Tutorial do ImageMagick

Neste tutorial, você verá como usar o Cloud Functions, a API Google Cloud Vision e o ImageMagick para detectar e desfocar imagens ofensivas que são enviadas para um bucket do Cloud Storage.

Objetivos

  • Implantar um Background Cloud Function acionado por armazenamento.
  • Usar a API Cloud Vision para detectar conteúdo violento ou adulto.
  • Usar o ImageMagick para desfocar imagens ofensivas.
  • Testar a função fazendo upload de uma imagem de um zumbi comedor de carne.

Custos

Neste tutorial, usamos os seguintes componentes faturáveis do Google Cloud:

  • Cloud Functions
  • Cloud Storage
  • Cloud Vision

Para gerar uma estimativa de custo baseada na projeção de uso deste tutorial, use a calculadora de preços. Novos usuários do Google Cloud podem estar qualificados para uma avaliação gratuita.

Antes de começar

  1. Faça login na sua conta do Google Cloud. Se você começou a usar o Google Cloud agora, crie uma conta para avaliar o desempenho de nossos produtos em situações reais. Clientes novos também recebem US$ 300 em créditos para executar, testar e implantar cargas de trabalho.
  2. No Console do Google Cloud, na página do seletor de projetos, selecione ou crie um projeto do Google Cloud.

    Acessar o seletor de projetos

  3. Verifique se o faturamento está ativado para seu projeto na nuvem. Saiba como confirmar se o faturamento está ativado para o projeto.

  4. Ative as APIs Cloud Functions, Cloud Build, Cloud Storage, and Cloud Vision.

    Ative as APIs

  5. Instale e inicialize o SDK do Cloud..
  6. No Console do Google Cloud, na página do seletor de projetos, selecione ou crie um projeto do Google Cloud.

    Acessar o seletor de projetos

  7. Verifique se o faturamento está ativado para seu projeto na nuvem. Saiba como confirmar se o faturamento está ativado para o projeto.

  8. Ative as APIs Cloud Functions, Cloud Build, Cloud Storage, and Cloud Vision.

    Ative as APIs

  9. Instale e inicialize o SDK do Cloud..
  10. Se o SDK do Cloud já estiver instalado, atualize-o executando o comando a seguir:

    gcloud components update
  11. Prepare seu ambiente de desenvolvimento.

Como visualizar o fluxo de dados

O fluxo de dados no aplicativo do tutorial do ImageMagick envolve vários passos:

  1. Uma imagem é enviada para um bucket do Cloud Storage.
  2. O Cloud Function analisa a imagem usando a API Cloud Vision.
  3. Se for detectado conteúdo violento ou adulto, o Cloud Function usará o ImageMagick para desfocar a imagem.
  4. É feito o upload da imagem desfocada para outro bucket do Cloud Storage para uso.

Como preparar o aplicativo

  1. Crie um bucket do Cloud Storage para fazer upload de imagens, onde YOUR_INPUT_BUCKET_NAME é um nome de bucket globalmente exclusivo:

    gsutil mb gs://YOUR_INPUT_BUCKET_NAME
    
  2. Criar um bucket do Cloud Storage para receber imagens desfocadas, onde YOUR_OUTPUT_BUCKET_NAME é um nome de bucket exclusivo globalmente:

    gsutil mb gs://YOUR_OUTPUT_BUCKET_NAME
    
  3. Clone o repositório do app de amostra na máquina local:

    Node.js

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

    Outra alternativa é fazer o download da amostra como um arquivo ZIP e extraí-lo.

    Python

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

    Outra alternativa é fazer o download da amostra como um arquivo ZIP e extraí-lo.

    Go

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

    Outra alternativa é fazer o download da amostra como um arquivo ZIP e extraí-lo.

    Java

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

    Outra alternativa é fazer o download da amostra como um arquivo ZIP e extraí-lo.

    C#

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

    Outra alternativa é fazer o download da amostra como um arquivo ZIP e extraí-lo.

    Ruby

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

    Outra alternativa é fazer o download da amostra como um arquivo ZIP e extraí-lo.

    PHP

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

    Outra alternativa é fazer o download da amostra como um arquivo ZIP e extraí-lo.

  4. Altere para o diretório que contém o código de amostra do Cloud Functions:

    Node.js

    cd nodejs-docs-samples/functions/imagemagick/

    Python

    cd python-docs-samples/functions/imagemagick/

    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/

Noções básicas sobre o código

Como importar dependências

O aplicativo precisa importar várias dependências para interagir com os serviços do Google Cloud Platform, o ImageMagick e o sistema de arquivos:

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;

Como analisar imagens

A função a seguir é invocada quando é feito upload de uma imagem no bucket do Cloud Storage criado para o armazenamento de imagens. A função usa a API Cloud Vision para detectar conteúdo violento ou adulto em imagens enviadas.

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);
    }
}

Imagens desfocadas

A função a seguir é chamada quando conteúdo violento ou adulto é detectado em uma imagem enviada. A função faz o download da imagem ofensiva, usa o ImageMagick para desfocar a imagem e depois faz upload da imagem desfocada sobre a imagem 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()
            )
        );
    }
}

Como implantar a função

  1. Para implantar a função do Cloud com um gatilho de armazenamento, execute o seguinte comando no diretório que contém o código de amostra (ou, no caso de Java, o arquivo 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
    É possível usar os seguintes valores para a sinalização --runtime para especificar sua versão preferida do Node.js:
    • nodejs16 (recomendado)
    • 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
    É possível usar os seguintes valores da sinalização --runtime para especificar a versão preferencial do Python:
    • python39 (recomendado)
    • 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
    É possível usar os seguintes valores para a sinalização --runtime para especificar sua versão Go preferencial:
    • go116 (recomendado)
    • 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
    Use os seguintes valores da sinalização --runtime para especificar a versão do Ruby que você quer usar:
    • ruby27 (recomendado)
    • ruby26

    PHP

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

    Em que YOUR_INPUT_BUCKET_NAME é o nome do bucket do Cloud Storage para upload de imagens, e YOUR_OUTPUT_BUCKET_NAME é o nome do bucket em que as imagens desfocadas devem ser salvas.

Como fazer upload de uma imagem

  1. Faça upload de uma imagem ofensiva, como essa imagem de um zumbi comedor de carne:

    gsutil cp zombie.jpg gs://YOUR_INPUT_BUCKET_NAME
    

    onde YOUR_INPUT_BUCKET_NAME é o bucket do Cloud Storage criado anteriormente para o upload de imagens.

  2. Verifique os registros para ter certeza de que as execuções foram concluídas:

    gcloud functions logs read --limit 100
    
  3. É possível visualizar as imagens desfocadas no bucket do Cloud Storage YOUR_OUTPUT_BUCKET_NAME criado anteriormente.

Limpeza

Para evitar cobranças na sua conta do Google Cloud pelos recursos usados no tutorial, exclua o projeto que os contém ou mantenha o projeto e exclua os recursos individuais.

Excluir o projeto

O jeito mais fácil de evitar cobranças é excluindo o projeto que você criou para o tutorial.

Para excluir o projeto:

  1. No Console do Cloud, acesse a página Gerenciar recursos:

    Acessar "Gerenciar recursos"

  2. Na lista de projetos, selecione o projeto que você quer excluir e clique em Excluir .
  3. Na caixa de diálogo, digite o ID do projeto e clique em Encerrar para excluí-lo.

Como excluir a Função do Cloud

A exclusão de Cloud Functions não remove nenhum recurso armazenado no Cloud Storage.

Para excluir a Função do Cloud implantada neste tutorial, execute o seguinte 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 

Também é possível excluir o Cloud Functions do Console do Google Cloud.