Instructivo de ImageMagick

En este instructivo, se muestra cómo usar Cloud Functions, ImageMagick y la API de Google Cloud Vision para detectar y difuminar imágenes ofensivas que se suben a un bucket de Cloud Storage.

Objetivos

  • Implementar una función de Cloud Functions en segundo plano activada por Storage
  • Usar la API de Cloud Vision para detectar contenido violento o destinado para adultos
  • Usar ImageMagick para difuminar imágenes ofensivas
  • Probar la función con solo subir una imagen de un zombi que come carne humana

Costos

En este instructivo, se usan los siguientes componentes facturables de Google Cloud:

  • Cloud Functions
  • Cloud Storage
  • Cloud Vision

Para generar una estimación de costos en función del uso previsto, usa la calculadora de precios. Es posible que los usuarios nuevos de Google Cloud califiquen para obtener una prueba gratuita.

Antes de comenzar

  1. Accede a tu cuenta de Google Cloud. Si eres nuevo en Google Cloud, crea una cuenta para evaluar el rendimiento de nuestros productos en situaciones reales. Los clientes nuevos también obtienen $300 en créditos gratuitos para ejecutar, probar y, además, implementar cargas de trabajo.
  2. En la página del selector de proyectos de Google Cloud Console, selecciona o crea un proyecto de Google Cloud.

    Ir al selector de proyectos

  3. Asegúrate de que la facturación esté habilitada para tu proyecto de Cloud. Descubre cómo confirmar que tienes habilitada la facturación en un proyecto.

  4. Habilita las API de Cloud Functions, Cloud Build, Cloud Storage, and Cloud Vision.

    Habilita las API

  5. Instala e inicializa el SDK de Cloud.
  6. En la página del selector de proyectos de Google Cloud Console, selecciona o crea un proyecto de Google Cloud.

    Ir al selector de proyectos

  7. Asegúrate de que la facturación esté habilitada para tu proyecto de Cloud. Descubre cómo confirmar que tienes habilitada la facturación en un proyecto.

  8. Habilita las API de Cloud Functions, Cloud Build, Cloud Storage, and Cloud Vision.

    Habilita las API

  9. Instala e inicializa el SDK de Cloud.
  10. Si ya tienes instalado el SDK de Cloud, ejecuta el siguiente comando para actualizarlo:

    gcloud components update
  11. Prepara tu entorno de desarrollo.

Visualiza el flujo de datos

El flujo de datos en la aplicación de instructivo de ImageMagick incluye varios pasos como se muestra a continuación:

  1. Se sube una imagen a un bucket de Cloud Storage.
  2. La función de Cloud Functions analiza la imagen con la API de Cloud Vision.
  3. Si se detecta contenido violento o destinado a adultos, la función de Cloud Functions usa ImageMagick para difuminar la imagen.
  4. La imagen difuminada se sube a otro bucket de Cloud Storage para su utilización.

Prepara la aplicación

  1. Crea un bucket de Cloud Storage para subir imágenes, en el que YOUR_INPUT_BUCKET_NAME es un nombre de bucket único a nivel global:

    gsutil mb gs://YOUR_INPUT_BUCKET_NAME
    
  2. Crea un bucket de Cloud Storage para recibir las imágenes difuminadas, donde YOUR_OUTPUT_BUCKET_NAME es un nombre de bucket único a nivel global:

    gsutil mb gs://YOUR_OUTPUT_BUCKET_NAME
    
  3. Clona el repositorio de la app de muestra en tu máquina local:

    Node.js

    git clone https://github.com/GoogleCloudPlatform/nodejs-docs-samples.git

    De manera opcional, puedes descargar la muestra como un archivo zip y extraerla.

    Python

    git clone https://github.com/googleapis/python-spanner

    De manera opcional, puedes descargar la muestra como un archivo zip y extraerla.

    Go

    git clone https://github.com/GoogleCloudPlatform/golang-samples.git

    De manera opcional, puedes descargar la muestra como un archivo ZIP y extraerla.

    Java

    git clone https://github.com/GoogleCloudPlatform/java-docs-samples.git

    De manera opcional, puedes descargar la muestra como un archivo ZIP y extraerla.

    C#

    git clone https://github.com/GoogleCloudPlatform/dotnet-docs-samples.git

    De manera opcional, puedes descargar la muestra como un archivo ZIP y extraerla.

    Ruby

    git clone https://github.com/GoogleCloudPlatform/ruby-docs-samples.git

    De manera opcional, puedes descargar la muestra como un archivo ZIP y extraerla.

    PHP

    git clone https://github.com/GoogleCloudPlatform/php-docs-samples.git

    De manera opcional, puedes descargar la muestra como un archivo ZIP y extraerla.

  4. Ve al directorio que contiene el código de muestra de Cloud Functions, como sigue:

    Node.js

    cd nodejs-docs-samples/functions/imagemagick/

    Python

    cd python-spanner/samples/samples

    Go

    cd golang-samples/functions/imagemagick/

    Java

    cd java-docs-samples/functions/imagemagick/

    C#

    cd dotnet-docs-samples/functions/imagemagick/

    Ruby

    cd ruby-docs-samples/functions/imagemagick/

    PHP

    cd php-docs-samples/functions/imagemagick/

Comprende el código

Importa dependencias

La aplicación debe importar varias dependencias con el fin de interactuar con los servicios de Google Cloud Platform, ImageMagick y el sistema de archivos:

Node.js

const gm = require('gm').subClass({imageMagick: true});
const fs = require('fs').promises;
const path = require('path');
const vision = require('@google-cloud/vision');

const {Storage} = require('@google-cloud/storage');
const storage = new Storage();
const client = new vision.ImageAnnotatorClient();

const {BLURRED_BUCKET_NAME} = process.env;

Python

import os
import tempfile

from google.cloud import storage, vision
from wand.image import Image

storage_client = storage.Client()
vision_client = vision.ImageAnnotatorClient()

Go


// Package imagemagick contains an example of using ImageMagick to process a
// file uploaded to Cloud Storage.
package imagemagick

import (
	"context"
	"errors"
	"fmt"
	"log"
	"os"
	"os/exec"

	"cloud.google.com/go/storage"
	vision "cloud.google.com/go/vision/apiv1"
	visionpb "google.golang.org/genproto/googleapis/cloud/vision/v1"
)

// Global API clients used across function invocations.
var (
	storageClient *storage.Client
	visionClient  *vision.ImageAnnotatorClient
)

func init() {
	// Declare a separate err variable to avoid shadowing the client variables.
	var err error

	storageClient, err = storage.NewClient(context.Background())
	if err != nil {
		log.Fatalf("storage.NewClient: %v", err)
	}

	visionClient, err = vision.NewImageAnnotatorClient(context.Background())
	if err != nil {
		log.Fatalf("vision.NewAnnotatorClient: %v", err)
	}
}

Java



import com.google.cloud.functions.BackgroundFunction;
import com.google.cloud.functions.Context;
import com.google.cloud.storage.Blob;
import com.google.cloud.storage.BlobId;
import com.google.cloud.storage.BlobInfo;
import com.google.cloud.storage.Storage;
import com.google.cloud.storage.StorageOptions;
import com.google.cloud.vision.v1.AnnotateImageRequest;
import com.google.cloud.vision.v1.AnnotateImageResponse;
import com.google.cloud.vision.v1.BatchAnnotateImagesResponse;
import com.google.cloud.vision.v1.Feature;
import com.google.cloud.vision.v1.Feature.Type;
import com.google.cloud.vision.v1.Image;
import com.google.cloud.vision.v1.ImageAnnotatorClient;
import com.google.cloud.vision.v1.ImageSource;
import com.google.cloud.vision.v1.SafeSearchAnnotation;
import functions.eventpojos.GcsEvent;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.List;
import java.util.logging.Level;
import java.util.logging.Logger;

public class ImageMagick implements BackgroundFunction<GcsEvent> {

  private static Storage storage = StorageOptions.getDefaultInstance().getService();
  private static final String BLURRED_BUCKET_NAME = System.getenv("BLURRED_BUCKET_NAME");
  private static final Logger logger = Logger.getLogger(ImageMagick.class.getName());
}

C#

using CloudNative.CloudEvents;
using Google.Cloud.Functions.Framework;
using Google.Cloud.Functions.Hosting;
using Google.Cloud.Storage.V1;
using Google.Cloud.Vision.V1;
using Google.Events.Protobuf.Cloud.Storage.V1;
using Grpc.Core;
using Microsoft.AspNetCore.Hosting;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Logging;
using System;
using System.Diagnostics;
using System.IO;
using System.Threading;
using System.Threading.Tasks;

namespace ImageMagick
{
    // Dependency injection configuration, executed during server startup.
    public class Startup : FunctionsStartup
    {
        public override void ConfigureServices(WebHostBuilderContext context, IServiceCollection services) =>
            services
                .AddSingleton(ImageAnnotatorClient.Create())
                .AddSingleton(StorageClient.Create());
    }

    [FunctionsStartup(typeof(Startup))]
    public class Function : ICloudEventFunction<StorageObjectData>
    {
        /// <summary>
        /// The bucket to store blurred images in. An alternative to using environment variables here would be to
        /// fetch it from IConfiguration.
        /// </summary>
        private static readonly string s_blurredBucketName = Environment.GetEnvironmentVariable("BLURRED_BUCKET_NAME");

        private readonly ImageAnnotatorClient _visionClient;
        private readonly StorageClient _storageClient;
        private readonly ILogger _logger;

        public Function(ImageAnnotatorClient visionClient, StorageClient storageClient, ILogger<Function> logger) =>
            (_visionClient, _storageClient, _logger) = (visionClient, storageClient, logger);

    }
}

Ruby

require "functions_framework"

FunctionsFramework.on_startup do
  set_global :storage_client do
    require "google/cloud/storage"
    Google::Cloud::Storage.new
  end

  set_global :vision_client do
    require "google/cloud/vision"
    Google::Cloud::Vision.image_annotator
  end
end

PHP

use Google\CloudFunctions\CloudEvent;
use Google\Cloud\Storage\StorageClient;
use Google\Cloud\Vision\V1\ImageAnnotatorClient;
use Google\Cloud\Vision\V1\Likelihood;
use Google\Rpc\Code;

Analiza imágenes

Se invoca la siguiente función cuando una imagen se sube al bucket de Cloud Storage que creaste para almacenar imágenes. La función usa la API de Cloud Vision para detectar contenido violento o destinado para adultos en imágenes que se suben.

Node.js

// Blurs uploaded images that are flagged as Adult or Violence.
exports.blurOffensiveImages = async event => {
  // This event represents the triggering Cloud Storage object.
  const object = event;

  const file = storage.bucket(object.bucket).file(object.name);
  const filePath = `gs://${object.bucket}/${object.name}`;

  console.log(`Analyzing ${file.name}.`);

  try {
    const [result] = await client.safeSearchDetection(filePath);
    const detections = result.safeSearchAnnotation || {};

    if (
      // Levels are defined in https://cloud.google.com/vision/docs/reference/rest/v1/AnnotateImageResponse#likelihood
      detections.adult === 'VERY_LIKELY' ||
      detections.violence === 'VERY_LIKELY'
    ) {
      console.log(`Detected ${file.name} as inappropriate.`);
      return await blurImage(file, BLURRED_BUCKET_NAME);
    } else {
      console.log(`Detected ${file.name} as OK.`);
    }
  } catch (err) {
    console.error(`Failed to analyze ${file.name}.`, err);
    throw err;
  }
};

Python

# Blurs uploaded images that are flagged as Adult or Violence.
def blur_offensive_images(data, context):
    file_data = data

    file_name = file_data["name"]
    bucket_name = file_data["bucket"]

    blob = storage_client.bucket(bucket_name).get_blob(file_name)
    blob_uri = f"gs://{bucket_name}/{file_name}"
    blob_source = vision.Image(source=vision.ImageSource(gcs_image_uri=blob_uri))

    # Ignore already-blurred files
    if file_name.startswith("blurred-"):
        print(f"The image {file_name} is already blurred.")
        return

    print(f"Analyzing {file_name}.")

    result = vision_client.safe_search_detection(image=blob_source)
    detected = result.safe_search_annotation

    # Process image
    if detected.adult == 5 or detected.violence == 5:
        print(f"The image {file_name} was detected as inappropriate.")
        return __blur_image(blob)
    else:
        print(f"The image {file_name} was detected as OK.")

Go


// GCSEvent is the payload of a GCS event.
type GCSEvent struct {
	Bucket string `json:"bucket"`
	Name   string `json:"name"`
}

// BlurOffensiveImages blurs offensive images uploaded to GCS.
func BlurOffensiveImages(ctx context.Context, e GCSEvent) error {
	outputBucket := os.Getenv("BLURRED_BUCKET_NAME")
	if outputBucket == "" {
		return errors.New("BLURRED_BUCKET_NAME must be set")
	}

	img := vision.NewImageFromURI(fmt.Sprintf("gs://%s/%s", e.Bucket, e.Name))

	resp, err := visionClient.DetectSafeSearch(ctx, img, nil)
	if err != nil {
		return fmt.Errorf("AnnotateImage: %v", err)
	}

	if resp.GetAdult() == visionpb.Likelihood_VERY_LIKELY ||
		resp.GetViolence() == visionpb.Likelihood_VERY_LIKELY {
		return blur(ctx, e.Bucket, outputBucket, e.Name)
	}
	log.Printf("The image %q was detected as OK.", e.Name)
	return nil
}

Java

@Override
// Blurs uploaded images that are flagged as Adult or Violence.
public void accept(GcsEvent event, Context context) {
  // Validate parameters
  if (event.getBucket() == null || event.getName() == null) {
    logger.severe("Error: Malformed GCS event.");
    return;
  }

  BlobInfo blobInfo = BlobInfo.newBuilder(event.getBucket(), event.getName()).build();

  // Construct URI to GCS bucket and file.
  String gcsPath = String.format("gs://%s/%s", event.getBucket(), event.getName());
  logger.info(String.format("Analyzing %s", event.getName()));

  // Construct request.
  ImageSource imgSource = ImageSource.newBuilder().setImageUri(gcsPath).build();
  Image img = Image.newBuilder().setSource(imgSource).build();
  Feature feature = Feature.newBuilder().setType(Type.SAFE_SEARCH_DETECTION).build();
  AnnotateImageRequest request =
      AnnotateImageRequest.newBuilder().addFeatures(feature).setImage(img).build();
  List<AnnotateImageRequest> requests = List.of(request);

  // Send request to the Vision API.
  try (ImageAnnotatorClient client = ImageAnnotatorClient.create()) {
    BatchAnnotateImagesResponse response = client.batchAnnotateImages(requests);
    List<AnnotateImageResponse> responses = response.getResponsesList();
    for (AnnotateImageResponse res : responses) {
      if (res.hasError()) {
        logger.info(String.format("Error: %s", res.getError().getMessage()));
        return;
      }
      // Get Safe Search Annotations
      SafeSearchAnnotation annotation = res.getSafeSearchAnnotation();
      if (annotation.getAdultValue() == 5 || annotation.getViolenceValue() == 5) {
        logger.info(String.format("Detected %s as inappropriate.", event.getName()));
        blur(blobInfo);
      } else {
        logger.info(String.format("Detected %s as OK.", event.getName()));
      }
    }
  } catch (IOException e) {
    logger.log(Level.SEVERE, "Error with Vision API: " + e.getMessage(), e);
  }
}

C#

public async Task HandleAsync(CloudEvent cloudEvent, StorageObjectData data, CancellationToken cancellationToken)
{
    // Validate parameters
    if (data.Bucket is null || data.Name is null)
    {
        _logger.LogError("Malformed GCS event.");
        return;
    }

    // Construct URI to GCS bucket and file.
    string gcsUri = $"gs://{data.Bucket}/{data.Name}";
    _logger.LogInformation("Analyzing {uri}", gcsUri);

    // Perform safe search detection using the Vision API.
    Image image = Image.FromUri(gcsUri);
    SafeSearchAnnotation annotation;
    try
    {
        annotation = await _visionClient.DetectSafeSearchAsync(image);
    }
    // If the call to the Vision API fails, log the error but let the function complete normally.
    // If the exceptions weren't caught (and just propagated) the event would be retried.
    // See the "Best Practices" section in the documentation for more details about retry.
    catch (AnnotateImageException e)
    {
        _logger.LogError(e, "Vision API reported an error while performing safe search detection");
        return;
    }
    catch (RpcException e)
    {
        _logger.LogError(e, "Error communicating with the Vision API");
        return;
    }

    if (annotation.Adult == Likelihood.VeryLikely || annotation.Violence == Likelihood.VeryLikely)
    {
        _logger.LogInformation("Detected {uri} as inappropriate.", gcsUri);
        await BlurImageAsync(data, cancellationToken);
    }
    else
    {
        _logger.LogInformation("Detected {uri} as OK.", gcsUri);
    }
}

Ruby

# Blurs uploaded images that are flagged as Adult or Violence.
FunctionsFramework.cloud_event "blur_offensive_images" do |event|
  # Event-triggered Ruby functions receive a CloudEvents::Event::V1 object.
  # See https://cloudevents.github.io/sdk-ruby/latest/CloudEvents/Event/V1.html
  # The storage event payload can be obtained from the event data.
  payload = event.data
  file_name = payload["name"]
  bucket_name = payload["bucket"]

  # Ignore already-blurred files
  if file_name.start_with? "blurred-"
    logger.info "The image #{file_name} is already blurred."
    return
  end

  # Get image annotations from the Vision service
  logger.info "Analyzing #{file_name}."
  gs_uri = "gs://#{bucket_name}/#{file_name}"
  result = global(:vision_client).safe_search_detection image: gs_uri
  annotation = result.responses.first.safe_search_annotation

  # Respond to annotations by possibly blurring the image
  if annotation.adult == :VERY_LIKELY || annotation.violence == :VERY_LIKELY
    logger.info "The image #{file_name} was detected as inappropriate."
    blur_image bucket_name, file_name
  else
    logger.info "The image #{file_name} was detected as OK."
  end
end

PHP

function blurOffensiveImages(CloudEvent $cloudevent): void
{
    $log = fopen(getenv('LOGGER_OUTPUT') ?: 'php://stderr', 'wb');

    $storage = new StorageClient();
    $data = $cloudevent->getData();

    $file = $storage->bucket($data['bucket'])->object($data['name']);
    $filePath = 'gs://' . $data['bucket'] . '/' . $data['name'];
    fwrite($log, 'Analyzing ' . $filePath . PHP_EOL);

    $annotator = new ImageAnnotatorClient();
    $storage = new StorageClient();

    try {
        $response = $annotator->safeSearchDetection($filePath);

        // Handle error
        if ($response->hasError()) {
            $code = Code::name($response->getError()->getCode());
            $message = $response->getError()->getMessage();
            fwrite($log, sprintf('%s: %s' . PHP_EOL, $code, $message));
            return;
        }

        $annotation = $response->getSafeSearchAnnotation();

        $isInappropriate =
            $annotation->getAdult() === Likelihood::VERY_LIKELY ||
            $annotation->getViolence() === Likelihood::VERY_LIKELY;

        if ($isInappropriate) {
            fwrite($log, 'Detected ' . $data['name'] . ' as inappropriate.' . PHP_EOL);
            $blurredBucketName = getenv('BLURRED_BUCKET_NAME');

            blurImage($log, $file, $blurredBucketName);
        } else {
            fwrite($log, 'Detected ' . $data['name'] . ' as OK.' . PHP_EOL);
        }
    } catch (Exception $e) {
        fwrite($log, 'Failed to analyze ' . $data['name'] . PHP_EOL);
        fwrite($log, $e->getMessage() . PHP_EOL);
    }
}

Desenfoca imágenes

La siguiente función recibe una llamada cuando se detecta contenido violento o destinado para adultos en una imagen que se sube. La función descarga la imagen ofensiva, usa ImageMagick para difuminarla y, luego, sube la imagen difuminada sobre la imagen original.

Node.js

// Blurs the given file using ImageMagick, and uploads it to another bucket.
const blurImage = async (file, blurredBucketName) => {
  const tempLocalPath = `/tmp/${path.parse(file.name).base}`;

  // Download file from bucket.
  try {
    await file.download({destination: tempLocalPath});

    console.log(`Downloaded ${file.name} to ${tempLocalPath}.`);
  } catch (err) {
    throw new Error(`File download failed: ${err}`);
  }

  await new Promise((resolve, reject) => {
    gm(tempLocalPath)
      .blur(0, 16)
      .write(tempLocalPath, (err, stdout) => {
        if (err) {
          console.error('Failed to blur image.', err);
          reject(err);
        } else {
          console.log(`Blurred image: ${file.name}`);
          resolve(stdout);
        }
      });
  });

  // Upload result to a different bucket, to avoid re-triggering this function.
  const blurredBucket = storage.bucket(blurredBucketName);

  // Upload the Blurred image back into the bucket.
  const gcsPath = `gs://${blurredBucketName}/${file.name}`;
  try {
    await blurredBucket.upload(tempLocalPath, {destination: file.name});
    console.log(`Uploaded blurred image to: ${gcsPath}`);
  } catch (err) {
    throw new Error(`Unable to upload blurred image to ${gcsPath}: ${err}`);
  }

  // Delete the temporary file.
  return fs.unlink(tempLocalPath);
};

Python

# Blurs the given file using ImageMagick.
def __blur_image(current_blob):
    file_name = current_blob.name
    _, temp_local_filename = tempfile.mkstemp()

    # Download file from bucket.
    current_blob.download_to_filename(temp_local_filename)
    print(f"Image {file_name} was downloaded to {temp_local_filename}.")

    # Blur the image using ImageMagick.
    with Image(filename=temp_local_filename) as image:
        image.resize(*image.size, blur=16, filter="hamming")
        image.save(filename=temp_local_filename)

    print(f"Image {file_name} was blurred.")

    # Upload result to a second bucket, to avoid re-triggering the function.
    # You could instead re-upload it to the same bucket + tell your function
    # to ignore files marked as blurred (e.g. those with a "blurred" prefix)
    blur_bucket_name = os.getenv("BLURRED_BUCKET_NAME")
    blur_bucket = storage_client.bucket(blur_bucket_name)
    new_blob = blur_bucket.blob(file_name)
    new_blob.upload_from_filename(temp_local_filename)
    print(f"Blurred image uploaded to: gs://{blur_bucket_name}/{file_name}")

    # Delete the temporary file.
    os.remove(temp_local_filename)

Go


// blur blurs the image stored at gs://inputBucket/name and stores the result in
// gs://outputBucket/name.
func blur(ctx context.Context, inputBucket, outputBucket, name string) error {
	inputBlob := storageClient.Bucket(inputBucket).Object(name)
	r, err := inputBlob.NewReader(ctx)
	if err != nil {
		return fmt.Errorf("NewReader: %v", err)
	}

	outputBlob := storageClient.Bucket(outputBucket).Object(name)
	w := outputBlob.NewWriter(ctx)
	defer w.Close()

	// Use - as input and output to use stdin and stdout.
	cmd := exec.Command("convert", "-", "-blur", "0x8", "-")
	cmd.Stdin = r
	cmd.Stdout = w

	if err := cmd.Run(); err != nil {
		return fmt.Errorf("cmd.Run: %v", err)
	}

	log.Printf("Blurred image uploaded to gs://%s/%s", outputBlob.BucketName(), outputBlob.ObjectName())

	return nil
}

Java

// Blurs the file described by blobInfo using ImageMagick,
// and uploads it to the blurred bucket.
private static void blur(BlobInfo blobInfo) throws IOException {
  String bucketName = blobInfo.getBucket();
  String fileName = blobInfo.getName();

  // Download image
  Blob blob = storage.get(BlobId.of(bucketName, fileName));
  Path download = Paths.get("/tmp/", fileName);
  blob.downloadTo(download);

  // Construct the command.
  Path upload = Paths.get("/tmp/", "blurred-" + fileName);
  List<String> args = List.of("convert", download.toString(), "-blur", "0x8", upload.toString());
  try {
    ProcessBuilder pb = new ProcessBuilder(args);
    Process process = pb.start();
    process.waitFor();
  } catch (Exception e) {
    logger.info(String.format("Error: %s", e.getMessage()));
  }

  // Upload image to blurred bucket.
  BlobId blurredBlobId = BlobId.of(BLURRED_BUCKET_NAME, fileName);
  BlobInfo blurredBlobInfo =
      BlobInfo.newBuilder(blurredBlobId).setContentType(blob.getContentType()).build();

  byte[] blurredFile = Files.readAllBytes(upload);
  storage.create(blurredBlobInfo, blurredFile);
  logger.info(
      String.format("Blurred image uploaded to: gs://%s/%s", BLURRED_BUCKET_NAME, fileName));

  // Remove images from fileSystem
  Files.delete(download);
  Files.delete(upload);
}

C#

/// <summary>
/// Downloads the Storage object specified by <paramref name="data"/>,
/// blurs it using ImageMagick, and uploads it to the "blurred" bucket.
/// </summary>
private async Task BlurImageAsync(StorageObjectData data, CancellationToken cancellationToken)
{
    // Download image
    string originalImageFile = Path.GetTempFileName();
    using (Stream output = File.Create(originalImageFile))
    {
        await _storageClient.DownloadObjectAsync(data.Bucket, data.Name, output, cancellationToken: cancellationToken);
    }

    // Construct the ImageMagick command
    string blurredImageFile = Path.GetTempFileName();
    // Command-line arguments for ImageMagick.
    // Paths are wrapped in quotes in case they contain spaces.
    string arguments = $"\"{originalImageFile}\" -blur 0x8, \"{blurredImageFile}\"";

    // Run the ImageMagick command line tool ("convert").
    Process process = Process.Start("convert", arguments);
    // Process doesn't expose a way of asynchronously waiting for completion.
    // See https://stackoverflow.com/questions/470256 for examples of how
    // this can be achieved using events, but for the sake of brevity,
    // this sample just waits synchronously.
    process.WaitForExit();

    // If ImageMagick failed, log the error but complete normally to avoid retrying.
    if (process.ExitCode != 0)
    {
        _logger.LogError("ImageMagick exited with code {exitCode}", process.ExitCode);
        return;
    }

    // Upload image to blurred bucket.
    using (Stream input = File.OpenRead(blurredImageFile))
    {
        await _storageClient.UploadObjectAsync(
            s_blurredBucketName, data.Name, data.ContentType, input, cancellationToken: cancellationToken);
    }

    string uri = $"gs://{s_blurredBucketName}/{data.Name}";
    _logger.LogInformation("Blurred image uploaded to: {uri}", uri);

    // Remove images from the file system.
    File.Delete(originalImageFile);
    File.Delete(blurredImageFile);
}

Ruby

require "tempfile"
require "mini_magick"

# Blurs the given file using ImageMagick.
def blur_image bucket_name, file_name
  tempfile = Tempfile.new
  begin
    # Download the image file
    bucket = global(:storage_client).bucket bucket_name
    file = bucket.file file_name
    file.download tempfile
    tempfile.close

    # Blur the image using ImageMagick
    MiniMagick::Image.new tempfile.path do |image|
      image.blur "0x16"
    end
    logger.info "Image #{file_name} was blurred"

    # Upload result to a second bucket, to avoid re-triggering the function.
    # You could instead re-upload it to the same bucket and tell your function
    # to ignore files marked as blurred (e.g. those with a "blurred" prefix.)
    blur_bucket_name = ENV["BLURRED_BUCKET_NAME"]
    blur_bucket = global(:storage_client).bucket blur_bucket_name
    blur_bucket.create_file tempfile.path, file_name
    logger.info "Blurred image uploaded to gs://#{blur_bucket_name}/#{file_name}"
  ensure
    # Ruby will remove the temp file when garbage collecting the object,
    # but it is good practice to remove it explicitly.
    tempfile.unlink
  end
end

PHP

// Blurs the given file using ImageMagick, and uploads it to another bucket.
function blurImage(
    $log,
    Object $file,
    string $blurredBucketName
): void {
    $tempLocalPath = sys_get_temp_dir() . '/' . $file->name();

    // Download file from bucket.
    $image = new Imagick();
    try {
        $image->readImageBlob($file->downloadAsStream());
    } catch (Exception $e) {
        throw new Exception('Streaming download failed: ' . $e);
    }

    // Blur file using ImageMagick
    // (The Imagick class is from the PECL 'imagick' package)
    $image->blurImage(0, 16);

    // Stream blurred image result to a different bucket. // (This avoids re-triggering this function.)
    $storage = new StorageClient();
    $blurredBucket = $storage->bucket($blurredBucketName);

    // Upload the Blurred image back into the bucket.
    $gcsPath = 'gs://' . $blurredBucketName . '/' . $file->name();
    try {
        $blurredBucket->upload($image->getImageBlob(), [
            'name' => $file->name()
        ]);
        fwrite($log, 'Streamed blurred image to: ' . $gcsPath . PHP_EOL);
    } catch (Exception $e) {
        throw new Exception(
            sprintf(
                'Unable to stream blurred image to %s: %s',
                $gcsPath,
                $e->getMessage()
            )
        );
    }
}

Implementa la función

  1. Para implementar la función de Cloud Functions con un activador de almacenamiento, ejecuta el siguiente comando en el directorio que contiene el código de muestra (o en el caso de Java, el archivo pom.xml):

    Node.js

    gcloud functions deploy blurOffensiveImages \
    --runtime nodejs16 \
    --trigger-bucket YOUR_INPUT_BUCKET_NAME \
    --set-env-vars BLURRED_BUCKET_NAME=YOUR_OUTPUT_BUCKET_NAME
    Puedes usar los siguientes valores para que la marca --runtime especifique tu versión preferida de Node.js:
    • nodejs16 (recomendada)
    • nodejs14
    • nodejs12
    • nodejs10

    Python

    gcloud functions deploy blur_offensive_images \
    --runtime python39 \
    --trigger-bucket YOUR_INPUT_BUCKET_NAME \
    --set-env-vars BLURRED_BUCKET_NAME=YOUR_OUTPUT_BUCKET_NAME
    Puedes usar los siguientes valores para que la marca --runtime especifique tu versión preferida de Python:
    • python39 (recomendada)
    • python38
    • python37

    Go

    gcloud functions deploy BlurOffensiveImages \
    --runtime go116 \
    --trigger-bucket YOUR_INPUT_BUCKET_NAME \
    --set-env-vars BLURRED_BUCKET_NAME=YOUR_OUTPUT_BUCKET_NAME
    Puedes usar los siguientes valores en la marca --runtime para especificar tu versión preferida de Go:
    • go116 (recomendada)
    • go113
    • go111

    Java

    gcloud functions deploy java-blur-function \
    --entry-point functions.ImageMagick \
    --runtime java11 \
    --memory 512MB \
    --trigger-bucket YOUR_INPUT_BUCKET_NAME \
    --set-env-vars BLURRED_BUCKET_NAME=YOUR_OUTPUT_BUCKET_NAME

    C#

    gcloud functions deploy csharp-blur-function \
    --entry-point ImageMagick.Function \
    --runtime dotnet3 \
    --trigger-bucket YOUR_INPUT_BUCKET_NAME \
    --set-env-vars BLURRED_BUCKET_NAME=YOUR_OUTPUT_BUCKET_NAME

    Ruby

    gcloud functions deploy blur_offensive_images --runtime ruby27 \
    --trigger-bucket YOUR_INPUT_BUCKET_NAME \
    --set-env-vars BLURRED_BUCKET_NAME=YOUR_OUTPUT_BUCKET_NAME
    Puedes usar los siguientes valores para que con la marca --runtime se especifique tu versión preferida de Ruby:
    • ruby27 (recomendada)
    • ruby26

    PHP

    gcloud functions deploy blurOffensiveImages --runtime php74 \
    --trigger-bucket YOUR_INPUT_BUCKET_NAME \
    --set-env-vars BLURRED_BUCKET_NAME=YOUR_OUTPUT_BUCKET_NAME

    YOUR_INPUT_BUCKET_NAME es el nombre del bucket de Cloud Storage en el que se suben las imágenes, y YOUR_OUTPUT_BUCKET_NAME es el nombre del bucket en el que se deberían guardar las imágenes difuminadas.

Sube una imagen

  1. Sube una imagen ofensiva, como la imagen de un zombi que come carne humana:

    gsutil cp zombie.jpg gs://YOUR_INPUT_BUCKET_NAME
    

    donde YOUR_INPUT_BUCKET_NAME es el bucket de Cloud Storage que creaste previamente para subir imágenes.

  2. Revisa los registros para asegurarte de que las ejecuciones se completaron:

    gcloud functions logs read --limit 100
    
  3. Puedes ver las imágenes desenfocadas en el bucket de Cloud Storage YOUR_OUTPUT_BUCKET_NAME que creaste antes.

Limpia

Para evitar que se apliquen cargos a tu cuenta de Google Cloud por los recursos usados en este instructivo, borra el proyecto que contiene los recursos o conserva el proyecto y borra los recursos individuales.

Borra el proyecto

La manera más fácil de eliminar la facturación es borrar el proyecto que creaste para el instructivo.

Para borrar el proyecto, sigue estos pasos:

  1. En Cloud Console, ve a la página Administrar recursos.

    Ir a Administrar recursos

  2. En la lista de proyectos, elige el proyecto que quieres borrar y haz clic en Borrar.
  3. En el diálogo, escribe el ID del proyecto y, luego, haz clic en Cerrar para borrar el proyecto.

Borra la función de Cloud Functions

Borrar las funciones de Cloud Functions no quita ningún recurso almacenado en Cloud Storage.

Para borrar la función de Cloud Functions que implementaste en este instructivo, ejecuta el siguiente comando:

Node.js

gcloud functions delete blurOffensiveImages 

Python

gcloud functions delete blur_offensive_images 

Go

gcloud functions delete BlurOffensiveImages 

Java

gcloud functions delete java-blur-function 

C#

gcloud functions delete csharp-blur-function 

Ruby

gcloud functions delete blur_offensive_images 

PHP

gcloud functions delete blurOffensiveImages 

También puedes borrar funciones de Cloud Functions en Google Cloud Console.