ImageEstimatorsCatalog.ResizeImages Méthode

Définition

Espace de noms:

Microsoft.ML

Assembly:

Microsoft.ML.ImageAnalytics.dll

Paquet:

Microsoft.ML.ImageAnalytics v2.0.0

Créez un ImageResizingEstimator, qui redimensionne l’image de la colonne spécifiée dans vers inputColumnName une nouvelle colonne : 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

Paramètres

catalog

TransformsCatalog

Catalogue de la transformation.

outputColumnName

String

Nom de la colonne résultant de la transformation de inputColumnName. Le type de données de cette colonne sera le même que celui de la colonne d’entrée.

imageWidth

Int32

Largeur de l’image transformée.

imageHeight

Int32

Hauteur de l’image transformée.

inputColumnName

String

Nom de la colonne avec des images. Cet estimateur fonctionne sur MLImage.

resizing

ImageResizingEstimator.ResizingKind

Type de redimensionnement d’image spécifié dans ImageResizingEstimator.ResizingKind.

cropAnchor

ImageResizingEstimator.Anchor

Où placer l’ancre pour commencer le rognage. Options définies dans ImageResizingEstimator.Anchor

Retours

ImageResizingEstimator

Exemples

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();
            }
        }
    }
}