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Based on NodeAV.","maintainers":[{"name":"vanilagy","email":"dpayr@musica-viva.de"}],"readme":"# @mediabunny/server\n\n[![](https://img.shields.io/npm/v/@mediabunny/server)](https://www.npmjs.com/package/@mediabunny/server)\n[![](https://img.shields.io/bundlephobia/minzip/@mediabunny/server)](https://bundlephobia.com/package/@mediabunny/server)\n[![](https://img.shields.io/npm/dm/@mediabunny/server)](https://www.npmjs.com/package/@mediabunny/server)\n[![](https://img.shields.io/discord/1390044844285497344?logo=discord&label=Discord)](https://discord.gg/hmpkyYuS4U)\n\n<div align=\"center\">\n    <img src=\"./logo.svg\" width=\"180\" height=\"180\">\n</div>\n\nBy default, Mediabunny requires a browser environment for full access to decoders, encoders, and video processing features. `@mediabunny/server` uses [NodeAV](https://github.com/seydx/node-av) to polyfill this functionality for server-side environments such as Node, Bun, or Deno, enabling the usage of all Mediabunny features on the server. The result is a server-side media processing API that integrates naturally with TypeScript as opposed to the awkwardness and inefficiencies of calling out to the FFmpeg CLI.\n\nFeatures added by this package include:\n- Video decoders and encoders for AVC (H.264), HEVC (H.265), VP8, VP9, AV1, and ProRes. Supports both length-prefixed and Annex B AVC/HEVC as well as transparent video via VP9 and ProRes.\n- Audio decoders and encoders for AAC, MP3, Vorbis, Opus, FLAC, AC-3 and E-AC-3. Supports AAC in both AAC and ADTS formats.\n- Video frame transformation support (resize, rotate, flip, crop)\n- Automatic hardware acceleration on all platforms (macOS, Linux, Windows)\n- Built-in multithreading\n- Zero-copy decode and encode paths\n\n> This package, like the rest of Mediabunny, is enabled by its [sponsors](https://mediabunny.dev/#sponsors) and their donations. If you've derived value from this package, please consider [leaving a donation](https://github.com/sponsors/Vanilagy)! 💘\n\n> This package was made possible in large part due to seydx's amazing work on [NodeAV](https://github.com/seydx/node-av). The library is truly modern, a joy to work with, and incredibly powerful. Give them a star!\n\n## Installation\n\nThis library peer-depends on Mediabunny. Install both using npm:\n```bash\nnpm install mediabunny @mediabunny/server\n```\n\n## Usage\n\n```ts\nimport { registerMediabunnyServer } from '@mediabunny/server';\nregisterMediabunnyServer();\n```\n\nThat's it - you now have access to the full Mediabunny feature set on the server.\n\n---\n\nAn optional `options` parameter is available for further configuration:\n```ts\nimport { registerMediabunnyServer } from '@mediabunny/server';\nimport * as NodeAv from 'node-av';\n\nregisterMediabunnyServer({\n    // Use a specific hardware rendering device:\n    hardwareContext: NodeAv.HardwareContext.create(\n        NodeAv.AV_HWDEVICE_TYPE_VAAPI,\n        '/dev/dri/renderD128',\n    ),\n});\n```\n\n## Upload media compression example\n\nHere, we set up a simple media compression server in Node.js. The client's request body is streamed to Mediabunny, the media gets processed, and the output is streamed directly to the disk. Memory usage is O(1) due to pipelining, and an overly fast uploader is automatically slowed down due to stream backpressure.\n\n```ts\nimport { ALL_FORMATS, Conversion, FilePathTarget, Input, Mp4OutputFormat, Output, Quality, ReadableStreamSource } from \"mediabunny\";\nimport { registerMediabunnyServer } from \"@mediabunny/server\";\nimport { Readable } from \"node:stream\";\nimport http from \"node:http\";\n\nregisterMediabunnyServer();\n\nconst server = http.createServer(async (req, res) => {\n    // Read the request body as a stream\n    const stream = Readable.toWeb(req) as ReadableStream<Uint8Array>;\n    const input = new Input({\n        source: new ReadableStreamSource(stream),\n        formats: ALL_FORMATS,\n    });\n\n    // Stream the output directly to the disk, could also stream to S3 etc.\n    const output = new Output({\n        format: new Mp4OutputFormat(),\n        target: new FilePathTarget(`./converted-${crypto.randomUUID()}.mp4`),\n    });\n\n    try {\n        const conversion = await Conversion.init({\n            input,\n            output,\n            video: async track => ({\n                codec: 'avc',\n                height: Math.min(720, await track.getDisplayHeight()),\n                quality: new Quality('medium'),\n            }),\n        });\n        await conversion.execute();\n    \n        res.statusCode = 204;\n        res.end();\n    } catch (error) {\n        res.statusCode = 500;\n        res.end();\n\n        console.error(\"Error processing media:\", error);\n    }\n});\n\nserver.listen(3000);\n```\n\nFor all the other ways to use Mediabunny, refer to its [guide](https://mediabunny.dev/guide/introduction).\n\n## Performance\n\n`@mediabunny/server` is extremely performant as it is a thin wrapper around [NodeAV](https://github.com/seydx/node-av), which itself is a thin wrapper around the FFmpeg C API. All decoders and encoders automatically run on separate threads, keeping the main thread unblocked. Hardware acceleration is automatically detected and utilized on all operating systems whenever available (unless explicitly disabled using `hardwareAcceleration: 'prefer-software'`). Video frame and audio sample data is never copied from FFmpeg unless explicitly requested via `VideoSample.copyTo()` and `AudioSample.copyTo()`, and zero-copy GPU decode -> encode paths are used automatically whenever possible.\n\n## Advanced usage\n\n### Usage with NodeAV\n\n`@mediabunny/server` provides `AvFrameVideoSampleResource` and `AvFrameAudioSampleResource` as a means to create `VideoSample` and `AudioSample` instances that are directly backed by data residing in NodeAV's [`Frame`](https://seydx.github.io/node-av/api/lib/classes/Frame.html) (and therefore FFmpeg's `AVFrame`) without ever having to copy data to or from JavaScript. Reading NodeAV's documentation can help you make full use of this integration.\n\nTo convert between Mediabunny and NodeAV (FFmpeg) worlds, you can do this:\n```ts\nimport { VideoSample, AudioSample } from 'mediabunny';\nimport { AvFrameVideoSampleResource, AvFrameAudioSampleResource, toAvFrame } from '@mediabunny/server';\n\n// Frame -> VideoSample\nnew VideoSample(new AvFrameVideoSampleResource(frame), { timestamp });\n\n// Frame -> AudioSample\nnew AudioSample(new AvFrameAudioSampleResource(frame));\n// (uses the timestamp in the frame)\n\n// VideoSample -> Frame\nawait toAvFrame(videoSample, frame);\n\n// AudioSample -> Frame\nawait toAvFrame(audioSample, frame);\n```\n\n#### Electron example\n\nFor example, when using Electron, we may want to capture the app's contents without moving video data from the GPU to the CPU:\n```ts\nimport { VideoSample } from 'mediabunny';\nimport { AvFrameVideoSampleResource } from '@mediabunny/server';\nimport { HardwareContext, SharedTexture, AV_HWDEVICE_TYPE_VIDEOTOOLBOX } from 'node-av';\n\n// Create hardware context (platform-specific)\nconst hw = HardwareContext.create(AV_HWDEVICE_TYPE_VIDEOTOOLBOX);\nusing sharedTexture = SharedTexture.create(hw);\n\n// In Electron paint event with offscreen rendering\noffscreen.webContents.on('paint', (event) => {\n    const texture = event.texture;\n    if (!texture?.textureInfo) {\n        return;\n    }\n\n    // Import as hardware frame (zero-copy)\n    const frame = sharedTexture.importTexture(texture.textureInfo, { pts: 0n });\n    const sample = new VideoSample(new AvFrameVideoSampleResource(frame), {\n        timestamp: 0,\n        duration: 0,\n    });\n\n    texture.release();\n});\n```\n\n#### Microphone recording example\n\nHere, we're using NodeAV's Device API to access the user's microphone:\n```ts\nimport { AudioSample } from 'mediabunny';\nimport { AvFrameAudioSampleResource } from '@mediabunny/server';\nimport { DeviceAPI, Decoder } from 'node-av';\n\nawait using mic = await DeviceAPI.openMicrophone();\nconst audioStream = mic.audio()!;\nusing decoder = await Decoder.create(audioStream);\n\nlet firstTimestamp: number | null = null;\nfor await (const frame of decoder.frames(mic.packets(audioStream.index))) {\n    if (!frame) {\n        break;\n    }\n\n    const sample = new AudioSample(new AvFrameAudioSampleResource(frame));\n    \n    if (firstTimestamp === null) {\n        firstTimestamp = sample.timestamp;\n    }\n\n    // Offset timestamps so they start at 0\n    sample.setTimestamp(sample.timestamp - firstTimestamp);\n\n    // Do something with the sample now, like passing it to an AudioSampleSource\n    // ...\n}\n```\n\n### Video and audio processing\n\nBrowser environments ship with many API goodies such as the Canvas 2D API which are a naturally great fit for doing video frame processing, and they integrate well with Mediabunny. On the server, these APIs don't exist, so other approaches must be used:\n\n#### VideoSample.transform()\n\nThis method allows for simple transformations on `VideoSample` instances and works when `@mediabunny/server` has been registered:\n```ts\nconst transformed = await sample.transform({\n    width: 640,\n    height: 360,\n    fit: 'cover',\n});\n```\n\n#### NodeAV filter graphs\n\nFFmpeg's `libavfilter` is an incredibly powerful and generic media processing library, and all of it is directly accessible via NodeAV. It works for both video as well as audio data.\n\nFor example, here we combine Mediabunny's Conversion API with a filter graph to grayscale a video:\n```ts\nimport { Conversion } from 'mediabunny';\nimport { AvFrameVideoSampleResource, toAvFrame } from '@mediabunny/server';\nimport { Frame, FilterAPI } from 'node-av';\n\nasync function* one(f: Frame) { yield f; }\n\nconst conversion = await Conversion.init({\n    // ...\n    video: {\n        process: async (sample) => {\n            // VideoSample -> Frame\n            using inFrame = new Frame();\n            inFrame.alloc();\n            await toAvFrame(sample, inFrame);\n\n            // Frame -> filter -> AvFrameVideoSampleResource\n            using filter = FilterAPI.create('format=gray');\n            for await (const outFrame of filter.frames(one(inFrame))) {\n                return outFrame && new AvFrameVideoSampleResource(outFrame);\n            }\n\n            return null;\n        },\n    },\n    // ...\n});\nawait conversion.execute();\n```\n\n#### Canvas API polyfills\n\nLibraries like [Skia Canvas](https://github.com/samizdatco/skia-canvas) provide GPU-enabled polyfills for the Canvas 2D API. Using it with Mediabunny is simply a matter of converting from and to the Canvas API:\n```ts\nconst width = videoSample.displayWidth;\nconst height = videoSample.displayHeight;\n\nconst canvas = new Canvas(width, height);\nconst ctx = canvas.getContext('2d');\n\n// Copy data from VideoSample\nconst imageData = ctx.createImageData(width, height);\nawait videoSample.copyTo(imageData.data, { format: 'RGBA' });\nctx.putImageData(imageData, 0, 0);\n\n// Issue draw commands\nctx.fillStyle = 'red';\nctx.fillRect(20, 20, 100, 60);\n\n// Convert to VideoSample again\nconst pixels = ctx.getImageData(0, 0, width, height).data;\nreturn new VideoSample(pixels, {\n    format: 'RGBA',\n    codedWidth: width,\n    codedHeight: height,\n    timestamp: videoSample.timestamp,\n    duration: videoSample.duration,\n});\n```\n\n## Controlling logging\n\nEspecially in command-line applications you usually don't want Mediabunny interfering with your stdout and stderr output. Mediabunny provides ways to control its console output:\n```ts\nimport { Logging, LogLevel } from 'mediabunny';\n\n// The default: Mediabunny can log errors, warnings, and information messages.\nLogging.level = LogLevel.Info;\n\n// Only log warnings and errors.\nLogging.level = LogLevel.Warnings;\n\n// Only log errors.\nLogging.level = LogLevel.Errors;\n\n// Don't log anything at all.\nLogging.level = LogLevel.None;\n```\n\nYou can also hook into log events:\n```ts\nLogging.on('error', (args: unknown[]) => {\n\t// Handle error message\n});\n\nLogging.on('warn', (args: unknown[]) => {\n\t// Handle warning message\n});\n\nLogging.on('info', (args: unknown[]) => {\n\t// Handle info message\n});\n```\n\n## Implementation details\n\n`@mediabunny/server` uses [NodeAV](https://github.com/seydx/node-av) under the hood which provides N-API C bindings to FFmpeg's C API. Using NodeAV, this package implements [custom decoders and encoders](https://mediabunny.dev/guide/supported-formats-and-codecs#custom-coders) by directly using the APIs provided by `libavcodec`.\n\nFor encoding, video frames and audio samples are transferred to FFmpeg by converting them to an `AVFrame` and are then passed to the correct encoder. The resulting packets are then normalized into the format expected by WebCodecs and the [Mediabunny Codec Registry](https://mediabunny.dev/codec-registry/overview). For decoding, the above process is inverted: packets and decoder metadata are passed to the correct decoder, and the resulting `AVFrame` instances are wrapped in `VideoSample` or `AudioSample` instances. Video frame transformations (resize, rotate, flip, crop) are implemented using the `libavfilter` API.\n\nWhenever possible, `AVFrame`s are never copied over to JavaScript unless explicitly needed. This enables zero-copy decode -> transformation -> encode paths.\n\nProRes decoding support is provided by [TurboRes](https://github.com/Vanilagy/turbores), as it is often faster than FFmpeg.\n\n## License\n\n`@mediabunny/server` uses the same MPL-2.0 license as Mediabunny.","readmeFilename":"README.md"}