feat: seedance参考图人脸打码(YuNet+切块旋转/白点阵) + VIP零额度降级 + veo3.1 1080p + CGO Dockerfile
This commit is contained in:
+15
-5
@@ -1,20 +1,30 @@
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# syntax=docker/dockerfile:1
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# onnxruntime 版本要与 go.mod 里 yalue/onnxruntime_go 的 API 版本匹配
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ARG ORT_VERSION=1.28.0
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# --- Stage 1: build the Go binary from source ---
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FROM golang:1.26-alpine AS build
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# YuNet 人脸检测走 onnxruntime，需要 CGO(gcc) + libonnxruntime 动态库，
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# 因此构建/运行镜像都用 glibc 的 debian（onnxruntime 官方包不支持 musl/alpine）。
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FROM golang:1.26-bookworm AS build
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ARG ORT_VERSION
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WORKDIR /src
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RUN apk add --no-cache git
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RUN wget -qO /tmp/ort.tgz https://github.com/microsoft/onnxruntime/releases/download/v${ORT_VERSION}/onnxruntime-linux-x64-${ORT_VERSION}.tgz \
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&& tar -xzf /tmp/ort.tgz -C /opt && rm /tmp/ort.tgz
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# Cache deps first for faster rebuilds.
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COPY go.mod go.sum ./
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RUN go mod download
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COPY . .
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RUN CGO_ENABLED=0 GOOS=linux go build -trimpath -ldflags="-s -w" -o /out/api ./cmd/api
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RUN CGO_ENABLED=1 GOOS=linux go build -trimpath -ldflags="-s -w" -o /out/api ./cmd/api
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# --- Stage 2: minimal runtime image ---
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FROM alpine:3.20
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FROM debian:bookworm-slim
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ARG ORT_VERSION
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# ca-certificates: outbound HTTPS to the AI providers. tzdata: POSTGRES_DSN sets
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# TimeZone=Asia/Shanghai. wget: container healthcheck.
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RUN apk add --no-cache ca-certificates tzdata wget
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RUN apt-get update && apt-get install -y --no-install-recommends ca-certificates tzdata wget \
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&& rm -rf /var/lib/apt/lists/*
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COPY --from=build /opt/onnxruntime-linux-x64-${ORT_VERSION}/lib/libonnxruntime.so* /usr/local/lib/
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WORKDIR /app
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COPY --from=build /out/api /app/api
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# Local fallback for generated media / reference uploads (RustFS/S3 is primary).
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@@ -13,6 +13,7 @@ require (
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github.com/google/uuid v1.6.0
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github.com/matoous/go-nanoid/v2 v2.1.0
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github.com/redis/go-redis/v9 v9.16.0
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github.com/yalue/onnxruntime_go v1.32.0
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golang.org/x/crypto v0.54.0
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golang.org/x/image v0.43.0
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gorm.io/datatypes v1.2.7
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@@ -156,6 +156,8 @@ github.com/ugorji/go/codec v1.3.0 h1:Qd2W2sQawAfG8XSvzwhBeoGq71zXOC/Q1E9y/wUcsUA
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github.com/ugorji/go/codec v1.3.0/go.mod h1:pRBVtBSKl77K30Bv8R2P+cLSGaTtex6fsA2Wjqmfxj4=
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github.com/xyproto/randomstring v1.0.5 h1:YtlWPoRdgMu3NZtP45drfy1GKoojuR7hmRcnhZqKjWU=
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github.com/xyproto/randomstring v1.0.5/go.mod h1:rgmS5DeNXLivK7YprL0pY+lTuhNQW3iGxZ18UQApw/E=
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github.com/yalue/onnxruntime_go v1.32.0 h1:O4pPw3IT+46CRrfuT0lcHWkczVoFvtfq6kMAO/iIVKc=
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github.com/yalue/onnxruntime_go v1.32.0/go.mod h1:b4X26A8pekNb1ACJ58wAXgNKeUCGEAQ9dmACut9Sm/4=
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go.uber.org/mock v0.5.2 h1:LbtPTcP8A5k9WPXj54PPPbjcI4Y6lhyOZXn+VS7wNko=
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go.uber.org/mock v0.5.2/go.mod h1:wLlUxC2vVTPTaE3UD51E0BGOAElKrILxhVSDYQLld5o=
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golang.org/x/arch v0.20.0 h1:dx1zTU0MAE98U+TQ8BLl7XsJbgze2WnNKF/8tGp/Q6c=
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@@ -368,7 +368,7 @@ func (h *UserGenerationHandler) VideoPresets(c *gin.Context) {
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"provider": "adobe",
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"durations": []string{"4s", "6s", "8s"},
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"ratios": []string{"16:9", "9:16"},
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"resolutions": []string{"720p"},
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"resolutions": []string{"720p", "1080p"},
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},
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{
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"key": "seedance-2.0-fast",
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Binary file not shown.
@@ -0,0 +1,462 @@
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package service
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import (
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"bytes"
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_ "embed"
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"errors"
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"fmt"
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"image"
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"image/color"
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"image/draw"
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"image/png"
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"math"
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"os"
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"runtime"
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"sort"
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"sync"
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ort "github.com/yalue/onnxruntime_go"
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)
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// YuNet 人脸检测模型（opencv_zoo face_detection_yunet_2023mar，输入尺寸已改为
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// 动态），编译进二进制，运行时只额外依赖 onnxruntime 动态库。
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//
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//go:embed assets/yunet.onnx
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var yunetModel []byte
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const (
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// 检出分数下限与 NMS 的 IoU 阈值
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faceScoreThreshold = 0.35
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faceNMSIoU = 0.3
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// 推理输入的长边上限：更大的图先等比缩小，检出框再映射回原图，
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// 避免超大参考图把内存和耗时拉爆。
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faceMaxInferSide = 2560
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)
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// YuNet 的三个输出分支步长
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var faceStrides = []int{8, 16, 32}
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// ErrNoFaceDetected 表示图中没有检出人脸，调用方按原图处理。
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var ErrNoFaceDetected = errors.New("no face detected")
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var (
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faceOnce sync.Once
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faceSession *ort.DynamicAdvancedSession
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faceInitErr error
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)
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// onnxruntimeLibPath 返回 onnxruntime 动态库路径：ONNXRUNTIME_LIB_PATH 优先，
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// 否则用各平台的默认位置。
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func onnxruntimeLibPath() string {
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if p := os.Getenv("ONNXRUNTIME_LIB_PATH"); p != "" {
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return p
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}
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if runtime.GOOS == "windows" {
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return "onnxruntime.dll"
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}
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return "/usr/local/lib/libonnxruntime.so"
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}
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// faceOutputNames 是 YuNet 需要读取的输出名，顺序与 readOutputs 的下标约定一致：
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// 先 cls_*、再 obj_*、最后 bbox_*（关键点分支用不到）。
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func faceOutputNames() []string {
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names := make([]string, 0, len(faceStrides)*3)
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for _, prefix := range []string{"cls", "obj", "bbox"} {
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for _, s := range faceStrides {
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names = append(names, fmt.Sprintf("%s_%d", prefix, s))
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}
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}
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return names
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}
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func faceDetector() (*ort.DynamicAdvancedSession, error) {
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faceOnce.Do(func() {
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ort.SetSharedLibraryPath(onnxruntimeLibPath())
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if err := ort.InitializeEnvironment(); err != nil {
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faceInitErr = fmt.Errorf("onnxruntime init: %w", err)
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return
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}
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faceSession, faceInitErr = ort.NewDynamicAdvancedSessionWithONNXData(
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yunetModel, []string{"input"}, faceOutputNames(), nil)
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})
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if faceInitErr != nil {
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return nil, faceInitErr
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}
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return faceSession, nil
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}
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type faceDetection struct {
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rect image.Rectangle
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score float32
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}
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// detectFaces 返回图中的人脸矩形框（坐标基于 src 的原始尺寸）。
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func detectFaces(src image.Image) ([]image.Rectangle, error) {
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sess, err := faceDetector()
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if err != nil {
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return nil, err
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}
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bounds := src.Bounds()
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long := bounds.Dx()
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if bounds.Dy() > long {
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long = bounds.Dy()
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}
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scale := 1.0
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if long > faceMaxInferSide {
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scale = float64(faceMaxInferSide) / float64(long)
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}
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inW := int(float64(bounds.Dx()) * scale)
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inH := int(float64(bounds.Dy()) * scale)
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if inW < 1 || inH < 1 {
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return nil, nil
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}
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// 输入补齐到 32 的整数倍，三个步长分支才有整数网格
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padW := (inW + 31) / 32 * 32
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padH := (inH + 31) / 32 * 32
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// YuNet 吃 BGR、NCHW、未归一化的 0~255 像素
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pixels := make([]float32, 3*padW*padH)
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plane := padW * padH
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for y := 0; y < inH; y++ {
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srcY := bounds.Min.Y + int(float64(y)/scale)
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for x := 0; x < inW; x++ {
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r, g, b, _ := src.At(bounds.Min.X+int(float64(x)/scale), srcY).RGBA()
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i := y*padW + x
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pixels[i] = float32(b >> 8)
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pixels[plane+i] = float32(g >> 8)
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pixels[2*plane+i] = float32(r >> 8)
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}
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}
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input, err := ort.NewTensor(ort.NewShape(1, 3, int64(padH), int64(padW)), pixels)
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if err != nil {
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return nil, err
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}
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defer input.Destroy()
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outputs := make([]ort.Value, len(faceStrides)*3)
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if err := sess.Run([]ort.Value{input}, outputs); err != nil {
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return nil, err
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}
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defer func() {
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for _, out := range outputs {
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if out != nil {
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out.Destroy()
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}
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}
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}()
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branch := func(i int) ([]float32, error) {
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t, ok := outputs[i].(*ort.Tensor[float32])
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if !ok {
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return nil, fmt.Errorf("yunet output %d is not a float32 tensor", i)
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}
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return t.GetData(), nil
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}
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inferBounds := image.Rect(0, 0, inW, inH)
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var dets []faceDetection
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for si, stride := range faceStrides {
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cls, err := branch(si)
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if err != nil {
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return nil, err
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}
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obj, err := branch(len(faceStrides) + si)
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if err != nil {
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return nil, err
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}
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box, err := branch(2*len(faceStrides) + si)
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if err != nil {
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return nil, err
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}
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cols, rows := padW/stride, padH/stride
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for row := 0; row < rows; row++ {
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for col := 0; col < cols; col++ {
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idx := row*cols + col
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score := float32(math.Sqrt(float64(clampUnit(cls[idx]) * clampUnit(obj[idx]))))
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if score < faceScoreThreshold {
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continue
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}
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cx := (float32(col) + box[idx*4]) * float32(stride)
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cy := (float32(row) + box[idx*4+1]) * float32(stride)
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w := float32(math.Exp(float64(box[idx*4+2]))) * float32(stride)
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h := float32(math.Exp(float64(box[idx*4+3]))) * float32(stride)
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rect := image.Rect(int(cx-w/2), int(cy-h/2), int(cx+w/2), int(cy+h/2)).Intersect(inferBounds)
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if rect.Dx() > 0 && rect.Dy() > 0 {
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dets = append(dets, faceDetection{rect: rect, score: score})
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}
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}
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}
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}
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boxes := make([]image.Rectangle, 0, len(dets))
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for _, d := range suppressOverlaps(dets, faceNMSIoU) {
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rect := d.rect
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if scale != 1 {
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rect = image.Rect(
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int(float64(rect.Min.X)/scale), int(float64(rect.Min.Y)/scale),
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int(float64(rect.Max.X)/scale), int(float64(rect.Max.Y)/scale),
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).Intersect(image.Rect(0, 0, bounds.Dx(), bounds.Dy()))
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}
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if rect.Dx() > 0 && rect.Dy() > 0 {
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boxes = append(boxes, rect.Add(bounds.Min))
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}
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}
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return boxes, nil
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}
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func clampUnit(v float32) float32 {
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if v < 0 {
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return 0
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}
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if v > 1 {
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return 1
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}
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return v
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}
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// suppressOverlaps 按分数从高到低做 NMS，丢掉与已保留框 IoU 超过阈值的框。
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func suppressOverlaps(dets []faceDetection, iouThreshold float64) []faceDetection {
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sort.SliceStable(dets, func(i, j int) bool { return dets[i].score > dets[j].score })
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kept := make([]faceDetection, 0, len(dets))
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for _, d := range dets {
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overlaps := false
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for _, k := range kept {
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if rectIoU(d.rect, k.rect) > iouThreshold {
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overlaps = true
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break
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}
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}
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if !overlaps {
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kept = append(kept, d)
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}
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}
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return kept
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}
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func rectIoU(a, b image.Rectangle) float64 {
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inter := a.Intersect(b)
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if inter.Empty() {
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return 0
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}
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interArea := float64(inter.Dx() * inter.Dy())
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return interArea / (float64(a.Dx()*a.Dy()+b.Dx()*b.Dy()) - interArea)
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}
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// applyFaceNotice 给图中每张人脸盖一层红色网格点，返回 PNG。
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// 没检出人脸（或不是可解码的图片）时返回 ErrNoFaceDetected，调用方应继续用原图；
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// 其它错误说明检测器不可用，调用方不应把未打码的图上传。
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func applyFaceNotice(b []byte) ([]byte, error) {
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src, _, err := image.Decode(bytes.NewReader(b))
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if err != nil {
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return nil, ErrNoFaceDetected
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}
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boxes, err := detectFaces(src)
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if err != nil {
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return nil, err
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}
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if len(boxes) == 0 {
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return nil, ErrNoFaceDetected
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}
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w, h := src.Bounds().Dx(), src.Bounds().Dy()
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orig := image.NewRGBA(image.Rect(0, 0, w, h))
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draw.Draw(orig, orig.Bounds(), src, src.Bounds().Min, draw.Src)
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offset := image.Pt(-src.Bounds().Min.X, -src.Bounds().Min.Y)
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// 脸多（>4 张）时不做顶部条，直接给每张脸盖一层白点阵。
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if len(boxes) > 4 {
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dst := image.NewRGBA(image.Rect(0, 0, w, h))
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draw.Draw(dst, dst.Bounds(), orig, image.Point{}, draw.Src)
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for _, box := range boxes {
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drawWhiteDots(dst, box.Add(offset).Intersect(dst.Bounds()))
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}
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var out bytes.Buffer
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if err := png.Encode(&out, dst); err != nil {
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return nil, err
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}
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return out.Bytes(), nil
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}
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// 紧贴脸的检出框：切片和盖黑都用它，两者一样大。
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heads := make([]image.Rectangle, 0, len(boxes))
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for _, box := range boxes {
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heads = append(heads, box.Add(offset).Intersect(orig.Bounds()))
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}
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// 取面积最大的一张脸切成 4 块——切割线正好穿过脸中心，每块只有 1/4 张脸，
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// 打乱后分开摆到图片上方新加的黑色条带里。
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main := largestRect(heads)
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quads := faceQuadrants(orig, main) // 已按打乱顺序排列的 4 块
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gap := main.Dx() / 8
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if gap < 8 {
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gap = 8
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}
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stripH := main.Dy()/2 + 2*gap
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black := image.NewUniform(color.RGBA{A: 255})
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dst := image.NewRGBA(image.Rect(0, 0, w, h+stripH))
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draw.Draw(dst, dst.Bounds(), black, image.Point{}, draw.Src) // 条带底色黑
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draw.Draw(dst, image.Rect(0, stripH, w, h+stripH), orig, image.Point{}, draw.Src)
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// 4 块横向排开，块间留黑缝，明显是碎片而非整脸。
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x := gap
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for _, q := range quads {
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qw, qh := q.Bounds().Dx(), q.Bounds().Dy()
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if x+qw > w {
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break
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}
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draw.Draw(dst, image.Rect(x, gap, x+qw, gap+qh), q, image.Point{}, draw.Src)
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x += qw + gap
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}
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// 原图里每张脸整块盖黑（坐标下移 stripH）。
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for _, hd := range heads {
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draw.Draw(dst, hd.Add(image.Pt(0, stripH)), black, image.Point{}, draw.Src)
|
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}
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|
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var out bytes.Buffer
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if err := png.Encode(&out, dst); err != nil {
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return nil, err
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}
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return out.Bytes(), nil
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}
|
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|
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// expandFaceBox 把 YuNet 的紧致人脸框向外扩到大致一个头部的范围（额头到下巴），
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// 只挡眼睛不足以让 Adobe 认不出大图正脸。结果裁剪到图像范围内。
|
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func expandFaceBox(b image.Rectangle, bounds image.Rectangle) image.Rectangle {
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w := b.Dx()
|
||||
h := b.Dy()
|
||||
padX := w * 60 / 100
|
||||
minX := b.Min.X - padX
|
||||
maxX := b.Max.X + padX
|
||||
width := maxX - minX
|
||||
// 高度按脸宽推算（额头到下巴 ≈ 1.2×脸宽）。YuNet 框常只圈住眼部，
|
||||
// 只按框高向下扩不足以盖住嘴和下巴。
|
||||
height := width * 115 / 100
|
||||
if hh := h * 180 / 100; hh > height {
|
||||
height = hh
|
||||
}
|
||||
top := b.Min.Y - h*85/100
|
||||
out := image.Rect(minX, top, maxX, top+height)
|
||||
return out.Intersect(bounds)
|
||||
}
|
||||
|
||||
// faceQuadrants 把 box 区域切成 2×2 四块，按固定置换打乱顺序后返回这 4 块子图。
|
||||
func faceQuadrants(src *image.RGBA, box image.Rectangle) []*image.RGBA {
|
||||
hw, hh := box.Dx()/2, box.Dy()/2
|
||||
rects := [4]image.Rectangle{
|
||||
image.Rect(box.Min.X, box.Min.Y, box.Min.X+hw, box.Min.Y+hh),
|
||||
image.Rect(box.Min.X+hw, box.Min.Y, box.Max.X, box.Min.Y+hh),
|
||||
image.Rect(box.Min.X, box.Min.Y+hh, box.Min.X+hw, box.Max.Y),
|
||||
image.Rect(box.Min.X+hw, box.Min.Y+hh, box.Max.X, box.Max.Y),
|
||||
}
|
||||
perm := [4]int{3, 1, 2, 0} // 打乱顺序
|
||||
rot := [4]int{1, 2, 3, 2} // 每块各自旋转 90°/180°/270°，打断人脸连续性
|
||||
out := make([]*image.RGBA, 0, 4)
|
||||
for i, s := range perm {
|
||||
r := rects[s]
|
||||
q := image.NewRGBA(image.Rect(0, 0, r.Dx(), r.Dy()))
|
||||
draw.Draw(q, q.Bounds(), src, r.Min, draw.Src)
|
||||
out = append(out, rotateRGBA(q, rot[i]))
|
||||
}
|
||||
return out
|
||||
}
|
||||
|
||||
// rotateRGBA 顺时针旋转 90° 的 k 倍，返回旋转后的新图。
|
||||
func rotateRGBA(src *image.RGBA, k int) *image.RGBA {
|
||||
k = ((k % 4) + 4) % 4
|
||||
if k == 0 {
|
||||
return src
|
||||
}
|
||||
w, h := src.Bounds().Dx(), src.Bounds().Dy()
|
||||
var dst *image.RGBA
|
||||
if k == 2 {
|
||||
dst = image.NewRGBA(image.Rect(0, 0, w, h))
|
||||
for y := 0; y < h; y++ {
|
||||
for x := 0; x < w; x++ {
|
||||
dst.SetRGBA(w-1-x, h-1-y, src.RGBAAt(x, y))
|
||||
}
|
||||
}
|
||||
return dst
|
||||
}
|
||||
dst = image.NewRGBA(image.Rect(0, 0, h, w))
|
||||
for y := 0; y < h; y++ {
|
||||
for x := 0; x < w; x++ {
|
||||
if k == 1 {
|
||||
dst.SetRGBA(h-1-y, x, src.RGBAAt(x, y))
|
||||
} else {
|
||||
dst.SetRGBA(y, w-1-x, src.RGBAAt(x, y))
|
||||
}
|
||||
}
|
||||
}
|
||||
return dst
|
||||
}
|
||||
|
||||
// drawWhiteDots 在脸框内铺一层小白点阵，盖住五官（只盖脸、不外扩）。
|
||||
func drawWhiteDots(dst *image.RGBA, box image.Rectangle) {
|
||||
step := box.Dx() / 16
|
||||
if step < 4 {
|
||||
step = 4
|
||||
}
|
||||
r := step / 3
|
||||
if r < 2 {
|
||||
r = 2
|
||||
}
|
||||
white := color.RGBA{R: 255, G: 255, B: 255, A: 255}
|
||||
for cy := box.Min.Y + step/2; cy < box.Max.Y; cy += step {
|
||||
for cx := box.Min.X + step/2; cx < box.Max.X; cx += step {
|
||||
fillDot(dst, cx, cy, r, box, white)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// largestRect 返回面积最大的矩形。
|
||||
func largestRect(rs []image.Rectangle) image.Rectangle {
|
||||
best := rs[0]
|
||||
for _, r := range rs[1:] {
|
||||
if r.Dx()*r.Dy() > best.Dx()*best.Dy() {
|
||||
best = r
|
||||
}
|
||||
}
|
||||
return best
|
||||
}
|
||||
|
||||
// minInt 返回两数中较小者。
|
||||
func minInt(a, b int) int {
|
||||
if a < b {
|
||||
return a
|
||||
}
|
||||
return b
|
||||
}
|
||||
|
||||
// faceDotAlpha 网格点的不透明度（255 = 实心）。
|
||||
const faceDotAlpha uint8 = 26
|
||||
|
||||
// blendPixel 把前景色按其 alpha 叠到底色上。
|
||||
func blendPixel(bg, fg color.RGBA) color.RGBA {
|
||||
a := int(fg.A)
|
||||
mix := func(f, b uint8) uint8 {
|
||||
return uint8((int(f)*a + int(b)*(255-a)) / 255)
|
||||
}
|
||||
return color.RGBA{R: mix(fg.R, bg.R), G: mix(fg.G, bg.G), B: mix(fg.B, bg.B), A: 255}
|
||||
}
|
||||
|
||||
// fillDot 以 (cx,cy) 为心画一个半径 r 的圆，按 c.A 与底图混合，裁剪在 clip 内。
|
||||
func fillDot(dst *image.RGBA, cx, cy, r int, clip image.Rectangle, c color.RGBA) {
|
||||
r2 := r * r
|
||||
for y := cy - r; y <= cy+r; y++ {
|
||||
if y < clip.Min.Y || y >= clip.Max.Y {
|
||||
continue
|
||||
}
|
||||
for x := cx - r; x <= cx+r; x++ {
|
||||
if x < clip.Min.X || x >= clip.Max.X {
|
||||
continue
|
||||
}
|
||||
dx := x - cx
|
||||
dy := y - cy
|
||||
if dx*dx+dy*dy <= r2 {
|
||||
dst.SetRGBA(x, y, blendPixel(dst.RGBAAt(x, y), c))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -123,9 +123,16 @@ func (s *RefreshProfileService) RefreshNow(ctx context.Context, id string) error
|
||||
tokenPatch["meta"] = meta
|
||||
|
||||
planCap := strings.ToLower(strings.TrimSpace(stringValue(quotaData["plan"])))
|
||||
meta["plan"] = planCap
|
||||
isVIP := planCap != "" && !strings.EqualFold(planCap, "free")
|
||||
planKnown = planCap != ""
|
||||
// 额度打到 0 的 VIP(母号/子号) 视为普号：写死 plan=free，额度恢复(>0)后下次刷新自动还原真实身份。
|
||||
if isVIP {
|
||||
if rem, ok := quotaData["remaining"].(int); ok && rem <= 0 {
|
||||
isVIP = false
|
||||
planCap = "free"
|
||||
}
|
||||
}
|
||||
meta["plan"] = planCap
|
||||
|
||||
// VIP: use Adobe's reset time; set concurrency 5.
|
||||
// 母号/子号 身份固定，不随积分动态变化——只有降级普号才刷新身份。
|
||||
@@ -134,6 +141,18 @@ func (s *RefreshProfileService) RefreshNow(ctx context.Context, id string) error
|
||||
tokenPatch["cached_quota_reset_after"] = resetAfter
|
||||
}
|
||||
tokenPatch["concurrency"] = 5
|
||||
// 身份固定：这里重建了整个 meta，若不带上 is_sub_account，刷新会把导入时
|
||||
// 确定的 母号/子号 标记冲掉。身份只在导入时确定，刷新只沿用、绝不靠积分猜：
|
||||
// 已有标记就带过来；取不到（没 meta / 缺字段）说明身份未知，直接置死号。
|
||||
if existing, gerr := s.tokens.Get(ctx, "adobe", id); gerr == nil {
|
||||
if v, ok := existing.Meta["is_sub_account"]; ok {
|
||||
meta["is_sub_account"] = v
|
||||
}
|
||||
}
|
||||
if _, ok := meta["is_sub_account"]; !ok {
|
||||
tokenPatch["status"] = "disabled"
|
||||
tokenPatch["dead"] = true
|
||||
}
|
||||
} else {
|
||||
// Free account: concurrency 1, limit image+video
|
||||
tokenPatch["concurrency"] = 1
|
||||
|
||||
@@ -713,15 +713,24 @@ func (s *TokenService) checkPendingAdobe(tokenID, cookie string) {
|
||||
if cb, e := s.adobe.FetchCreditsBalance(ctx, result.AccessToken); e == nil {
|
||||
quotaMeta["cached_quota_at"] = int(time.Now().Unix())
|
||||
planCap := strings.ToLower(strings.TrimSpace(stringValue(cb["plan"])))
|
||||
quotaMeta["plan"] = planCap
|
||||
isVIP := planCap != "" && planCap != "free"
|
||||
planKnown = planCap != ""
|
||||
|
||||
if rem, ok := cb["remaining"].(int); ok {
|
||||
rem, remOK := cb["remaining"].(int)
|
||||
if remOK {
|
||||
quotaMeta["cached_quota_remaining"] = rem
|
||||
if isVIP && rem > 0 && rem <= 4000 {
|
||||
quotaMeta["is_sub_account"] = true
|
||||
}
|
||||
// 额度打到 0 的 VIP(母号/子号) 视为普号：写死 plan=free，额度恢复(>0)后下次刷新自动还原真实身份。
|
||||
if isVIP && remOK && rem <= 0 {
|
||||
isVIP = false
|
||||
planCap = "free"
|
||||
}
|
||||
quotaMeta["plan"] = planCap
|
||||
// VIP 号导入即固定 母号/子号 身份并显式写入 is_sub_account：积分 1..4000 视为子号，
|
||||
// 其余（含 >4000）为母号(false)。母号必须显式写 false，否则 isVipMotherAccount
|
||||
// 因字段缺失把它判为非母号，导致 Seedance 无号可调度。
|
||||
if isVIP {
|
||||
quotaMeta["is_sub_account"] = rem > 0 && rem <= 4000
|
||||
}
|
||||
|
||||
// Set concurrency + limits based on plan
|
||||
@@ -1314,6 +1323,11 @@ func (s *TokenService) Quota(ctx context.Context, pool, id string) (map[string]a
|
||||
}
|
||||
if remaining, ok := data["remaining"].(int); ok {
|
||||
meta["cached_quota_remaining"] = remaining
|
||||
// 额度打到 0 的 VIP(母号/子号) 视为普号：写死 plan=free，额度恢复(>0)后下次扫描自动还原真实身份。
|
||||
if plan != "" && plan != "free" && remaining <= 0 {
|
||||
plan = "free"
|
||||
meta["plan"] = "free"
|
||||
}
|
||||
// is_sub_account 仅在导入时写入，刷新配额时不覆盖
|
||||
if _, hasFlag := meta["is_sub_account"]; !hasFlag && plan != "free" {
|
||||
meta["is_sub_account"] = remaining > 0 && remaining <= 4000
|
||||
|
||||
@@ -1801,6 +1801,20 @@ func (s *V1Service) generateAdobeVideo(ctx context.Context, eventID string, mode
|
||||
imgRefs = append(imgRefs, r)
|
||||
}
|
||||
}
|
||||
// Seedance 参考图先做人脸打码再上传；检不出人脸就沿用原图，
|
||||
// 检测器不可用则直接报错，避免把未打码的人脸传给上游。
|
||||
if isSeedanceModel(modelItem.ID) {
|
||||
for i, r := range imgRefs {
|
||||
marked, mErr := applyFaceNotice(r)
|
||||
if errors.Is(mErr, ErrNoFaceDetected) {
|
||||
continue
|
||||
}
|
||||
if mErr != nil {
|
||||
return nil, "", fmt.Errorf("face mask: %w", mErr)
|
||||
}
|
||||
imgRefs[i] = marked
|
||||
}
|
||||
}
|
||||
|
||||
engine, upstreamModel := resolveAdobeVideoEngine(modelItem.ID)
|
||||
referenceMode := defaultString(strings.TrimSpace(modelItem.ReferenceMode), "frame")
|
||||
|
||||
Reference in New Issue
Block a user