/**
 * 图片透明区域探测：用于后台在上传「热区按钮图 / 海报底图」时提示
 * 「这张图其实没有透明区域」——最常见的坑是把设计工具里带棋盘格的预览
 * 截图/另存下来，棋盘格就成了真实像素，前台会照实显示。
 */

export interface ImageTransparencyProbe {
  /** 是否存在透明像素（alpha < 250） */
  hasTransparentPixels: boolean
  /** 透明像素占比（0-1） */
  transparentRatio: number
  /** 不透明像素是否只有极少数浅灰/白颜色（棋盘格或纯色底烘焙进图片的典型特征） */
  suspectedBakedBackdrop: boolean
}

const SAMPLE_MAX_SIDE = 160
/** alpha 低于该值即视为透明像素 */
const TRANSPARENT_ALPHA = 250
/** 无明显透明像素的判定阈值（透明像素占比） */
const NEGLIGIBLE_TRANSPARENT_RATIO = 0.002

/** 纯像素分析（无 DOM 依赖，便于单测）。 */
export function analyzeImagePixels(data: Uint8ClampedArray | number[]): ImageTransparencyProbe {
  const total = Math.floor(data.length / 4)
  if (total <= 0) {
    return { hasTransparentPixels: false, transparentRatio: 0, suspectedBakedBackdrop: false }
  }

  let transparent = 0
  let opaque = 0
  let lightOnly = true
  const colors = new Set<number>()

  for (let index = 0; index < total; index += 1) {
    const offset = index * 4
    const r = data[offset] ?? 0
    const g = data[offset + 1] ?? 0
    const b = data[offset + 2] ?? 0
    const a = data[offset + 3] ?? 0
    if (a < TRANSPARENT_ALPHA) {
      transparent += 1
      continue
    }
    opaque += 1
    const min = Math.min(r, g, b)
    const max = Math.max(r, g, b)
    if (min < 216 || max - min > 28) lightOnly = false
    // 量化到 4bit/通道，避免抗锯齿噪点导致颜色数虚高
    colors.add(((r >> 4) << 8) | ((g >> 4) << 4) | (b >> 4))
  }

  const transparentRatio = transparent / total
  return {
    hasTransparentPixels: transparentRatio > NEGLIGIBLE_TRANSPARENT_RATIO,
    transparentRatio,
    suspectedBakedBackdrop:
      opaque > 0 &&
      lightOnly &&
      transparentRatio <= NEGLIGIBLE_TRANSPARENT_RATIO &&
      colors.size <= 4,
  }
}

/** 读取本地文件像素并分析；环境不支持时返回 null（不阻塞上传）。 */
export async function probeImageTransparency(file: File): Promise<ImageTransparencyProbe | null> {
  const source = await loadImageSource(file)
  if (!source) return null
  const width = Math.max(1, Math.round(source.width))
  const height = Math.max(1, Math.round(source.height))
  const scale = Math.min(1, SAMPLE_MAX_SIDE / Math.max(width, height))
  const targetWidth = Math.max(1, Math.round(width * scale))
  const targetHeight = Math.max(1, Math.round(height * scale))

  const canvas = document.createElement('canvas')
  canvas.width = targetWidth
  canvas.height = targetHeight
  const context = canvas.getContext('2d')
  if (!context) return null
  context.clearRect(0, 0, targetWidth, targetHeight)
  context.drawImage(source as CanvasImageSource, 0, 0, targetWidth, targetHeight)
  const imageData = context.getImageData(0, 0, targetWidth, targetHeight)
  return analyzeImagePixels(imageData.data)
}

async function loadImageSource(file: File): Promise<ImageBitmap | HTMLImageElement | null> {
  if (typeof createImageBitmap === 'function') {
    try {
      return await createImageBitmap(file)
    } catch {
      // 继续走 <img> 兜底
    }
  }
  return await new Promise(resolve => {
    const url = URL.createObjectURL(file)
    const image = new Image()
    image.onload = () => {
      URL.revokeObjectURL(url)
      resolve(image)
    }
    image.onerror = () => {
      URL.revokeObjectURL(url)
      resolve(null)
    }
    image.src = url
  })
}