file-adapters
File Converter Adapters
This skill provides comprehensive guidance for using @rytass/file-converter packages to process images with resizing, format conversion, watermarking, and pipeline processing.
Overview
All adapters implement the FileConverter interface from @rytass/file-converter, providing a unified API for image processing:
| Package | Function | Based On |
|---|---|---|
@rytass/file-converter |
Core interfaces and pipeline manager (核心介面與管道管理器) | TypeScript interfaces |
@rytass/file-converter-adapter-image-resizer |
Image resizing (圖像縮放) | Sharp ^0.34.5 |
@rytass/file-converter-adapter-image-transcoder |
Format conversion (格式轉換) | Sharp ^0.34.5, file-type ^21.1.1 |
@rytass/file-converter-adapter-image-watermark |
Watermark overlay (浮水印疊加) | Sharp ^0.34.5 |
Base Interface (@rytass/file-converter)
All adapters share these core concepts:
FileConverter - Main interface for file conversion
interface FileConverter<O = Record<string, unknown>> {
convert<Buffer>(file: ConvertableFile): Promise<Buffer>;
convert<Readable>(file: ConvertableFile): Promise<Readable>;
}
ConvertableFile - Supported input types
type ConvertableFile = Readable | Buffer;
ConverterManager - Pipeline processor for chaining conversions
class ConverterManager {
constructor(converters: FileConverter[]);
convert<Output>(file: ConvertableFile): Promise<Output>;
}
Installation
# Install base package
npm install @rytass/file-converter
# Choose the adapters you need
npm install @rytass/file-converter-adapter-image-resizer
npm install @rytass/file-converter-adapter-image-transcoder
npm install @rytass/file-converter-adapter-image-watermark
Quick Start
ImageResizer (圖像縮放)
Resize images while maintaining or controlling aspect ratio:
import { ImageResizer } from '@rytass/file-converter-adapter-image-resizer';
import { readFileSync, writeFileSync } from 'fs';
// Resize to max 800x600, maintaining aspect ratio
const resizer = new ImageResizer({
maxWidth: 800,
maxHeight: 600,
keepAspectRatio: true,
concurrency: 4, // Optional: parallel processing
});
const originalImage = readFileSync('photo.jpg');
const resizedImage = await resizer.convert<Buffer>(originalImage);
writeFileSync('photo-resized.jpg', resizedImage);
ImageTranscoder (格式轉換)
Convert images between formats (JPEG, PNG, WebP, AVIF, etc.):
import { ImageTranscoder } from '@rytass/file-converter-adapter-image-transcoder';
// Convert to WebP format
const transcoder = new ImageTranscoder({
targetFormat: 'webp',
quality: 85,
effort: 4,
});
const jpegBuffer = readFileSync('photo.jpg');
const webpBuffer = await transcoder.convert<Buffer>(jpegBuffer);
writeFileSync('photo.webp', webpBuffer);
ImageWatermark (浮水印)
Add watermarks to images:
import { ImageWatermark } from '@rytass/file-converter-adapter-image-watermark';
import { gravity } from 'sharp';
// Add watermark at bottom-right corner
const watermarker = new ImageWatermark({
watermarks: [
{
image: readFileSync('logo.png'), // Can be Buffer or file path
gravity: gravity.southeast, // Position: bottom-right
},
],
});
const originalImage = readFileSync('photo.jpg');
const watermarkedImage = await watermarker.convert<Buffer>(originalImage);
writeFileSync('photo-watermarked.jpg', watermarkedImage);
ConverterManager (管道處理)
Chain multiple converters in a pipeline:
import { ConverterManager } from '@rytass/file-converter';
import { ImageResizer } from '@rytass/file-converter-adapter-image-resizer';
import { ImageWatermark } from '@rytass/file-converter-adapter-image-watermark';
import { ImageTranscoder } from '@rytass/file-converter-adapter-image-transcoder';
import { gravity } from 'sharp';
// Create processing pipeline: Resize → Watermark → Convert to WebP
const pipeline = new ConverterManager([
new ImageResizer({
maxWidth: 1200,
maxHeight: 800,
keepAspectRatio: true,
}),
new ImageWatermark({
watermarks: [
{
image: './logo.png',
gravity: gravity.southeast,
},
],
}),
new ImageTranscoder({
targetFormat: 'webp',
quality: 85,
effort: 4,
}),
]);
const originalImage = readFileSync('photo.jpg');
const processedImage = await pipeline.convert<Buffer>(originalImage);
writeFileSync('processed.webp', processedImage);
Common Patterns
Buffer vs Stream Processing
Buffer - Use for small files (小檔案), faster, uses more memory:
const buffer = readFileSync('image.jpg');
const result = await converter.convert<Buffer>(buffer);
writeFileSync('output.jpg', result);
Stream (Readable) - Use for large files (大檔案), memory efficient:
import { createReadStream, createWriteStream } from 'fs';
import { Readable } from 'stream';
const stream = createReadStream('large-image.jpg');
const resultStream = await converter.convert<Readable>(stream);
// Pipe to output
resultStream.pipe(createWriteStream('output.jpg'));
Single Conversion
Process one image with one converter:
// Resize only
const resizer = new ImageResizer({ maxWidth: 800 });
const resized = await resizer.convert<Buffer>(imageBuffer);
// Convert format only
const transcoder = new ImageTranscoder({ targetFormat: 'webp', quality: 90 });
const webp = await transcoder.convert<Buffer>(jpegBuffer);
Pipeline Conversion
Chain multiple operations:
// Three-step processing
const pipeline = new ConverterManager([
new ImageResizer({ maxWidth: 1000, maxHeight: 750 }),
new ImageWatermark({ watermarks: [{ image: 'logo.png' }] }),
new ImageTranscoder({ targetFormat: 'webp', quality: 85 }),
]);
const result = await pipeline.convert<Buffer>(originalImage);
Batch Processing
Process multiple images:
import { glob } from 'glob';
import { basename } from 'path';
const pipeline = new ConverterManager([
new ImageResizer({ maxWidth: 800 }),
new ImageTranscoder({ targetFormat: 'webp', quality: 85 }),
]);
// Find all JPEG files
const images = await glob('photos/*.jpg');
// Process all images
await Promise.all(
images.map(async (imagePath) => {
const buffer = readFileSync(imagePath);
const result = await pipeline.convert<Buffer>(buffer);
const outputName = basename(imagePath, '.jpg') + '.webp';
writeFileSync(`output/${outputName}`, result);
})
);
Feature Comparison
| Feature | ImageResizer | ImageTranscoder | ImageWatermark | ConverterManager |
|---|---|---|---|---|
| Resize Images (縮放圖片) | Yes | No | No | Via pipeline |
| Convert Formats (轉換格式) | No | Yes | No | Via pipeline |
| Add Watermarks (添加浮水印) | No | No | Yes | Via pipeline |
| Maintain Aspect Ratio (保持縱橫比) | Yes | N/A | N/A | N/A |
| Crop to Fit (裁剪適配) | Yes | No | No | N/A |
| Buffer Support (緩衝支援) | Yes | Yes | Yes | Yes |
| Stream Support (串流支援) | Yes | Yes | Yes | Yes |
| Concurrency Control (並發控制) | Yes | Yes | Yes | N/A |
| Multiple Watermarks (多浮水印) | No | No | Yes | N/A |
| Pipeline Chaining (管道串聯) | No | No | No | Yes |
Supported Formats (ImageTranscoder)
| Input Formats | Output Formats |
|---|---|
| jpg, png, webp, gif, avif, tif, svg | jpg/jpeg, png, webp, avif, heif, gif, tif/tiff |
Note: Input formats are detected by
file-typelibrary. JPEG uses 'jpg' internally.
內部常數(未導出):
SupportSources- 支援的輸入格式陣列:['jpg', 'png', 'webp', 'gif', 'avif', 'tif', 'svg']UnsupportedSource- 當輸入格式不支援時拋出的錯誤類別
ImageTranscoderOptions Types
每種輸出格式都有對應的 Sharp options:
import type { AvifOptions, GifOptions, HeifOptions, JpegOptions, PngOptions, TiffOptions, WebpOptions } from 'sharp';
type ImageTranscoderOptions =
| { targetFormat: 'avif' } & AvifOptions
| { targetFormat: 'heif' } & HeifOptions
| { targetFormat: 'gif' } & GifOptions
| { targetFormat: 'tif' | 'tiff' } & TiffOptions
| { targetFormat: 'png' } & PngOptions
| { targetFormat: 'webp' } & WebpOptions
| { targetFormat: 'jpg' | 'jpeg' } & JpegOptions;
// Constructor 額外支援 concurrency 選項
new ImageTranscoder(options: ImageTranscoderOptions & { concurrency?: number });
ImageResizerOptions
interface ImageResizerOptions {
maxWidth?: number; // 最大寬度(至少需設定 maxWidth 或 maxHeight 其一)
maxHeight?: number; // 最大高度
keepAspectRatio?: boolean; // 保持縱橫比(預設 true,使用 'inside' fit)
concurrency?: number; // 並發數(預設 1)
}
Note: 使用
withoutEnlargement: true確保不會放大小於目標尺寸的圖片。當keepAspectRatio=false時使用fit: 'cover'裁剪適配。
ImageWatermarkOptions
interface Watermark {
image: string | Buffer; // 浮水印圖片(檔案路徑或 Buffer)
gravity?: Gravity; // 位置(預設 southeast)
}
interface ImageWatermarkOptions {
watermarks: Watermark[]; // 浮水印陣列(支援多個浮水印)
concurrency?: number; // 並發數(預設 1)
}
Watermark Positions (ImageWatermark)
| Position | Gravity Constant | Description |
|---|---|---|
| Top-Left (左上) | gravity.northwest |
Northwest corner |
| Top-Center (上中) | gravity.north |
Top center |
| Top-Right (右上) | gravity.northeast |
Northeast corner |
| Middle-Left (中左) | gravity.west |
Middle left |
| Center (中央) | gravity.center |
Center |
| Middle-Right (中右) | gravity.east |
Middle right |
| Bottom-Left (左下) | gravity.southwest |
Southwest corner |
| Bottom-Center (下中) | gravity.south |
Bottom center |
| Bottom-Right (右下) | gravity.southeast |
Southeast corner (default) |
Detailed Documentation
For complete API reference and advanced usage:
- ImageResizer Complete Reference - All options, methods, and use cases
- ImageTranscoder Complete Reference - Format-specific options, error handling
- ImageWatermark Complete Reference - Watermark configuration, positioning
Complete Examples
E-commerce Product Images
Process product photos: resize for web, add branding watermark, convert to modern format:
import { ConverterManager } from '@rytass/file-converter';
import { ImageResizer } from '@rytass/file-converter-adapter-image-resizer';
import { ImageWatermark } from '@rytass/file-converter-adapter-image-watermark';
import { ImageTranscoder } from '@rytass/file-converter-adapter-image-transcoder';
import { readFileSync, writeFileSync } from 'fs';
import { gravity } from 'sharp';
// Create product image processor
const productImageProcessor = new ConverterManager([
// Step 1: Resize to 1200x1200 max
new ImageResizer({
maxWidth: 1200,
maxHeight: 1200,
keepAspectRatio: true,
concurrency: 4,
}),
// Step 2: Add brand watermark at bottom-right
new ImageWatermark({
watermarks: [
{
image: readFileSync('brand-logo.png'),
gravity: gravity.southeast,
},
],
}),
// Step 3: Convert to WebP for smaller file size
new ImageTranscoder({
targetFormat: 'webp',
quality: 85,
effort: 4, // Higher effort = better compression
}),
]);
// Process a product image
const originalPhoto = readFileSync('product-001-raw.jpg');
const processedPhoto = await productImageProcessor.convert<Buffer>(originalPhoto);
writeFileSync('product-001.webp', processedPhoto);
Large File Stream Processing
Handle large files efficiently with streams to avoid memory issues:
import { createReadStream, createWriteStream } from 'fs';
import { ImageResizer } from '@rytass/file-converter-adapter-image-resizer';
import { Readable } from 'stream';
// Create resizer
const resizer = new ImageResizer({
maxWidth: 1920,
maxHeight: 1080,
keepAspectRatio: true,
});
// Process large file using streams
const inputStream = createReadStream('large-photo.jpg');
const outputStream = await resizer.convert<Readable>(inputStream);
// Pipe to output file
outputStream.pipe(createWriteStream('large-photo-resized.jpg'));
// Wait for completion
await new Promise((resolve, reject) => {
outputStream.on('finish', resolve);
outputStream.on('error', reject);
});
Batch Processing with Progress Tracking
Process multiple images with progress updates:
import { glob } from 'glob';
import { basename } from 'path';
import { ConverterManager } from '@rytass/file-converter';
import { ImageResizer } from '@rytass/file-converter-adapter-image-resizer';
import { ImageTranscoder } from '@rytass/file-converter-adapter-image-transcoder';
// Create pipeline
const pipeline = new ConverterManager([
new ImageResizer({ maxWidth: 800, maxHeight: 600, keepAspectRatio: true }),
new ImageTranscoder({ targetFormat: 'webp', quality: 80 }),
]);
// Find all images
const images = await glob('input-photos/*.{jpg,png,jpeg}');
const total = images.length;
let processed = 0;
console.log(`Found ${total} images to process`);
// Process with progress tracking
for (const imagePath of images) {
const buffer = readFileSync(imagePath);
const result = await pipeline.convert<Buffer>(buffer);
const outputName = basename(imagePath).replace(/\.(jpg|png|jpeg)$/, '.webp');
writeFileSync(`output/${outputName}`, result);
processed++;
console.log(`Progress: ${processed}/${total} (${Math.round((processed / total) * 100)}%)`);
}
console.log('All images processed successfully!');
Conditional Processing
Apply different processing based on image properties:
import sharp from 'sharp';
import { ImageResizer } from '@rytass/file-converter-adapter-image-resizer';
import { ImageTranscoder } from '@rytass/file-converter-adapter-image-transcoder';
import { ConverterManager } from '@rytass/file-converter';
async function processImage(inputBuffer: Buffer): Promise<Buffer> {
// Get image metadata
const metadata = await sharp(inputBuffer).metadata();
if (!metadata.width || !metadata.height) {
throw new Error('Unable to read image dimensions');
}
// For large images: resize first
if (metadata.width > 2000 || metadata.height > 2000) {
console.log('Large image detected, resizing...');
const pipeline = new ConverterManager([
new ImageResizer({ maxWidth: 1600, maxHeight: 1600, keepAspectRatio: true }),
new ImageTranscoder({ targetFormat: 'webp', quality: 85 }),
]);
return pipeline.convert<Buffer>(inputBuffer);
}
// For small images: just convert format
console.log('Small image detected, converting format only...');
const transcoder = new ImageTranscoder({ targetFormat: 'webp', quality: 90 });
return transcoder.convert<Buffer>(inputBuffer);
}
// Usage
const imageBuffer = readFileSync('photo.jpg');
const result = await processImage(imageBuffer);
writeFileSync('output.webp', result);
Troubleshooting
Common Issues
Memory Errors with Large Images
- Solution: Use Stream processing instead of Buffer
// Instead of Buffer
const buffer = readFileSync('huge-image.jpg');
const result = await converter.convert<Buffer>(buffer);
// Use Stream
const stream = createReadStream('huge-image.jpg');
const resultStream = await converter.convert<Readable>(stream);
Sharp Cache Issues
- Sharp automatically disables cache in all adapters with
sharp.cache(false) - No action needed
Concurrency Performance
- Adjust
concurrencyoption based on your CPU cores - Default is 1 (single-threaded)
- Try 4-8 for multi-core systems
const resizer = new ImageResizer({
maxWidth: 800,
concurrency: 8, // Adjust based on CPU cores
});
Unsupported Format Errors (ImageTranscoder)
- Check input format is supported: JPEG, PNG, WebP, GIF, AVIF, TIFF, SVG
- Error will throw
UnsupportedSourceexception (internal class, catch usinginstanceof Errorand checkmessage === 'UnsupportedSource')
Output Quality Issues
- Increase
qualityparameter (0-100) - For WebP/AVIF, increase
effort(0-9) for better compression
const transcoder = new ImageTranscoder({
targetFormat: 'webp',
quality: 95, // Higher quality
effort: 6, // More compression effort
});