mirror of
https://wget.la/https://github.com/Wxw-Gu/WechatExplorer
synced 2026-10-04 03:01:42 +08:00
- 图片文字索引性能与进度诚实化 - 问问微信:证据卡区分「消息类型」与「派生来源」,派生命中内容自报来源 - 问问微信:回答规则禁止未真实执行的多轮承诺 - 本地图片文字识别:支持 macOS 系统 OCR(Apple Vision)
132 lines
5.6 KiB
TypeScript
132 lines
5.6 KiB
TypeScript
// 【macOS】System OCR native fidelity。
|
||
//
|
||
// capability-gated 的原生冒烟测试:只有在「macOS + native 运行时可用」时才真正跑。
|
||
// macOS 的 Apple Vision 后端没有"语言包缺失"这一失败模式,所以门槛只有运行时本身;
|
||
// mock 单元测试仍然是 mandatory(tests/unit/system-ocr-service.test.ts)。
|
||
//
|
||
// 这里断言的是 **macOS 专有**的性质,与 system-ocr-windows.test.ts 刻意不同:
|
||
// - 引擎标识是 macos-system-ocr;
|
||
// - 不做任何图片归一化:Vision 原生接受 PNG / JPEG,不得转码、不得起 ffmpeg;
|
||
// - capability.language 恒为 null(识别语言由 Vision 决定);
|
||
// - line.confidence 是 Vision 的真实置信度,不像 Windows 恒为 1.0。
|
||
//
|
||
// fixture 全部是 synthetic 图片(tests/fixtures/ocr/*),不含任何真实聊天数据。
|
||
|
||
import { readFileSync } from 'node:fs'
|
||
import { join } from 'node:path'
|
||
import { describe, expect, it, vi } from 'vitest'
|
||
import { SYSTEM_OCR_ENGINE_MACOS } from '../../src/shared/system-ocr'
|
||
|
||
vi.mock('../../src/main/image-decrypt-service', () => ({
|
||
resolveFfmpegExecutable: (): string => 'ffmpeg'
|
||
}))
|
||
|
||
import { SystemOcrService, systemOcrService } from '../../src/main/services/system-ocr-service'
|
||
|
||
const fixtureDirectory = join(__dirname, '..', 'fixtures', 'ocr')
|
||
|
||
const toDataUrl = (fileName: string, mimeType: string): string =>
|
||
`data:${mimeType};base64,${readFileSync(join(fixtureDirectory, fileName)).toString('base64')}`
|
||
|
||
/** 只比较"主要 token",避免识别微差造成脆弱测试。 */
|
||
const expectContainsTokens = (text: string, tokens: string[]): void => {
|
||
const normalized = text.replace(/[\s\u3000]+/g, '').toLowerCase()
|
||
for (const token of tokens) {
|
||
expect(normalized).toContain(token.replace(/[\s\u3000]+/g, '').toLowerCase())
|
||
}
|
||
}
|
||
|
||
const capability = await systemOcrService.getCapability()
|
||
const onMac = process.platform === 'darwin'
|
||
const platformGate = onMac ? it : it.skip
|
||
const nativeGate = onMac && capability.available ? it : it.skip
|
||
|
||
/**
|
||
* 走「真实 process.platform/arch + 真实 native binding + 默认归一化路径」的实例,
|
||
* 只把 ffmpeg 解析器换成 spy —— 用来证明 macOS 路径根本没有碰归一化。
|
||
*/
|
||
const ffmpegResolver = vi.fn(() => 'ffmpeg')
|
||
const nativeService = new SystemOcrService({ resolveFfmpegExecutable: ffmpegResolver })
|
||
|
||
describe('macOS System OCR native fidelity', () => {
|
||
platformGate('reports a usable capability backed by Apple Vision', () => {
|
||
expect(capability.engine).toBe(SYSTEM_OCR_ENGINE_MACOS)
|
||
expect(capability.platform).toBe('darwin')
|
||
expect(capability.runtimeVersion).not.toBeNull()
|
||
// Vision 自行决定识别语言,不声称任何语言包。
|
||
expect(capability.language).toBeNull()
|
||
if (!capability.available) {
|
||
console.warn(`[integration] macOS System OCR smoke skipped: ${capability.message}`)
|
||
}
|
||
})
|
||
|
||
nativeGate('recognizes simplified Chinese text', async () => {
|
||
const result = await nativeService.recognize({
|
||
imageDataUrl: toDataUrl('system-ocr-zh.png', 'image/png')
|
||
})
|
||
expect(result.success).toBe(true)
|
||
expectContainsTokens(result.text, ['TraceMemo', '本地', '文字', '识别'])
|
||
expect(result.language).toBeNull()
|
||
expect(result.durationMs).toBeGreaterThan(0)
|
||
})
|
||
|
||
nativeGate('recognizes English text', async () => {
|
||
const result = await nativeService.recognize({
|
||
imageDataUrl: toDataUrl('system-ocr-en.png', 'image/png')
|
||
})
|
||
expect(result.success).toBe(true)
|
||
expectContainsTokens(result.text, ['TraceMemo', 'System', 'OCR'])
|
||
})
|
||
|
||
nativeGate('recognizes mixed Chinese/English text', async () => {
|
||
const result = await nativeService.recognize({
|
||
imageDataUrl: toDataUrl('system-ocr-mixed.png', 'image/png')
|
||
})
|
||
expect(result.success).toBe(true)
|
||
expectContainsTokens(result.text, ['TraceMemo', '本地', 'OCR', '2026'])
|
||
})
|
||
|
||
/**
|
||
* Vision 原生接受 JPEG —— 这条用例同时是「macOS 不做归一化」的回归保护:
|
||
* 一旦有人把 Windows 的 PNG-only 假设搬过来,ffmpeg 解析器就会被调用。
|
||
*/
|
||
nativeGate('accepts JPEG directly without any image normalization', async () => {
|
||
ffmpegResolver.mockClear()
|
||
const result = await nativeService.recognize({
|
||
imageDataUrl: toDataUrl('system-ocr-mixed.jpg', 'image/jpeg')
|
||
})
|
||
expect(result.success).toBe(true)
|
||
expectContainsTokens(result.text, ['TraceMemo', 'OCR', '2026'])
|
||
expect(ffmpegResolver).not.toHaveBeenCalled()
|
||
})
|
||
|
||
nativeGate('reports real Vision confidence and top-left-origin boxes', async () => {
|
||
const result = await nativeService.recognize({
|
||
imageDataUrl: toDataUrl('system-ocr-mixed.png', 'image/png')
|
||
})
|
||
expect(result.success).toBe(true)
|
||
expect(result.lines.length).toBeGreaterThan(0)
|
||
for (const line of result.lines) {
|
||
// Windows 恒为 1.0;macOS 必须给出真实置信度。
|
||
expect(line.confidence).toBeGreaterThanOrEqual(0)
|
||
expect(line.confidence).toBeLessThanOrEqual(1)
|
||
const { x, y, width, height } = line.boundingBox
|
||
for (const value of [x, y, width, height]) {
|
||
expect(Number.isFinite(value)).toBe(true)
|
||
}
|
||
expect(x).toBeGreaterThanOrEqual(0)
|
||
expect(y).toBeGreaterThanOrEqual(0)
|
||
expect(x + width).toBeLessThanOrEqual(1.0001)
|
||
expect(y + height).toBeLessThanOrEqual(1.0001)
|
||
}
|
||
})
|
||
|
||
nativeGate('caches an identical repeat request', async () => {
|
||
const request = { imageDataUrl: toDataUrl('system-ocr-en.png', 'image/png') }
|
||
const first = await systemOcrService.recognize(request)
|
||
const second = await systemOcrService.recognize(request)
|
||
expect(first.success).toBe(true)
|
||
expect(second.fromCache).toBe(true)
|
||
})
|
||
})
|