zyt/TUICallKit-Vue3/training/motion/roi-openness.ts

import type { CameraFrame, HandSample } from './types'

function clamp01(v: number) {
    return Math.max(0, Math.min(1, v))
}

/**
 * 开发者工具 / 不支持 VisionKit 时的粗开合估计：
 * 取画面中心 ROI 的亮度方差与边缘能量，映射到 openness。
 * 仅用于打通链路与 UI 联调，不能作为产品识别。
 */
export function estimateOpennessFromRoi(frame: CameraFrame): HandSample {
    const { width, height, data } = frame
    const u8 = new Uint8Array(data)
    const cx0 = Math.floor(width * 0.28)
    const cy0 = Math.floor(height * 0.22)
    const cx1 = Math.floor(width * 0.72)
    const cy1 = Math.floor(height * 0.78)
    const step = Math.max(4, Math.floor(Math.min(width, height) / 40))

    let count = 0
    let sum = 0
    let sumSq = 0
    let edge = 0
    let prev = 0

    for (let y = cy0; y < cy1; y += step) {
        for (let x = cx0; x < cx1; x += step) {
            const i = (y * width + x) * 4
            const r = u8[i]
            const g = u8[i + 1]
            const b = u8[i + 2]
            // 粗略肤色门控 + 亮度
            const luma = 0.299 * r + 0.587 * g + 0.114 * b
            const skinish = r > 60 && g > 30 && b > 20 && r >= g && Math.abs(r - g) > 8
            if (!skinish && luma < 40) continue
            sum += luma
            sumSq += luma * luma
            edge += Math.abs(luma - prev)
            prev = luma
            count += 1
        }
    }

    if (count < 20) {
        return {
            ts: Date.now(),
            openness: 0.5,
            score: 0.05,
            source: 'roi',
        }
    }

    const mean = sum / count
    const variance = Math.max(0, sumSq / count - mean * mean)
    const edgeNorm = edge / count

    // 张开手掌通常带来更大轮廓/边缘；握拳更紧凑。经验映射，仅联调。
    const openness = clamp01((Math.sqrt(variance) / 55 + edgeNorm / 40) * 0.85)
    const score = clamp01(0.25 + count / 800)

    return {
        ts: Date.now(),
        openness,
        score,
        source: 'roi',
    }
}