根据 Firebase Cloud Functions 文档，您可以在云函数中利用 ImageMagick：https://firebase.google.com/docs/functions/use-cases
是否可以做类似的事情，但调用 FFMPEG 而不是 ImageMagick？ 虽然缩略图图像很棒，但我还希望能够将传入图像附加到存储在 Firebase 存储上的视频文件中。
更新：
ffmpeg注意 截至 2023 年 4 月，Google 不再提供 ffmpeg 作为最新版本 Ubuntu（v22.04）的云功能预装包。因此，确保选择使用 Ubuntu (v18.04) 的运行时环境，以便在云功能上预安装 ffmpeg。您可以在此处找到使用 Ubuntu (v18.04) 的完整运行时环境列表。
注意： 您只有在 /tmp/ 处具有磁盘 写
访问权限。选项 1：使用 ffmpeg- Fluent npm 模块
const ffmpeg = require('fluent-ffmpeg');
let cmd = ffmpeg('example.mp4')
.clone()
.size('300x300')
.save('/tmp/smaller-file.mp4')
.on('end', () => {
// Finished processing the video.
console.log('Done');
// E.g. return the resized video:
res.sendFile('/tmp/smaller-file.mp4');
});
选项 2：直接调用 ffmpeg 二进制文件ffmpeg
已经安装，您可以通过 shell 进程调用二进制文件及其命令行选项。
const { exec } = require("child_process");
exec("ffmpeg -i example.mp4", (error, stdout, stderr) => {
//ffmpeg logs to stderr, but typically output is in stdout.
console.log(stderr);
});
选项 3：上传您自己的二进制文件./
../
index.js
ffmpeg
index.jsconst { exec } = require("child_process");
exec("ffmpeg -i example.mp4", (error, stdout, stderr) => {
//ffmpeg logs to stderr, but typically output is in stdout.
console.log(stderr);
});
我在 GitHub 上提供了两个完整的工作示例。这些示例适用于 Google Cloud Functions（并非专门针对 Firebase 的 Cloud Functions）。
根据
/**
* Copyright 2017 Google Inc. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for t`he specific language governing permissions and
* limitations under the License.
*/
'use strict';
const functions = require('firebase-functions');
const gcs = require('@google-cloud/storage')();
const path = require('path');
const os = require('os');
const fs = require('fs');
const ffmpeg = require('fluent-ffmpeg');
const ffmpeg_static = require('ffmpeg-static');
/**
* When an audio is uploaded in the Storage bucket We generate a mono channel audio automatically using
* node-fluent-ffmpeg.
*/
exports.generateMonoAudio = functions.storage.object().onChange(event => {
const object = event.data; // The Storage object.
const fileBucket = object.bucket; // The Storage bucket that contains the file.
const filePath = object.name; // File path in the bucket.
const contentType = object.contentType; // File content type.
const resourceState = object.resourceState; // The resourceState is 'exists' or 'not_exists' (for file/folder deletions).
const metageneration = object.metageneration; // Number of times metadata has been generated. New objects have a value of 1.
// Exit if this is triggered on a file that is not an audio.
if (!contentType.startsWith('audio/')) {
console.log('This is not an audio.');
return;
}
// Get the file name.
const fileName = path.basename(filePath);
// Exit if the audio is already converted.
if (fileName.endsWith('_output.flac')) {
console.log('Already a converted audio.');
return;
}
// Exit if this is a move or deletion event.
if (resourceState === 'not_exists') {
console.log('This is a deletion event.');
return;
}
// Exit if file exists but is not new and is only being triggered
// because of a metadata change.
if (resourceState === 'exists' && metageneration > 1) {
console.log('This is a metadata change event.');
return;
}
// Download file from bucket.
const bucket = gcs.bucket(fileBucket);
const tempFilePath = path.join(os.tmpdir(), fileName);
// We add a '_output.flac' suffix to target audio file name. That's where we'll upload the converted audio.
const targetTempFileName = fileName.replace(/\.[^/.]+$/, "") + '_output.flac';
const targetTempFilePath = path.join(os.tmpdir(), targetTempFileName);
const targetStorageFilePath = path.join(path.dirname(filePath), targetTempFileName);
return bucket.file(filePath).download({
destination: tempFilePath
}).then(() => {
console.log('Audio downloaded locally to', tempFilePath);
// Convert the audio to mono channel using FFMPEG.
const command = ffmpeg(tempFilePath)
.setFfmpegPath(ffmpeg_static.path)
.audioChannels(1)
.audioFrequency(16000)
.format('flac')
.on('error', (err) => {
console.log('An error occurred: ' + err.message);
})
.on('end', () => {
console.log('Output audio created at', targetTempFilePath);
// Uploading the audio.
return bucket.upload(targetTempFilePath, {destination: targetStorageFilePath}).then(() => {
console.log('Output audio uploaded to', targetStorageFilePath);
// Once the audio has been uploaded delete the local file to free up disk space.
fs.unlinkSync(tempFilePath);
fs.unlinkSync(targetTempFilePath);
console.log('Temporary files removed.', targetTempFilePath);
});
})
.save(targetTempFilePath);
});
});
https://github.com/firebase/functions-samples/blob/master/ffmpeg-convert-audio/functions/index.js
Cloud Functions 配额（10MB 上传）的音频/视频文件。
您需要在 GCP 的 AppEngine 上运行基本上就是举重运动员。它允许您编写后端并将其部署到云端。考虑一下您通常可能开发的 Node Express 服务器。然后将其部署到云端。这就是应用程序引擎。
Firebase / Cloud Functions 通常通过 HTTP 或 PubSub 与 App Engine 通信。
函数是为了轻量级工作而设计的。它们会告诉您事件何时发生（例如，文件上传到存储桶），并且触发的“事件”具有有关该事件的有效负载详细信息（例如，上传到存储桶的对象的详细信息）。
当该事件发生时，如果需要繁重的工作（或者 Node.js 运行时环境上缺少所需的软件），该函数会向 App Engine 发出 HTTP 请求，提供 App Engine 执行以下操作所需的信息：必要的处理。
App Engine 非常灵活。您定义一个 yaml 文件和一个可选的 Dockerfile。
这是一个例子：
runtime: custom # custom means it uses a Dockerfile
env: flex
manual_scaling:
instances: 1
resources:
cpu: 1
memory_gb: 0.5
disk_size_gb: 10
在这里定义CPU数量、内存、磁盘大小等。与函数不同的是，磁盘是可写的（我被引导相信，我仍在集成过程中）。
通过 Dockerfile，您可以准确定义要安装的软件。如果您不熟悉 Dockerfile，这里有一个很好的示例：
https://nodejs.org/en/docs/guides/nodejs-docker-webappgcloud app deploy
瞧，您的应用程序出现在云端。
gcloud命令随
Google Cloud SDK一起提供。 请注意，处理完成后，AppEngine 可以通过 HTTP 函数或 PubSub 与函数进行对话。