run format & lint

biome.jsonc

@@ -3,6 +3,10 @@
   "organizeImports": {
     "enabled": true
   },
+  "formatter": {
+    "indentStyle": "space",
+    "lineWidth": 120
+  },
   "linter": {
     "enabled": true,
     "rules": {
@@ -14,5 +18,13 @@
       "quoteStyle": "single",
       "semicolons": "asNeeded"
     }
+  },
+  "vcs": {
+    "enabled": true,
+    "clientKind": "git",
+    "useIgnoreFile": true
+  },
+  "files": {
+    "ignore": ["ios", "android"]
   }
-}
+}

examples/browser/browser.ts

@@ -29,12 +29,8 @@ function createApp(
 ) {
   const resultTextEl = document.querySelector('#result-text') as HTMLDivElement
   const performanceEl = document.querySelector('#performance') as HTMLDivElement
-  const resultImageEl = document.querySelector(
-    '#result-image',
-  ) as HTMLImageElement
-  const inputImageEl = document.querySelector(
-    '#input-image',
-  ) as HTMLImageElement
+  const resultImageEl = document.querySelector('#result-image') as HTMLImageElement
+  const inputImageEl = document.querySelector('#input-image') as HTMLImageElement
   inputImageEl.addEventListener('change', async (event) => {
     const file = (event.target as HTMLInputElement).files?.[0]
     if (!file) {

examples/browser/package.json

@@ -3,4 +3,4 @@
   "dependencies": {
     "@gutenye/ocr-browser": "worksapce:*"
   }
-}
+}

examples/node/node.ts

@@ -1,6 +1,6 @@
+import filePath from 'path'
 import Ocr from '@gutenye/ocr-node'
 import fs from 'fs/promises'
-import filePath from 'path'
 
 async function main() {
   const ocr = await Ocr.create()

examples/node/package.json

@@ -1,7 +1,7 @@
 {
-	"name": "node-example",
-	"type": "module",
-	"dependencies": {
-		"@gutenye/ocr-node": "^1.0.0"
-	}
-}
+  "name": "node-example",
+  "type": "module",
+  "dependencies": {
+    "@gutenye/ocr-node": "^1.0.0"
+  }
+}

examples/react-native/App.tsx

@@ -1,6 +1,6 @@
 import camera from 'expo-camera'
-import * as ort from 'onnxruntime-react-native'
 import { StatusBar } from 'expo-status-bar'
+import * as ort from 'onnxruntime-react-native'
 import { StyleSheet, Text, View } from 'react-native'
 import { SafeAreaProvider, SafeAreaView } from 'react-native-safe-area-context'
 import { Ocr } from '../build/ocr'

examples/react-native/babel.config.js

@@ -1,6 +1,6 @@
-module.exports = function(api) {
-  api.cache(true);
+module.exports = (api) => {
+  api.cache(true)
   return {
     presets: ['babel-preset-expo'],
-  };
-};
+  }
+}

examples/react-native/package.json

@@ -24,4 +24,4 @@
     "typescript": "^5.1.3"
   },
   "private": true
-}
+}

package.json

@@ -1,11 +1,10 @@
 {
   "name": "@gutenye/ocr",
-  "workspaces": [
-    "packages/*"
-  ],
+  "workspaces": ["packages/*"],
   "devDependencies": {
+    "@biomejs/biome": "1.7.3",
     "@types/bun": "latest",
     "tsc-alias": "^1.8.8",
     "typescript": "^5.0.0"
   }
-}
+}

packages/browser/package.json

@@ -13,17 +13,12 @@
     "bun": "./src/index.ts",
     "default": "./build/index.js"
   },
-  "files": [
-    "src",
-    "build",
-    "tsconfig.json",
-    "!**/__tests__"
-  ],
+  "files": ["src", "build", "tsconfig.json", "!**/__tests__"],
   "scripts": {
     "prepublishOnly": "./ake build"
   },
   "dependencies": {
     "@gutenye/ocr-common": "^1.2.0",
     "onnxruntime-web": "^1.17.3"
   }
-}
+}

packages/browser/src/ImageRaw.ts

@@ -1,5 +1,5 @@
 import { ImageRawBase } from '@gutenye/ocr-common'
-import type { ImageRawData, SizeOption, LineImage } from '@gutenye/ocr-common'
+import type { ImageRawData, LineImage, SizeOption } from '@gutenye/ocr-common'
 import invariant from 'tiny-invariant'
 
 export class ImageRaw extends ImageRawBase {
@@ -39,10 +39,7 @@ export class ImageRaw extends ImageRawBase {
   }
 
   async resize({ width, height }: SizeOption) {
-    invariant(
-      width !== undefined || height !== undefined,
-      'both width and height are undefined',
-    )
+    invariant(width !== undefined || height !== undefined, 'both width and height are undefined')
     const newWidth = width || Math.round((this.width / this.height) * height!)
     const newHeight = height || Math.round((this.height / this.width) * width!)
     const newCanvas = document.createElement('canvas')
@@ -92,34 +89,22 @@ export class ImageRaw extends ImageRawBase {
   }
 }
 
-function canvasDrawImage(
-  canvas: HTMLCanvasElement,
-  image: CanvasImageSource,
-  width?: number,
-  height?: number,
-) {
+function canvasDrawImage(canvas: HTMLCanvasElement, image: CanvasImageSource, width?: number, height?: number) {
   canvas.width = width || image.width
   canvas.height = height || image.height
   const ctx = canvas.getContext('2d')!
   ctx.drawImage(image, 0, 0, canvas.width, canvas.height)
 }
 
-function canvasPutImageData(
-  canvas: HTMLCanvasElement,
-  imageData: ImageData,
-  width?: number,
-  height?: number,
-) {
+function canvasPutImageData(canvas: HTMLCanvasElement, imageData: ImageData, width?: number, height?: number) {
   const ctx = canvas.getContext('2d')!
   canvas.width = width || imageData.width
   canvas.height = height || imageData.height
   ctx.putImageData(imageData, 0, 0)
 }
 
 function canvasGetImageData(canvas: HTMLCanvasElement) {
-  return canvas
-    .getContext('2d')!
-    .getImageData(0, 0, canvas.width, canvas.height)
+  return canvas.getContext('2d')!.getImageData(0, 0, canvas.width, canvas.height)
 }
 
 async function imageFromUrl(url: string) {

packages/browser/src/index.ts

@@ -1,7 +1,7 @@
 import Ocr, { registerBackend } from '@gutenye/ocr-common'
+import { InferenceSession } from 'onnxruntime-web'
 import { FileUtils } from './FileUtils'
 import { ImageRaw } from './ImageRaw'
-import { InferenceSession } from 'onnxruntime-web'
 
 registerBackend({ FileUtils, ImageRaw, InferenceSession })
 

packages/common/package.json

@@ -19,13 +19,7 @@
       "default": "./build/use-default-models.node.js"
     }
   },
-  "files": [
-    "assets",
-    "src",
-    "build",
-    "tsconfig.json",
-    "!**/__tests__"
-  ],
+  "files": ["assets", "src", "build", "tsconfig.json", "!**/__tests__"],
   "scripts": {
     "prepublishOnly": "./ake build"
   },
@@ -34,4 +28,4 @@
     "js-clipper": "^1.0.1",
     "tiny-invariant": "^1.3.3"
   }
-}
+}

packages/common/src/Ocr.ts

@@ -1,5 +1,5 @@
-import { Detection, Recognition } from './models'
 import invariant from 'tiny-invariant'
+import { Detection, Recognition } from './models'
 
 export class Ocr {
   static DEFAULT_DETECTION_PATH: string
@@ -17,11 +17,9 @@ export class Ocr {
   } = {}) {
     const detectionPath = this.DEFAULT_DETECTION_PATH || models?.detectionPath
     invariant(detectionPath, 'detectionPath is required')
-    const recognitionPath =
-      this.DEFAULT_RECOGINTION_PATH || models?.recognitionPath
+    const recognitionPath = this.DEFAULT_RECOGINTION_PATH || models?.recognitionPath
     invariant(recognitionPath, 'recognitionPath is required')
-    const dictionaryPath =
-      this.DEFAULT_DICTIONARY_PATH || models?.dictionaryPath
+    const dictionaryPath = this.DEFAULT_DICTIONARY_PATH || models?.dictionaryPath
     invariant(dictionaryPath, 'dictionaryPath is required')
 
     const detection = await Detection.create({

packages/common/src/backend/backend.ts

@@ -6,8 +6,7 @@ import type {
 
 let FileUtils: FileUtilsType = undefined as unknown as FileUtilsType
 let ImageRaw: ImageRawType = undefined as unknown as ImageRawType
-let InferenceSession: InferenceSessionType =
-  undefined as unknown as InferenceSessionType
+let InferenceSession: InferenceSessionType = undefined as unknown as InferenceSessionType
 
 export function registerBackend(backend: {
   FileUtils: FileUtilsType

packages/common/src/models/Detection.ts

@@ -1,8 +1,8 @@
+import type { Tensor } from 'onnxruntime-common'
 import { ImageRaw, InferenceSession } from '#/backend'
 import { splitIntoLineImages } from '#/splitIntoLineImages'
-import { Tensor } from 'onnxruntime-common'
+import type { ModelBaseConstructorArgs, Size } from '#/types'
 import { ModelBase } from './ModelBase'
-import type { Size, ModelBaseConstructorArgs } from '#/types'
 
 const BASE_SIZE = 32
 
@@ -25,7 +25,7 @@ export class Detection extends ModelBase {
     //   - image width and height must be a multiple of 32
     //   - bigger image -> more accurate result, but takes longer time
     // inputImage = await Image.resize(image, multipleOfBaseSize(image, { maxSize: 960 }))
-    let inputImage = await image.resize(multipleOfBaseSize(image))
+    const inputImage = await image.resize(multipleOfBaseSize(image))
     this.debugImage(inputImage, './output/out1-multiple-of-base-size.jpg')
 
     // Covert image data to model data
@@ -59,10 +59,7 @@ export class Detection extends ModelBase {
   }
 }
 
-function multipleOfBaseSize(
-  image: ImageRaw,
-  { maxSize }: { maxSize?: number } = {},
-): Size {
+function multipleOfBaseSize(image: ImageRaw, { maxSize }: { maxSize?: number } = {}): Size {
   let width = image.width
   let height = image.height
   if (maxSize && Math.max(width, height) > maxSize) {
@@ -76,10 +73,7 @@ function multipleOfBaseSize(
     Math.ceil(width / BASE_SIZE) * BASE_SIZE,
     BASE_SIZE,
   )
-  const newHeight = Math.max(
-    Math.ceil(height / BASE_SIZE) * BASE_SIZE,
-    BASE_SIZE,
-  )
+  const newHeight = Math.max(Math.ceil(height / BASE_SIZE) * BASE_SIZE, BASE_SIZE)
   return { width: newWidth, height: newHeight }
 }
 

packages/common/src/models/ModelBase.ts

@@ -1,11 +1,5 @@
 import { Tensor } from 'onnxruntime-common'
-import type {
-  ModelData,
-  InferenceSession,
-  ImageRaw,
-  ReshapeOptions,
-  ModelBaseConstructorArgs,
-} from '#/types'
+import type { ImageRaw, InferenceSession, ModelBaseConstructorArgs, ModelData, ReshapeOptions } from '#/types'
 
 export class ModelBase {
   isDebug: boolean
@@ -27,18 +21,10 @@ export class ModelBase {
 
   #prepareInput(modelData: ModelData) {
     const input = Float32Array.from(modelData.data)
-    return new Tensor('float32', input, [
-      1,
-      3,
-      modelData.height,
-      modelData.width,
-    ])
+    return new Tensor('float32', input, [1, 3, modelData.height, modelData.width])
   }
 
-  imageToInput(
-    image: ImageRaw,
-    { mean = [0, 0, 0], std = [1, 1, 1] }: ReshapeOptions,
-  ): ModelData {
+  imageToInput(image: ImageRaw, { mean = [0, 0, 0], std = [1, 1, 1] }: ReshapeOptions): ModelData {
     const R: number[] = []
     const G: number[] = []
     const B: number[] = []