ImageMagick 教程

本教程演示了如何使用 Cloud Functions 函数、Google Cloud Vision APIImageMagick 检测上传到 Cloud Storage 存储分区的令人反感的图片并对其进行模糊处理。

目标

  • 部署存储触发的后台 Cloud Functions 函数
  • 使用 Cloud Vision API 检测暴力或成人内容。
  • 使用 ImageMagick 对令人反感的图片进行模糊处理。
  • 上传一张肉食僵尸的图片来测试函数。

费用

本教程使用 Cloud Platform 的可计费组件,包括:

  • Google Cloud Functions
  • Google Cloud Storage
  • Google Cloud Vision API

您可使用价格计算器根据您的预计使用情况来估算费用。

Cloud Platform 新用户可能有资格申请免费试用

准备工作

  1. 登录您的 Google Cloud 帐号。如果您是 Google Cloud 新手,请创建一个帐号来评估我们的产品在实际场景中的表现。新客户还可获享 $300 赠金,用于运行、测试和部署工作负载。
  2. 在 Google Cloud Console 的项目选择器页面上,选择或创建一个 Google Cloud 项目。

    转到“项目选择器”

  3. 确保您的 Cloud 项目已启用结算功能。 了解如何确认您的项目是否已启用结算功能

  4. 启用 Cloud Functions, Cloud Build, Cloud Storage, and Cloud Vision API。

    启用 API

  5. 安装并初始化 Cloud SDK
  6. 如果您已安装 Cloud SDK,请运行以下命令进行更新:

    gcloud components update
  7. 准备开发环境。

直观呈现数据流

ImageMagick 教程应用中的数据流涉及以下几个步骤:

  1. 将图片上传到 Cloud Storage 存储分区。
  2. Cloud Functions 函数使用 Cloud Vision API 分析图片。
  3. 如果检测到暴力或成人内容,Cloud Functions 函数会使用 ImageMagick 对图片进行模糊处理。
  4. 经过模糊处理的图片会上传到其他 Cloud Storage 存储分区以供使用。

准备应用

  1. 创建一个 Cloud Storage 存储分区以上传图片,其中 YOUR_INPUT_BUCKET_NAME 是全局唯一的存储分区名称:

    gsutil mb gs://YOUR_INPUT_BUCKET_NAME
    
  2. 创建一个 Cloud Storage 存储分区以接收经过模糊处理的图片,其中 YOUR_OUTPUT_BUCKET_NAME 是全局唯一的存储分区名称:

    gsutil mb gs://YOUR_OUTPUT_BUCKET_NAME
    
  3. 将示例应用代码库克隆到本地机器:

    Node.js

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

    或者,您也可以下载该示例的 zip 文件并将其解压缩。

    Python

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

    或者,您也可以下载该示例的 zip 文件并将其解压缩。

    Go

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

    或者,您也可以下载该示例的 zip 文件并将其解压缩。

    Java

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

    或者,您也可以下载该示例的 zip 文件并将其解压缩。

    C#

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

    或者,您也可以下载该示例的 zip 文件并将其解压缩。

    Ruby

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

    或者,您也可以下载该示例的 zip 文件并将其解压缩。

    PHP

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

    或者,您也可以下载该示例的 zip 文件并将其解压缩。

  4. 切换到包含 Cloud Functions 函数示例代码的目录:

    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/

了解代码

导入依赖项

应用必须导入多个依赖项才能与 Google Cloud Platform 服务、ImageMagick 和文件系统进行交互:

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;

分析图片

当图片上传到您为了存储图片而创建的 Cloud Storage 存储分区时,系统会调用以下函数。该函数使用 Cloud Vision API 检测上传的图片中的暴力或成人内容。

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);
    }
}

对图片进行模糊处理

当在上传的图片中检测到暴力或成人内容时,系统将调用以下函数。该函数会下载令人反感的图片,使用 ImageMagick 对图片进行模糊处理,然后上传经过模糊处理后的图片来覆盖原始图片。

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()
            )
        );
    }
}

部署函数

  1. 如需使用存储触发器部署 Cloud Functions 函数,请在包含示例代码(如果是 Java,则为 pom.xml 文件)的目录中运行以下命令:

    Node.js

    gcloud functions deploy blurOffensiveImages \
    --runtime nodejs14 \
    --trigger-bucket YOUR_INPUT_BUCKET_NAME \
    --set-env-vars BLURRED_BUCKET_NAME=YOUR_OUTPUT_BUCKET_NAME
    您可以使用 --runtime 标志的以下值来指定偏好的 Node.js 版本:
    • nodejs16(预览版)
    • nodejs14(推荐)
    • 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
    您可以使用 --runtime 标志的以下值来指定偏好的 Python 版本:
    • python39(推荐)
    • python38
    • python37

    Go

    gcloud functions deploy BlurOffensiveImages \
    --runtime go113 \
    --trigger-bucket YOUR_INPUT_BUCKET_NAME \
    --set-env-vars BLURRED_BUCKET_NAME=YOUR_OUTPUT_BUCKET_NAME
    您可以使用 --runtime 标志的以下值来指定偏好的 Go 版本:
    • go116(预览版)
    • go113(推荐)
    • 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
    您可以使用 --runtime 标志的以下值来指定偏好的 Ruby 版本:
    • ruby27(推荐)
    • ruby26

    PHP

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

    其中 YOUR_INPUT_BUCKET_NAME 是用于上传图片的 Cloud Storage 存储分区的名称,YOUR_OUTPUT_BUCKET_NAME 是用于保存经过模糊处理的图片的存储分区名称。

上传图片

  1. 上传一张令人反感的图片,比如这张肉食僵尸图片:

    gsutil cp zombie.jpg gs://YOUR_INPUT_BUCKET_NAME
    

    其中 YOUR_INPUT_BUCKET_NAME 是您之前为了上传图片而创建的 Cloud Storage 存储分区。

  2. 查看日志以确保执行已完成:

    gcloud functions logs read --limit 100
    
  3. 您可以在之前创建的 YOUR_OUTPUT_BUCKET_NAME Cloud Storage 存储分区中查看经过模糊处理的图片。

清除数据

为避免因本教程中使用的资源导致您的 Google Cloud 帐号产生费用,请删除包含这些资源的项目,或者保留项目但删除各个资源。

删除项目

为了避免产生费用,最简单的方法是删除您为本教程创建的项目。

要删除项目,请执行以下操作:

  1. 在 Cloud Console 中,转到管理资源页面。

    转到“管理资源”

  2. 在项目列表中,选择要删除的项目,然后点击删除
  3. 在对话框中输入项目 ID,然后点击关闭以删除项目。

删除 Cloud Functions 函数

删除 Cloud Functions 函数不会移除存储在 Cloud Storage 中的任何资源。

如需删除您在本教程中部署的 Cloud Functions 函数,请运行以下命令:

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 

您也可以通过 Google Cloud Console 删除 Cloud Functions 函数。