der Katalog der Transformation.

outputColumnName

String

Der Name der Spalte, die sich aus der Transformation von inputColumnNameergibt. Der Datentyp dieser Spalte entspricht dem Datentyp der Eingabespalte.

imageWidth

Int32

Die breite des transformierten Bilds.

imageHeight

Int32

Die transformierte Bildhöhe.

inputColumnName

String

Name der Spalte mit Bildern. Dieser Schätzer arbeitet über MLImage.

resizing

ImageResizingEstimator.ResizingKind

Der Typ der Bildgröße, wie in ImageResizingEstimator.ResizingKindangegeben.

cropAnchor

ImageResizingEstimator.Anchor

Wo der Anker platziert werden soll, um mit dem Zuschneiden zu beginnen. In definierte Optionen ImageResizingEstimator.Anchor

Gibt zurück

ImageResizingEstimator

Beispiele

using System;
using System.IO;
using Microsoft.ML;
using Microsoft.ML.Data;

namespace Samples.Dynamic
{
    public static class ResizeImages
    {
        // Example on how to load the images from the file system, and resize them.
        public static void Example()
        {
            // Create a new ML context, for ML.NET operations. It can be used for
            // exception tracking and logging, as well as the source of randomness.
            var mlContext = new MLContext();

            // Downloading a few images, and an images.tsv file, which contains a
            // list of the files from the dotnet/machinelearning/test/data/images/.
            // If you inspect the fileSystem, after running this line, an "images"
            // folder will be created, containing 4 images, and a .tsv file
            // enumerating the images.
            var imagesDataFile = Microsoft.ML.SamplesUtils.DatasetUtils
                .GetSampleImages();

            // Preview of the content of the images.tsv file
            //
            // imagePath    imageType
            // tomato.bmp   tomato
            // banana.jpg   banana
            // hotdog.jpg   hotdog
            // tomato.jpg   tomato

            var data = mlContext.Data.CreateTextLoader(new TextLoader.Options()
            {
                Columns = new[]
                {
                        new TextLoader.Column("ImagePath", DataKind.String, 0),
                        new TextLoader.Column("Name", DataKind.String, 1),
                }
            }).Load(imagesDataFile);

            var imagesFolder = Path.GetDirectoryName(imagesDataFile);
            // Image loading pipeline.
            var pipeline = mlContext.Transforms.LoadImages("ImageObject",
                imagesFolder, "ImagePath")
                .Append(mlContext.Transforms.ResizeImages("ImageObjectResized",
                inputColumnName: "ImageObject", imageWidth: 100, imageHeight: 100));

            var transformedData = pipeline.Fit(data).Transform(data);
            // The transformedData IDataView contains the resized images now.

            // Preview the transformedData.
            PrintColumns(transformedData);

            // ImagePath    Name         ImageObject               ImageObjectResized
            // tomato.bmp   tomato       {Width=800, Height=534}   {Width=100, Height=100}
            // banana.jpg   banana       {Width=800, Height=288}   {Width=100, Height=100}
            // hotdog.jpg   hotdog       {Width=800, Height=391}   {Width=100, Height=100}
            // tomato.jpg   tomato       {Width=800, Height=534}   {Width=100, Height=100}
        }

        private static void PrintColumns(IDataView transformedData)
        {
            Console.WriteLine("{0, -25} {1, -25} {2, -25} {3, -25}", "ImagePath",
                "Name", "ImageObject", "ImageObjectResized");

            using (var cursor = transformedData.GetRowCursor(transformedData
                .Schema))
            {
                // Note that it is best to get the getters and values *before*
                // iteration, so as to facilitate buffer sharing (if applicable), and
                // column -type validation once, rather than many times.
                ReadOnlyMemory<char> imagePath = default;
                ReadOnlyMemory<char> name = default;
                MLImage imageObject = null;
                MLImage resizedImageObject = null;

                var imagePathGetter = cursor.GetGetter<ReadOnlyMemory<char>>(cursor
                    .Schema["ImagePath"]);

                var nameGetter = cursor.GetGetter<ReadOnlyMemory<char>>(cursor
                    .Schema["Name"]);

                var imageObjectGetter = cursor.GetGetter<MLImage>(cursor.Schema[
                    "ImageObject"]);

                var resizedImageGetter = cursor.GetGetter<MLImage>(cursor.Schema[
                    "ImageObjectResized"]);

                while (cursor.MoveNext())
                {
                    imagePathGetter(ref imagePath);
                    nameGetter(ref name);
                    imageObjectGetter(ref imageObject);
                    resizedImageGetter(ref resizedImageObject);

                    Console.WriteLine("{0, -25} {1, -25} {2, -25} {3, -25}",
                        imagePath, name,
                        $"Width={imageObject.Width}, Height={imageObject.Height}",
                        $"Width={resizedImageObject.Width}, Height={resizedImageObject.Height}");
                }

                // Dispose the image.
                imageObject.Dispose();
                resizedImageObject.Dispose();
            }
        }
    }
}