76 lines
3.4 KiB
JavaScript
76 lines
3.4 KiB
JavaScript
// 照片式 AI 炫图端到端验证: 注入程序化测试照片 → 拖框 → 生成 → 截画廊
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// 用法: node verify-photorender.mjs <token>
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import puppeteer from 'puppeteer-core'
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const browser = await puppeteer.launch({
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executablePath: 'C:/Program Files (x86)/Microsoft/Edge/Application/msedge.exe',
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headless: 'new',
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args: ['--window-size=1440,900', '--enable-unsafe-swiftshader'],
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defaultViewport: { width: 1440, height: 900 },
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})
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const page = await browser.newPage()
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page.on('pageerror', e => console.log(`[JS异常] ${String(e).slice(0, 200)}`))
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const token = process.argv[2]
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await page.goto(`http://localhost:8000/ai_render?token=${encodeURIComponent(token)}`, { waitUntil: 'networkidle2' })
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await new Promise(r => setTimeout(r, 2000))
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// 1) 选第一个样板
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await page.click('.controls .el-select')
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await new Promise(r => setTimeout(r, 800))
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const opt = await page.$('.el-select-dropdown__item')
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await opt.click()
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await new Promise(r => setTimeout(r, 1200))
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// 2) 程序化生成"室内照片"并注入 el-upload
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await page.evaluate(() => {
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const cv = document.createElement('canvas')
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cv.width = 1200; cv.height = 800
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const ctx = cv.getContext('2d')
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// 墙面渐变 + 地板 + 侧窗阴影区
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const g = ctx.createLinearGradient(0, 0, 0, 800)
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g.addColorStop(0, '#e8e0d2'); g.addColorStop(0.7, '#d8cdbb'); g.addColorStop(1, '#9c8b74')
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ctx.fillStyle = g; ctx.fillRect(0, 0, 1200, 800)
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ctx.fillStyle = 'rgba(120,100,80,0.25)'
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ctx.fillRect(380, 260, 440, 340) // 旧窗洞(深色)
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ctx.strokeStyle = 'rgba(90,70,50,0.5)'; ctx.lineWidth = 8
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ctx.strokeRect(380, 260, 440, 340)
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return new Promise(resolve => {
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cv.toBlob(blob => {
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const dt = new DataTransfer()
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dt.items.add(new File([blob], 'room.png', { type: 'image/png' }))
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const input = document.querySelector('.el-upload input[type=file]')
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input.files = dt.files
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input.dispatchEvent(new Event('change'))
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resolve()
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}, 'image/png')
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})
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})
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await new Promise(r => setTimeout(r, 1200))
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// 3) 在照片上拖框(对应旧窗洞位置)
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const stage = await page.$('.photo-cv')
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if (!stage) { console.log('✗ 照片舞台未出现'); process.exit(1) }
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const b = await stage.boundingBox()
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await page.mouse.move(b.x + b.width * 0.3, b.y + b.height * 0.3)
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await page.mouse.down()
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await page.mouse.move(b.x + b.width * 0.7, b.y + b.height * 0.75, { steps: 8 })
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await page.mouse.up()
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await new Promise(r => setTimeout(r, 400))
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// 4) 生成
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const genBtn = await page.evaluateHandle(() => [...document.querySelectorAll('button')].find(x => x.textContent.includes('生成炫图')))
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await genBtn.asElement().click()
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await new Promise(r => setTimeout(r, 6000))
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const shots = await page.$$('.shot')
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console.log(`方案数: ${shots.length}`)
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if (!shots.length) { console.log('✗ 未生成方案'); process.exit(1) }
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await page.evaluate(() => document.querySelector('.gallery')?.scrollIntoView({ block: 'center' }))
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await new Promise(r => setTimeout(r, 500))
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if (shots[0]) await shots[0].screenshot({ path: 'D:/Code/huamenchuang/shots/verify-photorender-0.png' })
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if (shots[1]) await shots[1].screenshot({ path: 'D:/Code/huamenchuang/shots/verify-photorender-1.png' })
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if (shots[2]) await shots[2].screenshot({ path: 'D:/Code/huamenchuang/shots/verify-photorender-2.png' })
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const stageEl = await page.$('.photo-cv')
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if (stageEl) await stageEl.screenshot({ path: 'D:/Code/huamenchuang/shots/verify-photo-stage.png' })
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console.log('✓ 照片合成炫图验证完成')
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await browser.close()
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