diff --git a/biome.jsonc b/biome.jsonc
index 8a62a1d..701cd05 100644
--- a/biome.jsonc
+++ b/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"]
   }
-}
\ No newline at end of file
+}
diff --git a/bun.lockb b/bun.lockb
index 751f510..cfd4162 100755
Binary files a/bun.lockb and b/bun.lockb differ
diff --git a/examples/browser/browser.ts b/examples/browser/browser.ts
index 7506b66..095a91d 100644
--- a/examples/browser/browser.ts
+++ b/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) {
diff --git a/examples/browser/package.json b/examples/browser/package.json
index 9c16ec4..94b5837 100644
--- a/examples/browser/package.json
+++ b/examples/browser/package.json
@@ -3,4 +3,4 @@
   "dependencies": {
     "@gutenye/ocr-browser": "worksapce:*"
   }
-}
\ No newline at end of file
+}
diff --git a/examples/node/node.ts b/examples/node/node.ts
index dbd4299..b3b5dbe 100644
--- a/examples/node/node.ts
+++ b/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()
diff --git a/examples/node/package.json b/examples/node/package.json
index ad098b5..6e271aa 100644
--- a/examples/node/package.json
+++ b/examples/node/package.json
@@ -1,7 +1,7 @@
 {
-	"name": "node-example",
-	"type": "module",
-	"dependencies": {
-		"@gutenye/ocr-node": "^1.0.0"
-	}
-}
\ No newline at end of file
+  "name": "node-example",
+  "type": "module",
+  "dependencies": {
+    "@gutenye/ocr-node": "^1.0.0"
+  }
+}
diff --git a/examples/react-native/App.tsx b/examples/react-native/App.tsx
index a458267..e6fda39 100644
--- a/examples/react-native/App.tsx
+++ b/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'
diff --git a/examples/react-native/babel.config.js b/examples/react-native/babel.config.js
index 2900afe..9f057ea 100644
--- a/examples/react-native/babel.config.js
+++ b/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'],
-  };
-};
+  }
+}
diff --git a/examples/react-native/package.json b/examples/react-native/package.json
index 62e5e57..0adec52 100644
--- a/examples/react-native/package.json
+++ b/examples/react-native/package.json
@@ -24,4 +24,4 @@
     "typescript": "^5.1.3"
   },
   "private": true
-}
\ No newline at end of file
+}
diff --git a/index.ts b/index.ts
deleted file mode 100644
index f67b2c6..0000000
--- a/index.ts
+++ /dev/null
@@ -1 +0,0 @@
-console.log("Hello via Bun!");
\ No newline at end of file
diff --git a/package.json b/package.json
index 3642ba7..801af67 100644
--- a/package.json
+++ b/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"
   }
-}
\ No newline at end of file
+}
diff --git a/packages/browser/package.json b/packages/browser/package.json
index 62761e3..9fe9df0 100644
--- a/packages/browser/package.json
+++ b/packages/browser/package.json
@@ -13,12 +13,7 @@
     "bun": "./src/index.ts",
     "default": "./build/index.js"
   },
-  "files": [
-    "src",
-    "build",
-    "tsconfig.json",
-    "!**/__tests__"
-  ],
+  "files": ["src", "build", "tsconfig.json", "!**/__tests__"],
   "scripts": {
     "prepublishOnly": "./ake build"
   },
@@ -26,4 +21,4 @@
     "@gutenye/ocr-common": "^1.2.0",
     "onnxruntime-web": "^1.17.3"
   }
-}
\ No newline at end of file
+}
diff --git a/packages/browser/src/ImageRaw.ts b/packages/browser/src/ImageRaw.ts
index a8637fa..e30427a 100644
--- a/packages/browser/src/ImageRaw.ts
+++ b/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')
@@ -92,24 +89,14 @@ 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
@@ -117,9 +104,7 @@ function canvasPutImageData(
 }
 
 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) {
diff --git a/packages/browser/src/index.ts b/packages/browser/src/index.ts
index 1c513ea..3de4ef4 100644
--- a/packages/browser/src/index.ts
+++ b/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 })
 
diff --git a/packages/common/package.json b/packages/common/package.json
index 535d305..cc6c34e 100644
--- a/packages/common/package.json
+++ b/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"
   }
-}
\ No newline at end of file
+}
diff --git a/packages/common/src/Ocr.ts b/packages/common/src/Ocr.ts
index 498b661..80c9187 100644
--- a/packages/common/src/Ocr.ts
+++ b/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({
diff --git a/packages/common/src/backend/backend.ts b/packages/common/src/backend/backend.ts
index e3dca72..e676186 100644
--- a/packages/common/src/backend/backend.ts
+++ b/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
diff --git a/packages/common/src/models/Detection.ts b/packages/common/src/models/Detection.ts
index 7067188..06f28c7 100644
--- a/packages/common/src/models/Detection.ts
+++ b/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 }
 }
 
diff --git a/packages/common/src/models/ModelBase.ts b/packages/common/src/models/ModelBase.ts
index a7e08c6..1eaa77b 100644
--- a/packages/common/src/models/ModelBase.ts
+++ b/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[] = []
diff --git a/packages/common/src/models/Recognition.ts b/packages/common/src/models/Recognition.ts
index cd88d11..c1eb580 100644
--- a/packages/common/src/models/Recognition.ts
+++ b/packages/common/src/models/Recognition.ts
@@ -1,12 +1,7 @@
+import type { Tensor } from 'onnxruntime-common'
 import { FileUtils, InferenceSession } from '#/backend'
-import { Tensor } from 'onnxruntime-common'
+import type { Dictionary, Line, LineImage, ModelBaseConstructorArgs } from '#/types'
 import { ModelBase } from './ModelBase'
-import type {
-  LineImage,
-  Line,
-  Dictionary,
-  ModelBaseConstructorArgs,
-} from '#/types'
 
 export class Recognition extends ModelBase {
   #dictionary: Dictionary
@@ -69,8 +64,8 @@ export class Recognition extends ModelBase {
 
   decodeText(output: Tensor) {
     const data = output
-    let predLen = data.dims[2]
-    let line: Line[] = []
+    const predLen = data.dims[2]
+    const line: Line[] = []
     let ml = data.dims[0] - 1
     for (let l = 0; l < data.data.length; l += predLen * data.dims[1]) {
       const predsIdx: number[] = []
@@ -78,7 +73,7 @@ export class Recognition extends ModelBase {
 
       for (let i = l; i < l + predLen * data.dims[1]; i += predLen) {
         const tmpArr = data.data.slice(i, i + predLen) as Float32Array
-        const tmpMax = tmpArr.reduce((a, b) => Math.max(a, b), -Infinity)
+        const tmpMax = tmpArr.reduce((a, b) => Math.max(a, b), Number.NEGATIVE_INFINITY)
         const tmpIdx = tmpArr.indexOf(tmpMax)
         predsProb.push(tmpMax)
         predsIdx.push(tmpIdx)
@@ -90,12 +85,7 @@ export class Recognition extends ModelBase {
   }
 }
 
-function decode(
-  dictionary: string[],
-  textIndex: number[],
-  textProb: number[],
-  isRemoveDuplicate: boolean,
-) {
+function decode(dictionary: string[], textIndex: number[], textProb: number[], isRemoveDuplicate: boolean) {
   const ignoredTokens = [0]
   const charList = []
   const confList = []
@@ -137,9 +127,9 @@ function calculateBox({
 }) {
   let mainLine = lines
   const box = lineImages
-  for (let i in mainLine) {
-    let b = box[mainLine.length - Number(i) - 1].box
-    for (let p of b) {
+  for (const i in mainLine) {
+    const b = box[mainLine.length - Number(i) - 1].box
+    for (const p of b) {
       p[0] = p[0]
       p[1] = p[1]
     }
@@ -151,9 +141,9 @@ function calculateBox({
 }
 
 function afAfRec(l: Line[]) {
-  let line: Line[] = []
-  let ind: Map<BoxType, number> = new Map()
-  for (let i in l) {
+  const line: Line[] = []
+  const ind: Map<BoxType, number> = new Map()
+  for (const i in l) {
     ind.set(l[i].box, Number(i))
   }
 
@@ -198,13 +188,13 @@ function afAfRec(l: Line[]) {
     return result
   }
 
-  let boxes = groupBoxesByMidlineDifference([...ind.keys()])
+  const boxes = groupBoxesByMidlineDifference([...ind.keys()])
 
-  for (let i of boxes) {
-    let t = []
+  for (const i of boxes) {
+    const t = []
     let m = 0
-    for (let j of i) {
-      let x = l[ind.get(j)]
+    for (const j of i) {
+      const x = l[ind.get(j)]
       t.push(x.text)
       m += x.mean
     }
diff --git a/packages/common/src/splitIntoLineImages.ts b/packages/common/src/splitIntoLineImages.ts
index 4dfced7..317ffc4 100644
--- a/packages/common/src/splitIntoLineImages.ts
+++ b/packages/common/src/splitIntoLineImages.ts
@@ -1,5 +1,5 @@
-import clipper from 'js-clipper'
 import cv from '@techstark/opencv-js'
+import clipper from 'js-clipper'
 import { ImageRaw } from '#/backend'
 import type { LineImage } from '#/types'
 
@@ -7,48 +7,34 @@ type pointType = [number, number]
 type BoxType = [pointType, pointType, pointType, pointType]
 type pointsType = pointType[]
 
-export async function splitIntoLineImages(
-  image: ImageRaw,
-  sourceImage: ImageRaw,
-): Promise<LineImage[]> {
+export async function splitIntoLineImages(image: ImageRaw, sourceImage: ImageRaw): Promise<LineImage[]> {
   const w = image.width
   const h = image.height
   const srcData = sourceImage
 
-  let edgeRect: { box: BoxType; image: ImageRaw }[] = []
+  const edgeRect: { box: BoxType; image: ImageRaw }[] = []
 
-  let src = cvImread(image)
+  const src = cvImread(image)
 
   cv.cvtColor(src, src, cv.COLOR_RGBA2GRAY, 0)
-  let contours = new cv.MatVector()
-  let hierarchy = new cv.Mat()
+  const contours = new cv.MatVector()
+  const hierarchy = new cv.Mat()
 
-  cv.findContours(
-    src,
-    contours,
-    hierarchy,
-    cv.RETR_LIST,
-    cv.CHAIN_APPROX_SIMPLE,
-  )
+  cv.findContours(src, contours, hierarchy, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
 
   for (let i = 0; i < contours.size(); i++) {
-    let minSize = 3
-    let cnt = contours.get(i)
-    let { points, sside } = getMiniBoxes(cnt)
+    const minSize = 3
+    const cnt = contours.get(i)
+    const { points, sside } = getMiniBoxes(cnt)
     if (sside < minSize) continue
     // TODO sort fast
 
-    let clipBox = unclip(points)
+    const clipBox = unclip(points)
 
-    const boxMap = new cv.matFromArray(
-      clipBox.length / 2,
-      1,
-      cv.CV_32SC2,
-      clipBox,
-    )
+    const boxMap = new cv.matFromArray(clipBox.length / 2, 1, cv.CV_32SC2, clipBox)
 
     const resultObj = getMiniBoxes(boxMap)
-    let box = resultObj.points
+    const box = resultObj.points
     if (resultObj.sside < minSize + 2) {
       continue
     }
@@ -56,24 +42,24 @@ export async function splitIntoLineImages(
       return Math.max(min, Math.min(n, max))
     }
 
-    let rx = srcData.width / w
-    let ry = srcData.height / h
+    const rx = srcData.width / w
+    const ry = srcData.height / h
 
     for (let i = 0; i < box.length; i++) {
       box[i][0] *= rx
       box[i][1] *= ry
     }
 
-    let box1 = orderPointsClockwise(box)
+    const box1 = orderPointsClockwise(box)
     box1.forEach((item) => {
       item[0] = clip(Math.round(item[0]), 0, srcData.width)
       item[1] = clip(Math.round(item[1]), 0, srcData.height)
     })
-    let rect_width = int(linalgNorm(box1[0], box1[1]))
-    let rect_height = int(linalgNorm(box1[0], box1[3]))
+    const rect_width = int(linalgNorm(box1[0], box1[1]))
+    const rect_height = int(linalgNorm(box1[0], box1[3]))
     if (rect_width <= 3 || rect_height <= 3) continue
 
-    let c = getRotateCropImage(srcData, box)
+    const c = getRotateCropImage(srcData, box)
 
     edgeRect.push({
       box,
@@ -90,9 +76,9 @@ export async function splitIntoLineImages(
 
 function getMiniBoxes(contour: any) {
   const boundingBox = cv.minAreaRect(contour)
-  const points = Array.from(
-    boxPoints(boundingBox.center, boundingBox.size, boundingBox.angle),
-  ).sort((a, b) => a[0] - b[0]) as pointsType
+  const points = Array.from(boxPoints(boundingBox.center, boundingBox.size, boundingBox.angle)).sort(
+    (a, b) => a[0] - b[0],
+  ) as pointsType
 
   let index_1 = 0,
     index_2 = 1,
@@ -113,12 +99,7 @@ function getMiniBoxes(contour: any) {
     index_3 = 2
   }
 
-  const box = [
-    points[index_1],
-    points[index_2],
-    points[index_3],
-    points[index_4],
-  ] as BoxType
+  const box = [points[index_1], points[index_2], points[index_3], points[index_4]] as BoxType
   const side = Math.min(boundingBox.size.height, boundingBox.size.width)
   return { points: box, sside: side }
 }
@@ -139,11 +120,7 @@ function unclip(box: pointsType) {
     tmpArr.push(obj)
   })
   const offset = new clipper.ClipperOffset()
-  offset.AddPath(
-    tmpArr,
-    clipper.JoinType.jtRound,
-    clipper.EndType.etClosedPolygon,
-  )
+  offset.AddPath(tmpArr, clipper.JoinType.jtRound, clipper.EndType.etClosedPolygon)
   const expanded: { X: number; Y: number }[][] = []
   offset.Execute(expanded, distance)
   let expandedArr: pointsType = []
@@ -182,18 +159,8 @@ function int(num: number) {
 }
 
 function getRotateCropImage(imageRaw: ImageRaw, points: BoxType): ImageRaw {
-  const img_crop_width = int(
-    Math.max(
-      linalgNorm(points[0], points[1]),
-      linalgNorm(points[2], points[3]),
-    ),
-  )
-  const img_crop_height = int(
-    Math.max(
-      linalgNorm(points[0], points[3]),
-      linalgNorm(points[1], points[2]),
-    ),
-  )
+  const img_crop_width = int(Math.max(linalgNorm(points[0], points[1]), linalgNorm(points[2], points[3])))
+  const img_crop_height = int(Math.max(linalgNorm(points[0], points[3]), linalgNorm(points[1], points[2])))
   const pts_std = [
     [0, 0],
     [img_crop_width, 0],
@@ -210,15 +177,7 @@ function getRotateCropImage(imageRaw: ImageRaw, points: BoxType): ImageRaw {
   const dst = new cv.Mat()
   const dsize = new cv.Size(img_crop_width, img_crop_height)
   // 透视转换
-  cv.warpPerspective(
-    src,
-    dst,
-    M,
-    dsize,
-    cv.INTER_CUBIC,
-    cv.BORDER_REPLICATE,
-    new cv.Scalar(),
-  )
+  cv.warpPerspective(src, dst, M, dsize, cv.INTER_CUBIC, cv.BORDER_REPLICATE, new cv.Scalar())
 
   const dst_img_height = dst.matSize[0]
   const dst_img_width = dst.matSize[1]
@@ -229,15 +188,7 @@ function getRotateCropImage(imageRaw: ImageRaw, points: BoxType): ImageRaw {
     const dsize_rot = new cv.Size(dst.rows, dst.cols)
     const center = new cv.Point(dst.cols / 2, dst.cols / 2)
     const M = cv.getRotationMatrix2D(center, 90, 1)
-    cv.warpAffine(
-      dst,
-      dst_rot,
-      M,
-      dsize_rot,
-      cv.INTER_CUBIC,
-      cv.BORDER_REPLICATE,
-      new cv.Scalar(),
-    )
+    cv.warpAffine(dst, dst_rot, M, dsize_rot, cv.INTER_CUBIC, cv.BORDER_REPLICATE, new cv.Scalar())
   }
 
   src.delete()
@@ -250,11 +201,7 @@ function getRotateCropImage(imageRaw: ImageRaw, points: BoxType): ImageRaw {
   return cvImshow(dst_rot || dst)
 }
 
-function boxPoints(
-  center: { x: number; y: number },
-  size: { width: number; height: number },
-  angle: number,
-) {
+function boxPoints(center: { x: number; y: number }, size: { width: number; height: number }, angle: number) {
   const width = size.width
   const height = size.height
 
diff --git a/packages/common/src/types/types.ts b/packages/common/src/types/types.ts
index 7f76488..b12d09c 100644
--- a/packages/common/src/types/types.ts
+++ b/packages/common/src/types/types.ts
@@ -1,5 +1,5 @@
-import { ImageRawBase as ImageRaw } from '#/backend/ImageRawBase'
 import { InferenceSession } from 'onnxruntime-common'
+import { ImageRawBase as ImageRaw } from '#/backend/ImageRawBase'
 
 export { FileUtilsBase as FileUtils } from '#/backend/FileUtilsBase'
 export { ImageRaw, InferenceSession }
diff --git a/packages/common/src/use-default-models.node.ts b/packages/common/src/use-default-models.node.ts
index 0102cd1..f6cfb6b 100644
--- a/packages/common/src/use-default-models.node.ts
+++ b/packages/common/src/use-default-models.node.ts
@@ -9,8 +9,5 @@ export default function useDefaultModels() {
 }
 
 function resolve(path: string) {
-  return filePath.resolve(
-    filePath.dirname(fileURLToPath(import.meta.url)),
-    path,
-  )
+  return filePath.resolve(filePath.dirname(fileURLToPath(import.meta.url)), path)
 }
diff --git a/packages/node/package.json b/packages/node/package.json
index d6f2151..2510ac6 100644
--- a/packages/node/package.json
+++ b/packages/node/package.json
@@ -13,12 +13,7 @@
     "bun": "./src/index.ts",
     "default": "./build/index.js"
   },
-  "files": [
-    "src",
-    "build",
-    "tsconfig.json",
-    "!**/__tests__"
-  ],
+  "files": ["src", "build", "tsconfig.json", "!**/__tests__"],
   "scripts": {
     "prepublishOnly": "./ake build"
   },
@@ -27,4 +22,4 @@
     "onnxruntime-node": "^1.17.3-rev.1",
     "sharp": "^0.33.3"
   }
-}
\ No newline at end of file
+}
diff --git a/packages/node/src/FileUtils.ts b/packages/node/src/FileUtils.ts
index 73337fe..8fe954b 100644
--- a/packages/node/src/FileUtils.ts
+++ b/packages/node/src/FileUtils.ts
@@ -1,5 +1,5 @@
-import fs from 'fs/promises'
 import { FileUtilsBase } from '@gutenye/ocr-common'
+import fs from 'fs/promises'
 
 export class FileUtils extends FileUtilsBase {
   static async read(path: string) {
diff --git a/packages/node/src/ImageRaw.ts b/packages/node/src/ImageRaw.ts
index fbb9241..9a1526b 100644
--- a/packages/node/src/ImageRaw.ts
+++ b/packages/node/src/ImageRaw.ts
@@ -1,7 +1,7 @@
-import sharp from 'sharp'
 import filePath from 'node:path'
 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 sharp from 'sharp'
 
 export class ImageRaw extends ImageRawBase {
   #sharp: sharp.Sharp
@@ -41,9 +41,7 @@ export class ImageRaw extends ImageRawBase {
           .join('\n')}
       </svg>
     `
-    return this.#apply(
-      this.#sharp.composite([{ input: Buffer.from(svg), left: 0, top: 0 }]),
-    )
+    return this.#apply(this.#sharp.composite([{ input: Buffer.from(svg), left: 0, top: 0 }]))
   }
 
   async #apply(sharp: sharp.Sharp) {
diff --git a/packages/node/src/index.ts b/packages/node/src/index.ts
index 8c9348d..e6be5a6 100644
--- a/packages/node/src/index.ts
+++ b/packages/node/src/index.ts
@@ -1,8 +1,8 @@
 import Ocr, { registerBackend } from '@gutenye/ocr-common'
 import useDefaultModels from '@gutenye/ocr-common/use-default-models.node'
+import { InferenceSession } from 'onnxruntime-node'
 import { FileUtils } from './FileUtils'
 import { ImageRaw } from './ImageRaw'
-import { InferenceSession } from 'onnxruntime-node'
 
 useDefaultModels()
 registerBackend({ FileUtils, ImageRaw, InferenceSession })
diff --git a/packages/react-native/package.json b/packages/react-native/package.json
index 967640e..b0c3f8c 100644
--- a/packages/react-native/package.json
+++ b/packages/react-native/package.json
@@ -13,12 +13,7 @@
     "react-native": "./src/index.ts",
     "default": "./build/index.js"
   },
-  "files": [
-    "src",
-    "build",
-    "tsconfig.json",
-    "!**/__tests__"
-  ],
+  "files": ["src", "build", "tsconfig.json", "!**/__tests__"],
   "scripts": {
     "prepublishOnly": "./ake build"
   },
diff --git a/packages/react-native/src/ImageRaw.ts b/packages/react-native/src/ImageRaw.ts
index 29b3ef6..7af7440 100644
--- a/packages/react-native/src/ImageRaw.ts
+++ b/packages/react-native/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'
 
 export class ImageRaw extends ImageRawBase {
   static async open(path: string): Promise<ImageRaw> {}
diff --git a/packages/react-native/src/index.ts b/packages/react-native/src/index.ts
index 50a54b1..f80794c 100644
--- a/packages/react-native/src/index.ts
+++ b/packages/react-native/src/index.ts
@@ -1,7 +1,7 @@
 import Ocr, { registerBackend } from '@gutenye/ocr-common'
+import { InferenceSession } from 'onnxruntime-react-native'
 import { FileUtils } from './FileUtils'
 import { ImageRaw } from './ImageRaw'
-import { InferenceSession } from 'onnxruntime-react-native'
 
 registerBackend({ FileUtils, ImageRaw, InferenceSession })