mirror of
https://github.com/fumiama/paper-manager.git
synced 2026-06-05 16:00:25 +08:00
add GetDuplicateRate
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@@ -24,6 +24,8 @@ import (
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"github.com/corona10/goimagehash"
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base14 "github.com/fumiama/go-base16384"
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"github.com/fumiama/go-docx"
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"github.com/fumiama/paper-manager/backend/utils"
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)
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const (
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@@ -394,10 +396,38 @@ func (f *FileDatabase) AddFile(tempath string, reg *Regex, istemp bool, progress
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return data
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}(),
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Vector: func() []byte {
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plain := base14.BytesToString(sb.Bytes())
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words := utils.Segmenter.Cut(base14.BytesToString(sb.Bytes()), true)
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if len(words) == 0 {
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return nil
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}
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v := make(map[string]uint8, len(words)*2)
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for _, word := range words {
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v[word]++
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}
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data, err := json.Marshal(v)
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if err != nil {
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return nil
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}
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return data
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}(),
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}
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var q Question
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dupmap := make(map[string]float64, 64)
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FileDB.mu.RLock()
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err = FileDB.db.FindFor(FileTableQuestion, &q, "", func() error {
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r, err := q.GetDuplicateRate(que)
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if err != nil {
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return err
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}
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var buf [8]byte
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binary.LittleEndian.PutUint64(buf[:], q.ID)
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dupmap[hex.EncodeToString(buf[:])] = r
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return nil
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})
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FileDB.mu.RUnlock()
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if err == nil {
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}
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}
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}
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return file, nil
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@@ -415,13 +445,69 @@ type Question struct {
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ID uint64 // ID is the first 8 bytes of the Plain's md5
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Plain string // Plain is the plain text of the question (like markdown format)
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Images []byte // Images is json of the image dhash in XML, ex. ['rId1': '1234567890abcdef', ...]
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Vector []byte // Vector is json of {word: rate, ...} freq
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Dup []byte // Dup is json of Duplication struct
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Vector []byte // Vector is json of {word: freq, ...}
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Dup []byte // Dup is json of {queid: rate, ...}
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}
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// Duplication is the struct representation of Question.Dup
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type Duplication struct {
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ID string `json:"id"` // ID is hex string for json's 53 bits number
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Rate float64 `json:"rate"` // Rate is the avg(non-leaf) or max(leaf) similarity
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To []Duplication `json:"to,omitempty"`
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// GetDuplicateRate calc q & que's dup rate
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func (q *Question) GetDuplicateRate(que *Question) (float64, error) {
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v1, v2 := make(map[string]uint8, 64), make(map[string]uint8, 64)
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m1, m2 := make(map[string]string, 64), make(map[string]string, 64)
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err := json.Unmarshal(q.Images, &m1)
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if err != nil {
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return 0, err
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}
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err = json.Unmarshal(que.Images, &m2)
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if err != nil {
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return 0, err
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}
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err = json.Unmarshal(q.Vector, &v1)
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if err != nil {
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return 0, err
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}
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err = json.Unmarshal(que.Vector, &v2)
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if err != nil {
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return 0, err
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}
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imgdsts := uint64(0)
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for _, dhstr2 := range m2 {
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d, err := hex.DecodeString(dhstr2)
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if err != nil {
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return 0, err
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}
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dh2 := goimagehash.NewImageHash(binary.LittleEndian.Uint64(d), goimagehash.DHash)
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r := 0
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for _, dhstr1 := range m1 {
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d, err := hex.DecodeString(dhstr1)
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if err != nil {
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return 0, err
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}
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dh1 := goimagehash.NewImageHash(binary.LittleEndian.Uint64(d), goimagehash.DHash)
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dst, err := dh2.Distance(dh1)
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if err != nil {
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return 0, err
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}
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if dst > r {
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r = dst
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}
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}
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imgdsts += uint64(r)
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}
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imgdupr := float64(imgdsts) / float64(len(m2)) / 64.0
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v1space := make([]uint8, 0, len(v1)+len(v2))
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v2space := make([]uint8, 0, len(v1)+len(v2))
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for k, v := range v1 {
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v1space = append(v1space, v)
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if tv, ok := v2[k]; ok {
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v2space = append(v2space, tv)
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delete(v2, k)
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} else {
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v2space = append(v2space, 0)
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}
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}
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for _, v := range v2 {
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v1space = append(v1space, 0)
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v2space = append(v2space, v)
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}
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return utils.Similarity(v1space, v2space) + imgdupr/2.0, nil
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}
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