{"version":3,"sources":["../lib/stable/index.ts","../node_modules/.pnpm/tsup@8.5.1_postcss@8.5.26_typescript@5.9.3/node_modules/tsup/assets/cjs_shims.js","../lib/stable/errors.ts","../lib/stable/lifecycle.ts","../lib/stable/mirror.ts","../lib/stable/native.ts","../lib/stable/workflows.ts"],"sourcesContent":["import { EventEmitter } from \"node:events\";\nimport { mkdir, writeFile } from \"node:fs/promises\";\nimport os from \"node:os\";\nimport path from \"node:path\";\nimport { Worker } from \"node:worker_threads\";\nimport sharp from \"sharp\";\n\nimport { LibRawError, normalizeError } from \"./errors\";\nimport {\n abortError,\n restoreBuffers,\n stateAfterFailure,\n stateAfterOperation,\n stateAfterThumbnail,\n} from \"./lifecycle\";\nimport { installForwardedOperations } from \"./mirror\";\nimport { findPackageRoot, loadNativeAddon } from \"./native\";\nimport type {\n BayerDescriptor,\n DataErrorEvent,\n DecoderInfo,\n EncodedImageResult,\n ExifTagEvent,\n LibRawImageDataSnapshot,\n LibRawOptions,\n JPEGUsage,\n MakerNoteEvent,\n MemoryImageFormat,\n OperationOptions,\n OptimalJPEGSettings,\n ProcessedImage,\n ProcessorState,\n ProgressEvent,\n} from \"./types\";\nimport {\n createPpmResult,\n optimalJpegSettings,\n sharpInput,\n type RenderOptions,\n} from \"./workflows\";\n\nexport * from \"./errors\";\nexport type * from \"./types\";\n\ninterface WorkerResponse {\n id?: number;\n event?: { name: string; [key: string]: unknown };\n result?: unknown;\n error?: Error & { code?: string; librawCode?: number };\n}\n\ninterface PendingRequest {\n resolve(value: unknown): void;\n reject(error: unknown): void;\n}\n\nexport class LibRaw extends EventEmitter {\n readonly flags: number;\n private readonly worker: Worker;\n private readonly cancellationBuffer = new SharedArrayBuffer(4);\n private readonly cancellation: Int32Array;\n private readonly pending = new Map();\n private nextRequestId = 1;\n private tail: Promise = Promise.resolve();\n private closePromise?: Promise;\n private closeRequested = false;\n private workerFailure?: Error;\n private _state: ProcessorState = \"idle\";\n\n constructor(options: LibRawOptions = {}) {\n super();\n this.flags = options.flags ?? 0;\n this.cancellation = new Int32Array(this.cancellationBuffer);\n this.worker = new Worker(\n path.join(findPackageRoot(), \"dist\", \"processor-worker.cjs\"),\n {\n workerData: {\n flags: this.flags,\n cancellationBuffer: this.cancellationBuffer,\n },\n },\n );\n this.worker.on(\"message\", (message: WorkerResponse) => {\n if (message.event) {\n const { name, ...event } = message.event;\n this.emit(name, event);\n return;\n }\n if (message.id === undefined) return;\n const pending = this.pending.get(message.id);\n if (!pending) return;\n this.pending.delete(message.id);\n if (message.error) pending.reject(message.error);\n else pending.resolve(restoreBuffers(message.result));\n });\n const failWorker = (error: Error) => {\n this.workerFailure ??= error;\n for (const pending of this.pending.values()) pending.reject(error);\n this.pending.clear();\n if (this._state !== \"closing\" && this._state !== \"closed\") {\n this._state = \"error\";\n }\n };\n this.worker.on(\"error\", failWorker);\n this.worker.on(\"exit\", (code) => {\n if (this._state !== \"closing\" && this._state !== \"closed\") {\n failWorker(new Error(`LibRaw processor worker exited with code ${code}`));\n }\n });\n }\n\n get state(): ProcessorState {\n return this._state;\n }\n\n private request(method: string, args: unknown[]): Promise {\n if (this.workerFailure) return Promise.reject(this.workerFailure);\n const id = this.nextRequestId++;\n return new Promise((resolve, reject) => {\n this.pending.set(id, { resolve, reject });\n try {\n this.worker.postMessage({ id, method, args });\n } catch (error) {\n this.pending.delete(id);\n reject(error);\n }\n });\n }\n\n private enqueue(\n operation: string,\n args: unknown[] = [],\n options: OperationOptions = {},\n nativeOperation = operation,\n ): Promise {\n if (this.closeRequested || this._state === \"closing\" || this._state === \"closed\") {\n return Promise.reject(\n new LibRawError(\"LibRaw instance is closed\", {\n code: \"INSTANCE_CLOSED\",\n operation,\n state: \"closed\",\n }),\n );\n }\n if (options.signal?.aborted) {\n return Promise.reject(\n abortError(operation, this._state, options.signal.reason),\n );\n }\n\n const queuedState = this._state;\n const run = this.tail.then(async () => {\n if (options.signal?.aborted) {\n throw abortError(operation, queuedState, options.signal.reason);\n }\n const before = this._state;\n Atomics.store(this.cancellation, 0, 0);\n if (nativeOperation.startsWith(\"open\") || nativeOperation.startsWith(\"load\")) {\n this._state = \"opening\";\n }\n let aborted = false;\n const onAbort = () => {\n aborted = true;\n Atomics.store(this.cancellation, 0, 1);\n };\n options.signal?.addEventListener(\"abort\", onAbort, { once: true });\n try {\n const value = await this.request(nativeOperation, args);\n if (aborted) throw abortError(operation, before, options.signal?.reason);\n if (!this.closeRequested) {\n if (nativeOperation === \"processRawThumbnailNative\") {\n this._state = stateAfterThumbnail(value);\n } else if (\n nativeOperation === \"freeImage\" ||\n nativeOperation === \"setOutputParams\"\n ) {\n this._state = before === \"processed\" ? \"unpacked\" : before;\n } else {\n this._state = stateAfterOperation[nativeOperation] ?? this._state;\n }\n }\n return value as T;\n } catch (error) {\n if (aborted) throw abortError(operation, before, options.signal?.reason);\n if (!this.closeRequested) {\n this._state = stateAfterFailure[nativeOperation] ?? before;\n }\n throw normalizeError(error, operation, before);\n } finally {\n options.signal?.removeEventListener(\"abort\", onAbort);\n }\n });\n this.tail = run.then(\n () => undefined,\n () => undefined,\n );\n return run;\n }\n\n openFile(file: string, options?: OperationOptions): Promise {\n return this.enqueue(\"openFile\", [file], options).then(() => undefined);\n }\n\n openBuffer(input: Uint8Array, options?: OperationOptions): Promise {\n return this.enqueue(\"openBuffer\", [Buffer.from(input)], options).then(\n () => undefined,\n );\n }\n\n openBayer(\n input: Uint8Array,\n descriptor: BayerDescriptor,\n options?: OperationOptions,\n ): Promise {\n return this.enqueue(\n \"openBayer\",\n [Buffer.from(input), descriptor],\n options,\n ).then(() => undefined);\n }\n\n loadFile(file: string, options?: OperationOptions): Promise {\n return this.enqueue(\"loadFile\", [file], options).then(() => undefined);\n }\n\n loadBuffer(input: Uint8Array, options?: OperationOptions): Promise {\n return this.enqueue(\"loadBuffer\", [Buffer.from(input)], options).then(\n () => undefined,\n );\n }\n\n loadBayerData(\n file: string,\n descriptor: BayerDescriptor,\n options?: OperationOptions,\n ): Promise {\n return this.enqueue(\"loadBayerData\", [file, descriptor], options).then(\n () => undefined,\n );\n }\n\n recycle(options?: OperationOptions): Promise {\n return this.enqueue(\"recycle\", [], options).then(() => undefined);\n }\n\n async close(): Promise {\n if (this._state === \"closed\") return;\n if (this.closePromise) return this.closePromise;\n this.closeRequested = true;\n this._state = \"closing\";\n this.closePromise = this.tail\n .then(() =>\n this.workerFailure ? undefined : this.request(\"close\", []),\n )\n .then(() => undefined)\n .finally(async () => {\n await this.worker.terminate();\n this._state = \"closed\";\n });\n return this.closePromise;\n }\n\n getImgData(options?: OperationOptions): Promise {\n return this.enqueue(\"getImgData\", [], options);\n }\n\n unpack(options?: OperationOptions): Promise {\n return this.enqueue(\"unpack\", [], options).then(() => undefined);\n }\n\n unpackThumb(options?: OperationOptions): Promise {\n return this.enqueue(\"unpackThumb\", [], options).then(() => undefined);\n }\n\n unpackThumbEx(index: number, options?: OperationOptions): Promise {\n return this.enqueue(\"unpackThumbEx\", [index], options).then(() => undefined);\n }\n\n dcrawProcess(options?: OperationOptions): Promise {\n return this.enqueue(\"dcrawProcess\", [], options).then(() => undefined);\n }\n\n processImage(options?: OperationOptions): Promise {\n return this.enqueue(\"processImage\", [], options).then(() => undefined);\n }\n\n dcrawMakeMemImage(options?: OperationOptions): Promise {\n return this.enqueue(\"dcrawMakeMemImage\", [], options);\n }\n\n dcrawMakeMemThumb(options?: OperationOptions): Promise {\n return this.enqueue(\"dcrawMakeMemThumb\", [], options);\n }\n\n createMemoryImage(options?: OperationOptions): Promise {\n return this.dcrawMakeMemImage(options);\n }\n\n createMemoryThumbnail(options?: OperationOptions): Promise {\n return this.dcrawMakeMemThumb(options);\n }\n\n setCancelFlag(): void {\n Atomics.store(this.cancellation, 0, 1);\n }\n\n clearCancelFlag(): void {\n Atomics.store(this.cancellation, 0, 0);\n }\n\n async copyMemImage(\n destination: Buffer,\n stride: number,\n bgr = false,\n options?: OperationOptions,\n ): Promise {\n const copy = await this.enqueue(\n \"copyMemImage\",\n [destination.length, stride, bgr],\n options,\n \"copyMemImageOwned\",\n );\n copy.copy(destination);\n }\n\n private async runWorkflow(\n operation: string,\n work: () => T | Promise,\n ): Promise {\n try {\n return await work();\n } catch (error) {\n throw normalizeError(error, operation, this._state);\n }\n }\n\n private async render(\n format: Exclude,\n options: RenderOptions = {},\n source: EncodedImageResult[\"source\"] = \"processed\",\n operation = `create${format.toUpperCase()}Buffer`,\n ): Promise {\n const started = performance.now();\n const image =\n source === \"embedded-thumbnail\"\n ? await this.enqueue(\n operation,\n [],\n options,\n \"renderThumbnail\",\n )\n : await this.enqueue(\n operation,\n [],\n options,\n \"renderProcessedImage\",\n );\n return this.runWorkflow(operation, () =>\n this.encodeImage(image, format, options, source, started),\n );\n }\n\n private async encodeImage(\n image: ProcessedImage,\n format: Exclude,\n options: RenderOptions,\n source: EncodedImageResult[\"source\"],\n started = performance.now(),\n ): Promise {\n const sharpData = sharpInput(\n image,\n `create${format.toUpperCase()}Buffer`,\n this._state,\n );\n let pipeline =\n image.type === 1\n ? sharp(sharpData)\n : sharp(sharpData, {\n raw: {\n width: image.width,\n height: image.height,\n channels: image.colors as 1 | 2 | 3 | 4,\n },\n });\n if (options.width || options.height) {\n pipeline = pipeline.resize(options.width, options.height, { fit: \"inside\" });\n }\n if (format === \"jpeg\") {\n pipeline = pipeline.jpeg({\n quality: options.quality,\n progressive: options.progressive,\n mozjpeg: options.mozjpeg,\n chromaSubsampling: options.chromaSubsampling,\n optimizeCoding: options.optimizeCoding,\n trellisQuantisation: options.trellisQuantisation,\n optimizeScans: options.optimizeScans,\n });\n }\n if (format === \"png\") {\n pipeline = pipeline.png({ compressionLevel: options.compressionLevel });\n }\n if (format === \"tiff\") pipeline = pipeline.tiff();\n if (format === \"webp\") pipeline = pipeline.webp({ quality: options.quality });\n if (format === \"avif\") {\n pipeline = pipeline.avif({ quality: options.quality, effort: options.effort });\n }\n const { data, info } = await pipeline.toBuffer({ resolveWithObject: true });\n return {\n data,\n format,\n width: info.width,\n height: info.height,\n channels: info.channels,\n size: data.length,\n processingTimeMs: performance.now() - started,\n source,\n };\n }\n\n createJPEGBuffer(options?: RenderOptions): Promise {\n return this.render(\"jpeg\", options, \"processed\", \"createJPEGBuffer\");\n }\n createPNGBuffer(options?: RenderOptions): Promise {\n return this.render(\"png\", options, \"processed\", \"createPNGBuffer\");\n }\n createTIFFBuffer(options?: RenderOptions): Promise {\n return this.render(\"tiff\", options, \"processed\", \"createTIFFBuffer\");\n }\n createWebPBuffer(options?: RenderOptions): Promise {\n return this.render(\"webp\", options, \"processed\", \"createWebPBuffer\");\n }\n createAVIFBuffer(options?: RenderOptions): Promise {\n return this.render(\"avif\", options, \"processed\", \"createAVIFBuffer\");\n }\n createThumbnailJPEGBuffer(options?: RenderOptions): Promise {\n return this.render(\n \"jpeg\",\n options,\n \"embedded-thumbnail\",\n \"createThumbnailJPEGBuffer\",\n );\n }\n\n async createPPMBuffer(options: OperationOptions = {}): Promise {\n const started = performance.now();\n const image = await this.enqueue(\n \"createPPMBuffer\",\n [],\n options,\n \"renderProcessedImage\",\n );\n return this.runWorkflow(\"createPPMBuffer\", () =>\n createPpmResult(image, started, this._state),\n );\n }\n\n async convertToJPEG(\n outputPath: string,\n options: RenderOptions = {},\n ): Promise {\n return this.writeJPEG(\"convertToJPEG\", outputPath, options);\n }\n\n convertToJPEGFast(\n outputPath: string,\n options: RenderOptions = {},\n ): Promise {\n return this.writeJPEG(\"convertToJPEGFast\", outputPath, {\n quality: 80,\n effort: 1,\n ...options,\n });\n }\n\n private async writeJPEG(\n operation: string,\n outputPath: string,\n options: RenderOptions,\n ): Promise {\n const result = await this.render(\"jpeg\", options, \"processed\", operation);\n return this.runWorkflow(operation, async () => {\n await writeFile(outputPath, result.data);\n return result;\n });\n }\n\n async convertToJPEGMultiSize(\n baseOutputPath: string,\n options: RenderOptions & {\n sizes?: Array;\n } = {},\n ): Promise> {\n const sizes = options.sizes ?? [\n { name: \"thumb\", width: 400, quality: 85 },\n { name: \"web\", width: 1920, quality: 80 },\n { name: \"full\", quality: 85 },\n ];\n const image = await this.enqueue(\n \"convertToJPEGMultiSize\",\n [],\n options,\n \"renderProcessedImage\",\n );\n return this.runWorkflow(\"convertToJPEGMultiSize\", async () => {\n const result: Record = {};\n for (const size of sizes) {\n const { name, ...renderOptions } = size;\n const encoded = await this.encodeImage(\n image,\n \"jpeg\",\n { ...options, ...renderOptions } as RenderOptions,\n \"processed\",\n );\n await writeFile(`${baseOutputPath}_${name}.jpg`, encoded.data);\n result[name] = encoded;\n }\n return result;\n });\n }\n\n batchConvertToJPEG(\n inputPaths: string[],\n outputDirectory: string,\n options: RenderOptions & { maxConcurrency?: number } = {},\n ): Promise {\n return LibRaw.batchConvertToJPEGParallel(\n inputPaths,\n outputDirectory,\n options,\n );\n }\n\n async processRawThumbnail(options: {\n filePath: string;\n format: \"jpeg\" | \"png\" | \"webp\";\n maxSize: number;\n quality?: number;\n compressionLevel?: number;\n tryEmbedded?: boolean;\n signal?: AbortSignal;\n }): Promise {\n const started = performance.now();\n const native = await this.enqueue<{\n image: ProcessedImage;\n source: EncodedImageResult[\"source\"];\n }>(\n \"processRawThumbnail\",\n [{\n filePath: options.filePath,\n format: options.format,\n tryEmbedded: options.tryEmbedded !== false,\n }],\n options,\n \"processRawThumbnailNative\",\n );\n const renderOptions = {\n width: options.maxSize,\n quality: options.quality,\n compressionLevel: options.compressionLevel,\n signal: options.signal,\n };\n return this.runWorkflow(\"processRawThumbnail\", () =>\n this.encodeImage(\n native.image,\n options.format,\n renderOptions,\n native.source,\n started,\n ),\n );\n }\n\n async getOptimalJPEGSettings(\n options: { usage?: JPEGUsage } = {},\n ): Promise {\n const metadata = await this.getMetadata();\n return optimalJpegSettings(metadata, options.usage);\n }\n\n static async batchConvertToJPEGParallel(\n inputPaths: string[],\n outputDirectory: string,\n options: RenderOptions & { maxConcurrency?: number } = {},\n ): Promise {\n try {\n await mkdir(outputDirectory, { recursive: true });\n const concurrency = Math.max(\n 1,\n Math.min(\n options.maxConcurrency ?? Math.min(os.cpus().length, 4),\n inputPaths.length || 1,\n ),\n );\n const results = new Array(inputPaths.length);\n let nextIndex = 0;\n await Promise.all(\n Array.from({ length: concurrency }, async () => {\n for (;;) {\n const index = nextIndex++;\n if (index >= inputPaths.length) return;\n const input = inputPaths[index]!;\n const processor = new LibRaw();\n try {\n await processor.loadFile(input, options);\n const filename = path.basename(input, path.extname(input));\n results[index] = await processor.convertToJPEG(\n path.join(outputDirectory, `${filename}.jpg`),\n options,\n );\n } finally {\n await processor.close();\n }\n }\n }),\n );\n return results;\n } catch (error) {\n throw normalizeError(error, \"batchConvertToJPEGParallel\", \"idle\");\n }\n }\n\n static version(): string {\n return loadNativeAddon().LibRawWrapper.getVersion().replace(/-.*$/, \"\");\n }\n static versionNumber(): number {\n const [major = 0, minor = 0, patch = 0] = this.version()\n .split(\".\")\n .map(Number);\n return (major << 16) | (minor << 8) | patch;\n }\n static capabilities(): number {\n return loadNativeAddon().LibRawWrapper.getCapabilities();\n }\n static cameraList(): readonly string[] {\n return Object.freeze([...loadNativeAddon().LibRawWrapper.getCameraList()]);\n }\n static cameraCount(): number {\n return loadNativeAddon().LibRawWrapper.getCameraCount();\n }\n static strError(code: number): string {\n const wrapper = new (loadNativeAddon().LibRawWrapper)();\n try {\n const strerror = wrapper.strerror;\n if (!strerror) return `LibRaw error ${code}`;\n return String(strerror.call(wrapper, code));\n } finally {\n wrapper.close();\n }\n }\n static strProgress(progress: number): string {\n return loadNativeAddon().LibRawWrapper.strProgress(progress);\n }\n static cameraMakerIndexToMaker(index: number): string | null {\n return loadNativeAddon().LibRawWrapper.cameraMakerIndexToMaker(index);\n }\n static simplifyMakeModel(\n makerIndex: number,\n make: string,\n model: string,\n ): { makerIndex: number; make: string; model: string } {\n const result = loadNativeAddon().LibRawWrapper.simplifyMakeModel(\n makerIndex,\n make,\n model,\n ) as { makerIndex: number; make: string; model: string };\n return result;\n }\n static powfLimited(base: number, exponent: number, limit: number): number {\n return exponent > limit || exponent < -limit\n ? 0\n : Math.pow(base, exponent);\n }\n static powf64Limited(base: number, exponent: number): number {\n return this.powfLimited(base, exponent, 64);\n }\n static readBigEndianUnsigned(length: number, input: Uint8Array): number {\n if (length < 0 || length > 4 || input.length < length) {\n throw new RangeError(\"length must be between 0 and 4 and fit input\");\n }\n let result = 0;\n for (let index = 0; index < length; index++) {\n result = result * 256 + input[index]!;\n }\n return result >>> 0;\n }\n\n version(): string {\n return LibRaw.version();\n }\n versionNumber(): number {\n return LibRaw.versionNumber();\n }\n static getVersion(): string {\n return this.version();\n }\n static getCapabilities(): number {\n return this.capabilities();\n }\n static getCameraList(): readonly string[] {\n return this.cameraList();\n }\n static getCameraCount(): number {\n return this.cameraCount();\n }\n}\n\ninstallForwardedOperations(LibRaw.prototype);\n\nexport interface LibRaw {\n on(event: \"progress\", listener: (event: ProgressEvent) => void): this;\n on(event: \"dataError\", listener: (event: DataErrorEvent) => void): this;\n on(event: \"exifTag\", listener: (event: ExifTagEvent) => void): this;\n on(event: \"makerNote\", listener: (event: MakerNoteEvent) => void): this;\n on(event: string | symbol, listener: (...args: any[]) => void): this;\n errorCount(options?: OperationOptions): Promise;\n recycleDatastream(options?: OperationOptions): Promise;\n subtractBlack(options?: OperationOptions): Promise;\n subtractBlackInternal(options?: OperationOptions): Promise;\n raw2Image(options?: OperationOptions): Promise;\n raw2ImageEx(subtractBlack?: boolean, options?: OperationOptions): Promise;\n raw2ImageStart(options?: OperationOptions): Promise;\n freeImage(options?: OperationOptions): Promise;\n adjustMaximum(options?: OperationOptions): Promise;\n adjustSizesInfoOnly(options?: OperationOptions): Promise;\n adjustToRawInsetCrop(mask: number, maxCrop?: number, options?: OperationOptions): Promise;\n setMakeFromIndex(index: number, options?: OperationOptions): Promise;\n convertFloatToInt(min?: number, max?: number, target?: number, options?: OperationOptions): Promise;\n dcrawPpmTiffWriter(file: string, options?: OperationOptions): Promise;\n dcrawThumbWriter(file: string, options?: OperationOptions): Promise;\n getMemImageFormat(options?: OperationOptions): Promise;\n copyMemImage(destination: Buffer, stride: number, bgr?: boolean, options?: OperationOptions): Promise;\n colorAt(row: number, column: number, options?: OperationOptions): Promise;\n filterColorAt(row: number, column: number, options?: OperationOptions): Promise;\n fcol(row: number, column: number, options?: OperationOptions): Promise;\n unpackFunctionName(options?: OperationOptions): Promise;\n getDecoderInfo(options?: OperationOptions): Promise;\n phaseOneSubtractBlack(source: Buffer, options?: OperationOptions): Promise;\n phaseOneCorrect(options?: OperationOptions): Promise;\n adobeCoeff(makerIndex: number, model: string, internalOnly?: boolean, options?: OperationOptions): Promise;\n thumbOk(maxSize?: number, options?: OperationOptions): Promise;\n isFujiRotated(options?: OperationOptions): Promise;\n isSraw(options?: OperationOptions): Promise;\n srawMidpoint(options?: OperationOptions): Promise;\n isNikonSraw(options?: OperationOptions): Promise;\n isCoolscanNef(options?: OperationOptions): Promise;\n isJpegThumb(options?: OperationOptions): Promise;\n isFloatingPoint(options?: OperationOptions): Promise;\n haveFpData(options?: OperationOptions): Promise;\n getMetadata(options?: OperationOptions): Promise;\n getImageSize(options?: OperationOptions): Promise;\n getAdvancedMetadata(options?: OperationOptions): Promise;\n getLensInfo(options?: OperationOptions): Promise;\n getColorInfo(options?: OperationOptions): Promise;\n setOutputParams(params: Partial, options?: OperationOptions): Promise;\n getOutputParams(options?: OperationOptions): Promise;\n getLastError(options?: OperationOptions): Promise;\n strerror(code: number, options?: OperationOptions): Promise;\n writePPM(file: string, options?: OperationOptions): Promise;\n writeTIFF(file: string, options?: OperationOptions): Promise;\n writeThumbnail(file: string, options?: OperationOptions): Promise;\n getRawImageBuffer(options?: OperationOptions): Promise;\n}\n\nexport default LibRaw;\n","// Shim globals in cjs bundle\n// There's a weird bug that esbuild will always inject importMetaUrl\n// if we export it as `const importMetaUrl = ... __filename ...`\n// But using a function will not cause this issue\n\nconst getImportMetaUrl = () => \n typeof document === \"undefined\" \n ? new URL(`file:${__filename}`).href \n : (document.currentScript && document.currentScript.tagName.toUpperCase() === 'SCRIPT') \n ? document.currentScript.src \n : new URL(\"main.js\", document.baseURI).href;\n\nexport const importMetaUrl = /* @__PURE__ */ getImportMetaUrl()\n","import type { ProcessorState } from \"./types\";\n\nexport interface LibRawErrorOptions {\n code: string;\n operation: string;\n librawCode?: number | null;\n state: ProcessorState;\n cause?: unknown;\n}\n\nexport class LibRawError extends Error {\n readonly code: string;\n readonly operation: string;\n readonly librawCode: number | null;\n readonly state: ProcessorState;\n override readonly cause: unknown;\n\n constructor(message: string, options: LibRawErrorOptions) {\n super(message, { cause: options.cause });\n this.name = \"LibRawError\";\n this.code = options.code;\n this.operation = options.operation;\n this.librawCode = options.librawCode ?? null;\n this.state = options.state;\n this.cause = options.cause;\n }\n}\n\nexport function normalizeError(\n error: unknown,\n operation: string,\n state: ProcessorState,\n): LibRawError {\n if (error instanceof LibRawError) return error;\n const candidate = error as {\n message?: string;\n code?: string;\n librawCode?: number;\n cause?: unknown;\n };\n return new LibRawError(candidate?.message ?? String(error), {\n code: candidate?.code ?? \"LIBRAW_ERROR\",\n operation,\n librawCode: candidate?.librawCode ?? null,\n state,\n cause: candidate?.cause ?? error,\n });\n}\n","import { LibRawError } from \"./errors\";\nimport type { EncodedImageResult, ProcessorState } from \"./types\";\n\nexport const stateAfterOperation: Partial> = {\n openFile: \"opened\",\n openBuffer: \"opened\",\n openBayer: \"opened\",\n loadFile: \"unpacked\",\n loadBuffer: \"unpacked\",\n loadBayerData: \"unpacked\",\n unpack: \"unpacked\",\n dcrawProcess: \"processed\",\n processImage: \"processed\",\n renderProcessedImage: \"processed\",\n recycle: \"idle\",\n};\n\nexport const stateAfterFailure: Partial> = {\n loadFile: \"idle\",\n loadBuffer: \"idle\",\n loadBayerData: \"idle\",\n processRawThumbnailNative: \"idle\",\n};\n\nexport function stateAfterThumbnail(\n value: unknown,\n): Extract {\n const source = (value as { source?: EncodedImageResult[\"source\"] })?.source;\n return source === \"embedded-thumbnail\" ? \"unpacked\" : \"processed\";\n}\n\nexport function restoreBuffers(value: unknown): unknown {\n if (value instanceof Uint8Array && !Buffer.isBuffer(value)) {\n return Buffer.from(value);\n }\n if (Array.isArray(value)) return value.map(restoreBuffers);\n if (value && typeof value === \"object\") {\n return Object.fromEntries(\n Object.entries(value).map(([key, child]) => [key, restoreBuffers(child)]),\n );\n }\n return value;\n}\n\nexport function abortError(\n operation: string,\n state: ProcessorState,\n cause: unknown,\n): LibRawError {\n return new LibRawError(`Operation ${operation} was aborted`, {\n code: \"ABORT_ERR\",\n operation,\n state,\n cause,\n });\n}\n","import type { OperationOptions } from \"./types\";\n\nexport const forwardedOperations = [\n \"errorCount\", \"recycleDatastream\", \"subtractBlack\", \"subtractBlackInternal\",\n \"raw2Image\", \"raw2ImageEx\", \"raw2ImageStart\", \"freeImage\", \"adjustMaximum\",\n \"adjustSizesInfoOnly\", \"adjustToRawInsetCrop\", \"setMakeFromIndex\",\n \"convertFloatToInt\", \"dcrawPpmTiffWriter\", \"dcrawThumbWriter\",\n \"getMemImageFormat\", \"colorAt\", \"filterColorAt\", \"fcol\",\n \"unpackFunctionName\", \"getDecoderInfo\", \"phaseOneSubtractBlack\",\n \"phaseOneCorrect\", \"adobeCoeff\", \"thumbOk\",\n \"isFujiRotated\", \"isSraw\", \"srawMidpoint\", \"isNikonSraw\",\n \"isCoolscanNef\", \"isJpegThumb\", \"isFloatingPoint\", \"haveFpData\",\n \"getMetadata\", \"getImageSize\", \"getAdvancedMetadata\", \"getLensInfo\",\n \"getColorInfo\", \"setOutputParams\", \"getOutputParams\", \"getLastError\",\n \"strerror\", \"writePPM\", \"writeTIFF\", \"writeThumbnail\",\n \"getRawImageBuffer\",\n] as const;\n\ninterface QueueTarget {\n enqueue(\n name: string,\n values: unknown[],\n options?: OperationOptions,\n ): Promise;\n}\n\nexport function installForwardedOperations(\n prototype: object,\n): void {\n for (const operation of forwardedOperations) {\n Object.defineProperty(prototype, operation, {\n configurable: true,\n value: function (this: QueueTarget, ...args: unknown[]) {\n const maybeOptions = args.at(-1);\n const options =\n maybeOptions &&\n typeof maybeOptions === \"object\" &&\n \"signal\" in maybeOptions\n ? 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code: \"INVALID_PROCESSED_IMAGE\",\n operation: \"createPPMBuffer\",\n state,\n });\n }\n const pixelData = Buffer.allocUnsafe(pixels * 3 * bytesPerSample);\n for (let pixel = 0; pixel < pixels; pixel++) {\n const source = pixel * sourceStride;\n const destination = pixel * 3 * bytesPerSample;\n for (let channel = 0; channel < 3; channel++) {\n if (image.bits === 8) {\n pixelData[destination + channel] = image.data[source + channel]!;\n } else if (os.endianness() === \"LE\") {\n pixelData[destination + channel * 2] =\n image.data[source + channel * 2 + 1]!;\n pixelData[destination + channel * 2 + 1] =\n image.data[source + channel * 2]!;\n } else {\n pixelData[destination + channel * 2] =\n image.data[source + channel * 2]!;\n pixelData[destination + channel * 2 + 1] =\n image.data[source + channel * 2 + 1]!;\n }\n }\n }\n const header = Buffer.from(\n `P6\\n${image.width} ${image.height}\\n${image.bits === 16 ? 65535 : 255}\\n`,\n );\n const data = Buffer.concat([header, 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