This commit is contained in:
toom1996
2026-09-17 00:38:01 +08:00
parent 7dd3fda73c
commit 6c31b18e0f
10 changed files with 389 additions and 77 deletions

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@ -32,16 +32,19 @@ func (BrandRunwayDraft) TableName() string { return "brand_runway_draft" }
// BrandRunwayDraftImage 草稿图片(对应 brand_runway_draft_images)。
type BrandRunwayDraftImage struct {
ID uint32 `gorm:"primaryKey;column:id" json:"id"`
DraftID uint32 `gorm:"column:draft_id" json:"draft_id"`
Image string `gorm:"column:image" json:"image"`
Name string `gorm:"column:name" json:"name"`
SortOrder uint32 `gorm:"column:sort_order" json:"sort_order"`
LookIndex uint32 `gorm:"column:look_index" json:"look_index"` // 细节图归属的主图序号
IsDetail uint8 `gorm:"column:is_detail" json:"is_detail"` // 0=主图 1=细节图
IsDeleted uint8 `gorm:"column:is_deleted" json:"is_deleted"`
CreatedAt uint32 `gorm:"column:created_at" json:"created_at"`
UpdatedAt uint32 `gorm:"column:updated_at" json:"updated_at"`
ID uint32 `gorm:"primaryKey;column:id" json:"id"`
DraftID uint32 `gorm:"column:draft_id" json:"draft_id"`
Image string `gorm:"column:image" json:"image"`
Name string `gorm:"column:name" json:"name"`
SortOrder uint32 `gorm:"column:sort_order" json:"sort_order"`
LookIndex uint32 `gorm:"column:look_index" json:"look_index"` // 细节图归属的主图序号
IsDetail uint8 `gorm:"column:is_detail" json:"is_detail"` // 0=主图 1=细节图
IsDeleted uint8 `gorm:"column:is_deleted" json:"is_deleted"`
CreatedAt uint32 `gorm:"column:created_at" json:"created_at"`
UpdatedAt uint32 `gorm:"column:updated_at" json:"updated_at"`
Phash uint64 `gorm:"column:phash" json:"phash"` // 感知哈希 64-bit;0=未计算
IsDuplicate uint8 `gorm:"column:is_duplicate" json:"is_duplicate"` // 近似重复标记:0=否 1=是(命中留痕不删)
DupOf string `gorm:"column:dup_of" json:"dup_of"` // 近似重复指向的图 uid(hashid),''=非重复
}
// TableName 指定草稿图片表名。

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@ -2,17 +2,20 @@ package model
// BrandRunwayImage 走秀图片。
type BrandRunwayImage struct {
ID uint32 `gorm:"primaryKey;column:id" json:"id"`
CreatedAt uint32 `gorm:"column:created_at" json:"created_at"`
UpdatedAt uint32 `gorm:"column:updated_at" json:"updated_at"`
IsDeleted uint8 `gorm:"column:is_deleted" json:"is_deleted"`
Image string `gorm:"column:image" json:"image"`
RunwayID uint32 `gorm:"column:runway_id" json:"runway_id"`
BrandID uint32 `gorm:"column:brand_id" json:"brand_id"`
Name string `gorm:"column:name" json:"name"`
SortOrder uint32 `gorm:"column:sort_order" json:"sort_order"` // 拖拽排序用,由迁移脚本新增
LookIndex uint32 `gorm:"column:look_index" json:"look_index"` // 细节图归属的主图序号(主图=该 look;细节图=所属主图的 look)
IsDetail uint8 `gorm:"column:is_detail" json:"is_detail"` // 0=主图/look 图(默认展示) 1=细节图
ID uint32 `gorm:"primaryKey;column:id" json:"id"`
CreatedAt uint32 `gorm:"column:created_at" json:"created_at"`
UpdatedAt uint32 `gorm:"column:updated_at" json:"updated_at"`
IsDeleted uint8 `gorm:"column:is_deleted" json:"is_deleted"`
Image string `gorm:"column:image" json:"image"`
RunwayID uint32 `gorm:"column:runway_id" json:"runway_id"`
BrandID uint32 `gorm:"column:brand_id" json:"brand_id"`
Name string `gorm:"column:name" json:"name"`
SortOrder uint32 `gorm:"column:sort_order" json:"sort_order"` // 拖拽排序用,由迁移脚本新增
LookIndex uint32 `gorm:"column:look_index" json:"look_index"` // 细节图归属的主图序号(主图=该 look;细节图=所属主图的 look)
IsDetail uint8 `gorm:"column:is_detail" json:"is_detail"` // 0=主图/look 图(默认展示) 1=细节图
Phash uint64 `gorm:"column:phash" json:"phash"` // 感知哈希 64-bit;0=未计算(存量)
IsDuplicate uint8 `gorm:"column:is_duplicate" json:"is_duplicate"` // 近似重复标记:0=否 1=是(命中留痕不删)
DupOf string `gorm:"column:dup_of" json:"dup_of"` // 近似重复指向的图 uid(hashid),''=非重复
}
// TableName 指定表名。

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@ -23,14 +23,17 @@ func (StreetSnap) TableName() string { return "street_snap" }
//
// 仿 brand_runway_images,但把 runway_id 改名为 snap_id,去掉 brand_id(街拍无品牌关联)。
type StreetSnapImage struct {
ID uint32 `gorm:"primaryKey;column:id" json:"id"`
SnapID uint32 `gorm:"column:snap_id" json:"snap_id"`
Image string `gorm:"column:image" json:"image"`
Name string `gorm:"column:name" json:"name"`
SortOrder uint32 `gorm:"column:sort_order" json:"sort_order"`
IsDeleted uint8 `gorm:"column:is_deleted" json:"is_deleted"`
CreatedAt uint32 `gorm:"column:created_at" json:"created_at"`
UpdatedAt uint32 `gorm:"column:updated_at" json:"updated_at"`
ID uint32 `gorm:"primaryKey;column:id" json:"id"`
SnapID uint32 `gorm:"column:snap_id" json:"snap_id"`
Image string `gorm:"column:image" json:"image"`
Name string `gorm:"column:name" json:"name"`
SortOrder uint32 `gorm:"column:sort_order" json:"sort_order"`
IsDeleted uint8 `gorm:"column:is_deleted" json:"is_deleted"`
CreatedAt uint32 `gorm:"column:created_at" json:"created_at"`
UpdatedAt uint32 `gorm:"column:updated_at" json:"updated_at"`
Phash uint64 `gorm:"column:phash" json:"phash"` // 感知哈希 64-bit;0=未计算(存量)
IsDuplicate uint8 `gorm:"column:is_duplicate" json:"is_duplicate"` // 近似重复标记:0=否 1=是(命中留痕不删)
DupOf string `gorm:"column:dup_of" json:"dup_of"` // 近似重复指向的图 uid(hashid),''=非重复
}
// TableName 指定图片明细表名。

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@ -28,14 +28,17 @@ func (StreetSnapDraft) TableName() string { return "street_snap_draft" }
// StreetSnapDraftImage 街拍草稿图片(对应 street_snap_draft_images)。
type StreetSnapDraftImage struct {
ID uint32 `gorm:"primaryKey;column:id" json:"id"`
DraftID uint32 `gorm:"column:draft_id" json:"draft_id"`
Image string `gorm:"column:image" json:"image"`
Name string `gorm:"column:name" json:"name"`
SortOrder uint32 `gorm:"column:sort_order" json:"sort_order"`
IsDeleted uint8 `gorm:"column:is_deleted" json:"is_deleted"`
CreatedAt uint32 `gorm:"column:created_at" json:"created_at"`
UpdatedAt uint32 `gorm:"column:updated_at" json:"updated_at"`
ID uint32 `gorm:"primaryKey;column:id" json:"id"`
DraftID uint32 `gorm:"column:draft_id" json:"draft_id"`
Image string `gorm:"column:image" json:"image"`
Name string `gorm:"column:name" json:"name"`
SortOrder uint32 `gorm:"column:sort_order" json:"sort_order"`
IsDeleted uint8 `gorm:"column:is_deleted" json:"is_deleted"`
CreatedAt uint32 `gorm:"column:created_at" json:"created_at"`
UpdatedAt uint32 `gorm:"column:updated_at" json:"updated_at"`
Phash uint64 `gorm:"column:phash" json:"phash"` // 感知哈希 64-bit;0=未计算
IsDuplicate uint8 `gorm:"column:is_duplicate" json:"is_duplicate"` // 近似重复标记:0=否 1=是(命中留痕不删)
DupOf string `gorm:"column:dup_of" json:"dup_of"` // 近似重复指向的图 uid(hashid),''=非重复
}
// TableName 指定草稿图片表名。

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@ -10,7 +10,7 @@ import (
// - 查询串模式(style 含 =):base_url/key?w=..&q=..
// - /uploads/ 与 http(s) 原样返回
func TestDisplayStyle(t *testing.T) {
c := New("https://mybucket.s3.bitiful.net", "high", "thumb", "")
c := New("https://mybucket.s3.bitiful.net", "high", "thumb")
got := c.Compose("runway/abc123.jpg")
want := "https://mybucket.s3.bitiful.net/runway/abc123.jpg!style:high"
if got != want {
@ -18,13 +18,13 @@ func TestDisplayStyle(t *testing.T) {
}
// 缺省回落 high
c0 := New("https://mybucket.s3.bitiful.net", "", "", "")
c0 := New("https://mybucket.s3.bitiful.net", "", "")
if c0.Compose("runway/abc123.jpg") != "https://mybucket.s3.bitiful.net/runway/abc123.jpg!style:high" {
t.Fatal("style 缺省应回落 high")
}
// 查询串模式
cq := New("https://mybucket.s3.bitiful.net", "w=1080&q=80&fmt=webp", "", "")
cq := New("https://mybucket.s3.bitiful.net", "w=1080&q=80&fmt=webp", "")
gq := cq.Compose("runway/abc123.jpg")
wq := "https://mybucket.s3.bitiful.net/runway/abc123.jpg?w=1080&q=80&fmt=webp"
if gq != wq {
@ -45,7 +45,7 @@ func TestDisplayStyle(t *testing.T) {
// TestComposeThumb 验证列表缩略图拼装:走 StyleThumb,兜底逻辑与 Compose 一致。
func TestComposeThumb(t *testing.T) {
c := New("https://mybucket.s3.bitiful.net", "high", "thumb", "")
c := New("https://mybucket.s3.bitiful.net", "high", "thumb")
got := c.ComposeThumb("runway/abc123.jpg")
want := "https://mybucket.s3.bitiful.net/runway/abc123.jpg!style:thumb"
if got != want {
@ -53,7 +53,7 @@ func TestComposeThumb(t *testing.T) {
}
// 未配置 styleThumb 时应回落展示样式,不得拼出空样式(key!style:)
c0 := New("https://mybucket.s3.bitiful.net", "high", "", "")
c0 := New("https://mybucket.s3.bitiful.net", "high", "")
if got := c0.ComposeThumb("runway/abc123.jpg"); got != "https://mybucket.s3.bitiful.net/runway/abc123.jpg!style:high" {
t.Fatalf("styleThumb 缺省应回落 styleDisplay,实际 %s", got)
}
@ -72,7 +72,7 @@ func TestComposeThumb(t *testing.T) {
// TestDisplayStyleURLSafe 确认展示 URL 不含任何签名/过期参数(匿名可访问)。
func TestDisplayStyleURLSafe(t *testing.T) {
c := New("https://mybucket.s3.bitiful.net", "high", "thumb", "")
c := New("https://mybucket.s3.bitiful.net", "high", "thumb")
u := c.Compose("runway/abc123.jpg")
for _, bad := range []string{"X-Amz", "sign", "e="} {
if strings.Contains(u, bad) {

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@ -56,6 +56,16 @@ type IngestRepository interface {
// ScheduleRetry 失败时调用:attempts+1,未达上限则退避后重置 pending,达上限则置 failed。
// 用于临时失败(网络抖动 / 单图下载失败)的自动重试,区别于永久失败(payload 解析错等)直接 MarkFailed。
ScheduleRetry(ctx context.Context, id uint32, errMsg string) error
// ListImagePHashes 返回全部已晋升图片(runway + street)的 (id, phash, kind),
// 跳过 is_deleted 与 phash=0/NULL(存量未计算)。供入库时与新增图做全局汉明比对(近似去重)。
ListImagePHashes(ctx context.Context) ([]ImagePHash, error)
}
// ImagePHash 已晋升图片的感知哈希摘要,供入库时全局近似去重比对。
type ImagePHash struct {
ID uint32 // 图片数字主键
Phash uint64 // 感知哈希(SQL 已过滤 0/NULL)
Kind string // "runway" | "street"(决定 dup_of 的 hashid 类型)
}
type ingestRepository struct {
@ -366,6 +376,40 @@ func (r *ingestRepository) RetryJob(ctx context.Context, id uint32) error {
}).Error
}
// ListImagePHashes 返回全部已晋升图片(runway + street)的感知哈希摘要,供入库时全局近似去重。
// 跳过 is_deleted 与 phash=0/NULL(存量未计算)。结果合并 runway + street 两类,
// 用 Kind 标注类型,调用方据此把 dup_of 编码成对应 hashid 类型。
//
// 注:每次入库任务都会全量拉取一次(图片量当前为千级,可接受);若后续图片量到十万级,
// 可改为按 runway_id/snap_id 分批或加内存缓存 + 定时刷新,避免每 job 一次全表扫描。
func (r *ingestRepository) ListImagePHashes(ctx context.Context) ([]ImagePHash, error) {
type phRow struct {
ID uint32 `gorm:"column:id"`
Phash uint64 `gorm:"column:phash"`
}
out := make([]ImagePHash, 0, 64)
const whereActive = "is_deleted = 0 AND phash IS NOT NULL AND phash <> 0"
var rw []phRow
if err := r.db.WithContext(ctx).Model(&model.BrandRunwayImage{}).
Select("id, phash").Where(whereActive).Scan(&rw).Error; err != nil {
return nil, err
}
for _, x := range rw {
out = append(out, ImagePHash{ID: x.ID, Phash: x.Phash, Kind: "runway"})
}
var sn []phRow
if err := r.db.WithContext(ctx).Model(&model.StreetSnapImage{}).
Select("id, phash").Where(whereActive).Scan(&sn).Error; err != nil {
return nil, err
}
for _, x := range sn {
out = append(out, ImagePHash{ID: x.ID, Phash: x.Phash, Kind: "street"})
}
return out, nil
}
// isDuplicateKey 兜底:gorm 的 ErrDuplicatedKey 在不同驱动下的封装不一定一致,
// 直接命中 MySQL 1062 错误号更稳。
func isDuplicateKey(err error) bool {

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@ -245,15 +245,18 @@ func (r *reviewRepository) SaveRunwayFromDraft(ctx context.Context, draftID uint
rows := make([]model.BrandRunwayImage, 0, len(imgs))
for i, im := range imgs {
rows = append(rows, model.BrandRunwayImage{
RunwayID: runwayID,
BrandID: draft.BrandID,
Image: im.Image,
Name: im.Name,
SortOrder: uint32(i + 1),
LookIndex: im.LookIndex,
IsDetail: im.IsDetail,
CreatedAt: now,
UpdatedAt: now,
RunwayID: runwayID,
BrandID: draft.BrandID,
Image: im.Image,
Name: im.Name,
SortOrder: uint32(i + 1),
LookIndex: im.LookIndex,
IsDetail: im.IsDetail,
Phash: im.Phash,
IsDuplicate: im.IsDuplicate,
DupOf: im.DupOf,
CreatedAt: now,
UpdatedAt: now,
})
}
if cErr := tx.Create(&rows).Error; cErr != nil {
@ -437,12 +440,15 @@ func (r *reviewRepository) SaveStreetSnapFromDraft(ctx context.Context, draftID
rows := make([]model.StreetSnapImage, 0, len(imgs))
for i, im := range imgs {
rows = append(rows, model.StreetSnapImage{
SnapID: snapID,
Image: im.Image,
Name: im.Name,
SortOrder: uint32(i + 1),
CreatedAt: now,
UpdatedAt: now,
SnapID: snapID,
Image: im.Image,
Name: im.Name,
SortOrder: uint32(i + 1),
Phash: im.Phash,
IsDuplicate: im.IsDuplicate,
DupOf: im.DupOf,
CreatedAt: now,
UpdatedAt: now,
})
}
if cErr := tx.Create(&rows).Error; cErr != nil {

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@ -30,7 +30,7 @@ func TestFetchImagesCleansUpOnFailure(t *testing.T) {
defer srv.Close()
urls := []string{srv.URL + "/ok1.jpg", srv.URL + "/ok2.jpg", srv.URL + "/bad.jpg"}
_, out, keys, failed := s.fetchImages(context.Background(), urls, "runway")
_, out, _, keys, failed := s.fetchImages(context.Background(), urls, "runway")
if !failed {
t.Fatalf("expected failed=true when one image errors")
}

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@ -15,6 +15,7 @@ import (
"fashionapi/internal/dto"
"fashionapi/internal/model"
"fashionapi/internal/pkg/hashid"
"fashionapi/internal/pkg/phash"
"fashionapi/internal/pkg/season"
"fashionapi/internal/pkg/storage"
"fashionapi/internal/repository"
@ -234,17 +235,24 @@ func (s *IngestService) processRunway(ctx context.Context, job model.IngestJob,
// 4) 下载图片并上传到存储(结构化 Looks 优先:主图+细节图分组;否则回退 Images 全部视为主图)。
// 内容哈希(sha1)key 保证重爬不产生孤儿文件:失败回滚删本批 key 即可。
// 同时算出每张图的 pHash(downloadOne 内基于原始字节),供后续全局近似去重标记。
var cover string
var draftImages []model.BrandRunwayDraftImage
var keys []string
var imgFailed bool
var imageCount uint16
var phashList []uint64
if len(p.Looks) > 0 {
cover, draftImages, keys, imgFailed = s.fetchLookImages(ctx, p.Looks, "runway")
imageCount = uint16(len(p.Looks))
phashList = make([]uint64, len(draftImages))
for i, d := range draftImages {
phashList[i] = d.Phash
}
} else {
var imgs []string
cover, imgs, keys, imgFailed = s.fetchImages(ctx, p.Images, "runway")
var phs []uint64
cover, imgs, phs, keys, imgFailed = s.fetchImages(ctx, p.Images, "runway")
imageCount = uint16(len(imgs))
for i, img := range imgs {
draftImages = append(draftImages, model.BrandRunwayDraftImage{
@ -253,8 +261,10 @@ func (s *IngestService) processRunway(ctx context.Context, job model.IngestJob,
SortOrder: uint32(i + 1),
LookIndex: uint32(i + 1),
IsDetail: 0,
Phash: phs[i],
})
}
phashList = phs
}
if imgFailed {
// 单图失败=整任务失败:先回滚本批已上传的图(S4 + 本地兜底),避免孤儿文件永远堆在存储里,
@ -264,6 +274,13 @@ func (s *IngestService) processRunway(ctx context.Context, job model.IngestJob,
return
}
// 4.5) 全局近似去重标记:与「已晋升图片」比对汉明距离,命中则留痕(is_duplicate=1 + dup_of),
// 不丢弃、交后台人工裁决(只拦新增,不碰存量)。比对失败仅告警,不阻断入库。
s.tagDuplicates(ctx, phashList, func(i int, dupOf string) {
draftImages[i].IsDuplicate = 1
draftImages[i].DupOf = dupOf
})
// 5) 写草稿表(status=pending),等待后台审核通过后再晋升正式表
draft := &model.BrandRunwayDraft{
JobID: job.ID,
@ -309,7 +326,7 @@ func (s *IngestService) fetchLookImages(ctx context.Context, looks []dto.RunwayL
lookIdx := li + 1
if look.Main != "" {
order++
url, key, err := s.downloadOne(ctx, look.Main, order, prefix)
url, key, ph, err := s.downloadOne(ctx, look.Main, order, prefix)
if err != nil {
failed = true
} else {
@ -323,6 +340,7 @@ func (s *IngestService) fetchLookImages(ctx context.Context, looks []dto.RunwayL
SortOrder: uint32(order),
LookIndex: uint32(lookIdx),
IsDetail: 0,
Phash: ph,
})
}
}
@ -331,7 +349,7 @@ func (s *IngestService) fetchLookImages(ctx context.Context, looks []dto.RunwayL
continue
}
order++
url, key, err := s.downloadOne(ctx, d, order, prefix)
url, key, ph, err := s.downloadOne(ctx, d, order, prefix)
if err != nil {
failed = true
continue
@ -343,6 +361,7 @@ func (s *IngestService) fetchLookImages(ctx context.Context, looks []dto.RunwayL
SortOrder: uint32(order),
LookIndex: uint32(lookIdx),
IsDetail: 1,
Phash: ph,
})
}
}
@ -358,8 +377,8 @@ func (s *IngestService) processStreet(ctx context.Context, job model.IngestJob,
return
}
// 2) 下载图片并上传到存储(七牛优先,失败兜底本地)
cover, imgs, keys, imgFailed := s.fetchImages(ctx, p.Images, "street")
// 2) 下载图片并上传到存储(七牛优先,失败兜底本地);同时算 pHash 供近似去重。
cover, imgs, phs, keys, imgFailed := s.fetchImages(ctx, p.Images, "street")
if len(p.Images) > 0 && imgFailed {
// 单图失败=整任务失败:先回滚本批已上传的图(七牛 + 本地兜底),避免孤儿文件永远堆在存储里,
// 然后按指数退避自动重试,达上限才置 failed 等后台手动重试。
@ -390,8 +409,16 @@ func (s *IngestService) processStreet(ctx context.Context, job model.IngestJob,
Image: img,
Name: fmt.Sprintf("Look %d", i+1),
SortOrder: uint32(i + 1),
Phash: phs[i],
})
}
// 3.5) 全局近似去重标记(与走秀同逻辑,只拦新增、留痕不删)。
s.tagDuplicates(ctx, phs, func(i int, dupOf string) {
rows[i].IsDuplicate = 1
rows[i].DupOf = dupOf
})
if err := s.repo.CreateStreetSnapDraftImages(ctx, rows); err != nil {
s.failOrRetry(ctx, job.ID, "create street draft images: "+err.Error())
return
@ -399,16 +426,18 @@ func (s *IngestService) processStreet(ctx context.Context, job model.IngestJob,
_ = s.repo.MarkDone(ctx, job.ID)
}
// fetchImages 下载图片并上传到存储,返回 (cover 地址, 全部图片地址, 已成功上传对象的 key 列表, 是否有任意一张失败)。
// fetchImages 下载图片并上传到存储,返回 (cover 地址, 全部图片地址, 各图 pHash, 已成功上传对象的 key 列表, 是否有任意一张失败)。
// prefix 为七牛 key 前缀(runway/ 或 street/)。只要任意一张下载/上传失败,failed 即置 true,
// 调用方据此把整条任务判为失败(不再写草稿),并拿 keys 回滚本批已上传的对象,符合「单图失败=整任务失败」策略。
func (s *IngestService) fetchImages(ctx context.Context, urls []string, prefix string) (string, []string, []string, bool) {
// 返回的 pHash 与图片地址按索引对齐(phash=0 表示解码失败未计算,比对时跳过)。
func (s *IngestService) fetchImages(ctx context.Context, urls []string, prefix string) (string, []string, []uint64, []string, bool) {
cover := ""
out := make([]string, 0, len(urls))
phashes := make([]uint64, 0, len(urls))
keys := make([]string, 0, len(urls))
failed := false
for i, u := range urls {
url, key, err := s.downloadOne(ctx, u, i, prefix)
url, key, ph, err := s.downloadOne(ctx, u, i, prefix)
if err != nil {
failed = true
continue
@ -417,9 +446,10 @@ func (s *IngestService) fetchImages(ctx context.Context, urls []string, prefix s
cover = url
}
out = append(out, url)
phashes = append(phashes, ph)
keys = append(keys, key)
}
return cover, out, keys, failed
return cover, out, phashes, keys, failed
}
// cleanupUploads 删除一批本批次成功上传的对象(七牛 + 本地兜底),用于任务失败回滚:
@ -442,19 +472,20 @@ func (s *IngestService) cleanupUploads(ctx context.Context, keys []string) {
}
// downloadOne 把单张远程图下载后上传到存储(七牛优先,失败兜底本地),
// 返回可直接写入数据库的访问地址(七牛为完整 https URL,本地为相对 /uploads 路径)。
func (s *IngestService) downloadOne(ctx context.Context, u string, idx int, prefix string) (string, string, error) {
// 返回 (访问地址, 对象 key, 感知哈希, error)。访问地址可直接写入数据库
// (七牛为完整 https URL,本地为相对 /uploads 路径);感知哈希基于原始字节算一次,供入库时近似去重。
func (s *IngestService) downloadOne(ctx context.Context, u string, idx int, prefix string) (string, string, uint64, error) {
resp, err := s.httpClient.Get(u)
if err != nil {
return "", "", err
return "", "", 0, err
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
return "", "", fmt.Errorf("status %d", resp.StatusCode)
return "", "", 0, fmt.Errorf("status %d", resp.StatusCode)
}
data, err := io.ReadAll(resp.Body)
if err != nil {
return "", "", err
return "", "", 0, err
}
ext := path.Ext(u)
if ext == "" || len(ext) > 5 {
@ -467,16 +498,74 @@ func (s *IngestService) downloadOne(ctx context.Context, u string, idx int, pref
key := fmt.Sprintf("%s/%s%s", prefix, hash, ext)
ct := resp.Header.Get("Content-Type")
// 感知哈希:同一份字节在此算一次(decode 失败时 ph=0,比对时跳过,不阻断入库)。
ph := phash.Of(data)
if ph == 0 {
log.Printf("[warn] ingest pHash 未计算(解码失败或非 jpeg/png/gif 格式) url=%s", u)
}
// 主上传器(七牛)
if url, err := s.uploader.Upload(ctx, key, data, ct); err == nil {
return url, key, nil
return url, key, ph, nil
} else if s.local != nil {
// 兜底本地,避免图片完全丢失
if lurl, lerr := s.local.Upload(ctx, key, data, ct); lerr == nil {
return lurl, key, nil
return lurl, key, ph, nil
} else {
return "", "", err
return "", "", 0, err
}
}
return "", "", err
return "", "", 0, err
}
// tagDuplicates 对一批图片(phashList 与 apply 下标对齐)做全局近似去重标记:
// 与「已晋升图片」的 phash 库比汉明距离(≤ phash.DefaultThreshold 即近似重复),
// 命中则调用 apply(i, dupOf) 由调用方把第 i 张图标 IsDuplicate=1、DupOf=命中图 uid。
// 不丢弃任何图、仅留痕(交后台人工裁决),契合「只拦新增、全局跨所有图、标记不删」。
// 比对库拉取失败仅告警并跳过(不阻断入库);phash=0 的图不比对、不误杀。
func (s *IngestService) tagDuplicates(ctx context.Context, phashList []uint64, apply func(i int, dupOf string)) {
uids, err := s.matchDuplicates(ctx, phashList)
if err != nil {
log.Printf("[warn] ingest 近似去重比对失败 err=%v(跳过标记,不阻断入库)", err)
return
}
for i, u := range uids {
if u != "" {
apply(i, u)
}
}
}
// matchDuplicates 返回与 phashList 等长的 dup_of uid 切片(""=未命中近似重复)。
// 对每张新图,在已晋升图片库里找汉明距离 ≤ 阈值的命中,取距离最近者,
// 按其 kind(runway/street)编码成对应 hashid 类型作为 dup_of。
func (s *IngestService) matchDuplicates(ctx context.Context, phashList []uint64) ([]string, error) {
refs, err := s.repo.ListImagePHashes(ctx)
if err != nil {
return nil, err
}
out := make([]string, len(phashList))
for i, ph := range phashList {
if ph == 0 {
continue // 未计算 phash 的图不比对(避免误杀)
}
bestUID := ""
bestDist := phash.DefaultThreshold + 1
for _, ref := range refs {
if ref.Phash == 0 {
continue
}
d := phash.Hamming(ph, ref.Phash)
if d <= phash.DefaultThreshold && d < bestDist {
var typ byte = hashid.TypeRunwayImage
if ref.Kind == "street" {
typ = hashid.TypeSnapImage
}
bestUID = hashid.EncodeWithType(ref.ID, typ)
bestDist = d
}
}
out[i] = bestUID
}
return out, nil
}

View File

@ -0,0 +1,161 @@
#!/usr/bin/env bash
#
# setup_pg_docker.sh — 用 Docker 起 PostgreSQL 16 + pgvector 本地开发环境
#
# 用法(在 WSL 终端里,不要用 Windows 的 CMD/PowerShell):
# sudo bash setup_pg_docker.sh
#
# 行为:
# 1) 先卸载上次用 apt 装失败的 PostgreSQL 残留(清理 pgdg 源 / 坏 key / 包),幂等。
# 2) 确保 docker 可用(缺失则尝试 apt 装 docker.io 并起守护进程;仍不行则给出 Docker Desktop 指引)。
# 3) docker compose up -d 起 pgvector 容器(幂等:已存在则不变)。
# 4) 等就绪后验证 version() 与 vector 扩展版本。
#
# 仅用于本地开发 / 迁移验证。生产请改强密码并单独评审配置。
#
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
COMPOSE_FILE="$SCRIPT_DIR/docker-compose.yml"
DB_USER=fashion
DB_PASS="fashion_dev_2026"
DB_NAME=fashion
log() { echo -e "\033[32m==>\033[0m $*"; }
warn() { echo -e "\033[33m⚠️ \033[0m $*"; }
if [ "$(id -u)" -ne 0 ]; then
echo "请以 root 运行: sudo bash $0"; exit 1
fi
# ---------- 1) 卸载上次 apt 版 PostgreSQL 的残留 ----------
if command -v psql >/dev/null 2>&1 || [ -f /etc/apt/sources.list.d/pgdg.list ]; then
log "卸载上次 apt 版 PostgreSQL 残留(清理失败残留,幂等)"
pg_ctlcluster "$(ls /etc/postgresql 2>/dev/null | head -1)" main stop 2>/dev/null \
|| service postgresql stop 2>/dev/null \
|| true
apt-get remove --purge -y 'postgresql-*' 2>/dev/null || true
rm -f /etc/apt/sources.list.d/pgdg.list
rm -f /usr/share/postgresql-common/pgdg/apt.postgresql.org.asc \
/usr/share/postgresql-common/pgdg/apt.postgresql.org.gpg
apt-get autoremove -y 2>/dev/null || true
log "apt 版 PostgreSQL 残留已清理"
else
log "未发现 apt 版 PostgreSQL,跳过卸载"
fi
# ---------- 2) 确保 docker 可用 ----------
if command -v docker >/dev/null 2>&1 && docker info >/dev/null 2>&1; then
log "docker 可用"
else
if command -v docker >/dev/null 2>&1; then
warn "docker 已安装但守护进程未起,尝试启动"
service docker start 2>/dev/null || (dockerd >/var/log/docker.log 2>&1 &) || true
sleep 3
fi
if ! command -v docker >/dev/null 2>&1 || ! docker info >/dev/null 2>&1; then
warn "docker 不可用,尝试 apt 安装 docker.io"
apt-get update -y
if apt-get install -y docker.io; then
service docker start 2>/dev/null || (dockerd >/var/log/docker.log 2>&1 &) || true
sleep 3
fi
fi
if ! command -v docker >/dev/null 2>&1 || ! docker info >/dev/null 2>&1; then
echo "❌ 仍无法使用 docker。请二选一:"
echo " A) 装 Docker Desktop (Windows),安装时勾选 'Use WSL 2',"
echo " 装好后在其 Settings > Resources > WSL Integration 里启用你的 WSL 发行版,重启 WSL 后重试;"
echo " B) 或在本 WSL 内: sudo apt-get install -y docker.io && sudo service docker start"
exit 1
fi
fi
# 选 docker compose 命令(v2 插件优先,回退 v1)
if docker compose version >/dev/null 2>&1; then
DC=(docker compose)
elif command -v docker-compose >/dev/null 2>&1; then
DC=(docker-compose)
else
echo "❌ 未找到 docker compose / docker-compose,请安装 Docker Compose 后重试"; exit 1
fi
# ---------- 2.5) 配置国内镜像源加速(避免直连 Docker Hub 慢) ----------
MIRRORS='["https://docker.m.daocloud.io","https://hub-mirror.c.163.com","https://mirror.baidubce.com"]'
if docker context ls 2>/dev/null | grep -qw "desktop-linux" || [[ "${DOCKER_HOST:-}" == *"npipe"* ]]; then
# Docker Desktop(守护进程在 Windows 侧):WSL 内的 daemon.json 不生效,必须在 GUI 配
warn "检测到 Docker Desktop:WSL 内的 daemon.json 不影响 Windows 侧守护进程。"
echo " 请在 Windows 的 Docker Desktop > Settings > Docker Engine 的 JSON 中加入:"
echo " \"registry-mirrors\": $MIRRORS"
echo " 然后点 Apply & Restart;重启后再直接跑: docker compose -f $COMPOSE_FILE up -d"
echo " (本脚本不再自动拉起,避免与 Docker Desktop 守护进程冲突)"
exit 1
elif ! docker info 2>/dev/null | grep -q "docker.m.daocloud.io"; then
# docker.io 跑在 WSL 内:直接写 daemon.json 并重启守护进程
if [ ! -f /etc/docker/daemon.json ] || ! grep -q registry-mirrors /etc/docker/daemon.json; then
log "配置国内镜像源加速(写入 /etc/docker/daemon.json 并重启 docker 守护进程)"
cat > /etc/docker/daemon.json <<JSON
{
"registry-mirrors": $MIRRORS
}
JSON
service docker restart 2>/dev/null || systemctl restart docker 2>/dev/null \
|| (dockerd --registry-mirror=https://docker.m.daocloud.io >/var/log/docker.log 2>&1 &) || true
sleep 3
else
log "daemon.json 已含 registry-mirrors,跳过"
fi
# 等守护进程重新就绪
for i in $(seq 1 15); do
docker info >/dev/null 2>&1 && break
sleep 1
done
fi
# ---------- 3) 起容器(幂等) ----------
log "启动 PostgreSQL + pgvector 容器(docker compose up -d)"
"${DC[@]}" -f "$COMPOSE_FILE" up -d
# ---------- 4) 等就绪 ----------
log "等待数据库就绪(最多 30s)"
ready=0
for i in $(seq 1 30); do
if docker exec pgvector pg_isready -U "$DB_USER" -d "$DB_NAME" >/dev/null 2>&1; then
ready=1; break
fi
sleep 1
done
if [ "$ready" -ne 1 ]; then
echo "❌ 数据库未就绪,查看日志: docker logs pgvector"; exit 1
fi
# ---------- 5) 验证 ----------
log "验证安装"
docker exec -i pgvector psql -U "$DB_USER" -d "$DB_NAME" \
-c "SELECT version();" \
-c "SELECT extname, extversion FROM pg_extension WHERE extname='vector';"
cat <<EOF
✅ PostgreSQL 16 + pgvector 就绪(Docker,容器名 pgvector)
连接串 : postgres://$DB_USER:$DB_PASS@localhost:5432/$DB_NAME
命令行 : docker exec -it pgvector psql -U $DB_USER -d $DB_NAME
启停 : docker compose -f $COMPOSE_FILE up -d / stop
清数据 : docker compose -f $COMPOSE_FILE down -v
(可选)CLIP / DINOv2 embedding 表示例:
CREATE TABLE image_embedding (
id BIGSERIAL PRIMARY KEY,
image_uid VARCHAR(32) NOT NULL, -- 对应你现有的 hashid uid
kind SMALLINT NOT NULL, -- 0=runway 1=street
embedding vector(512), -- 512 维特征(CLIP ViT-B/32 或 DINOv2)
created_at INTEGER NOT NULL DEFAULT 0
);
CREATE INDEX image_embedding_vec_idx
ON image_embedding USING hnsw (embedding vector_cosine_ops);
-- 去重查询:找最近邻
SELECT image_uid, 1 - (embedding <=> '[...]'::vector) AS sim
FROM image_embedding
WHERE kind = 0
ORDER BY embedding <=> '[...]'::vector
LIMIT 20;
EOF