mirror of
https://github.com/cgzirim/seek-tune.git
synced 2025-12-17 17:04:22 +00:00
It works better than the recent, the downside is that it finds matches for silent recordings.
105 lines
2.8 KiB
Go
105 lines
2.8 KiB
Go
package shazam
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import (
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"fmt"
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"math"
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"song-recognition/utils"
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"sort"
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"time"
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)
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type Match struct {
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SongID uint32
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SongTitle string
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SongArtist string
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YouTubeID string
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Timestamp uint32
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Score float64
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}
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// FindMatches processes the audio samples and finds matches in the database
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func FindMatches(audioSamples []float64, audioDuration float64, sampleRate int) ([]Match, time.Duration, error) {
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startTime := time.Now()
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logger := utils.GetLogger()
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spectrogram, err := Spectrogram(audioSamples, sampleRate)
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if err != nil {
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return nil, time.Since(startTime), fmt.Errorf("failed to get spectrogram of samples: %v", err)
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}
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peaks := ExtractPeaks(spectrogram, audioDuration)
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fingerprints := Fingerprint(peaks, utils.GenerateUniqueID())
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addresses := make([]uint32, 0, len(fingerprints))
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for address := range fingerprints {
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addresses = append(addresses, address)
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}
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db, err := utils.NewDbClient()
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if err != nil {
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return nil, time.Since(startTime), err
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}
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defer db.Close()
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m, err := db.GetCouples(addresses)
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if err != nil {
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return nil, time.Since(startTime), err
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}
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matches := map[uint32][][2]uint32{} // songID -> [(sampleTime, dbTime)]
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timestamps := map[uint32][]uint32{}
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for address, couples := range m {
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for _, couple := range couples {
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matches[couple.SongID] = append(matches[couple.SongID], [2]uint32{fingerprints[address].AnchorTimeMs, couple.AnchorTimeMs})
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timestamps[couple.SongID] = append(timestamps[couple.SongID], couple.AnchorTimeMs)
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}
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}
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scores := analyzeRelativeTiming(matches)
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var matchList []Match
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for songID, points := range scores {
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song, songExists, err := db.GetSongByID(songID)
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if !songExists {
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logger.Info(fmt.Sprintf("song with ID (%v) doesn't exist", songID))
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continue
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}
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if err != nil {
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logger.Info(fmt.Sprintf("failed to get song by ID (%v): %v", songID, err))
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continue
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}
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sort.Slice(timestamps[songID], func(i, j int) bool {
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return timestamps[songID][i] < timestamps[songID][j]
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})
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match := Match{songID, song.Title, song.Artist, song.YouTubeID, timestamps[songID][0], points}
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matchList = append(matchList, match)
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}
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sort.Slice(matchList, func(i, j int) bool {
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return matchList[i].Score > matchList[j].Score
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})
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return matchList, time.Since(startTime), nil
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}
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// AnalyzeRelativeTiming checks for consistent relative timing and returns a score
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func analyzeRelativeTiming(matches map[uint32][][2]uint32) map[uint32]float64 {
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scores := make(map[uint32]float64)
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for songID, times := range matches {
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count := 0
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for i := 0; i < len(times); i++ {
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for j := i + 1; j < len(times); j++ {
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sampleDiff := math.Abs(float64(times[i][0] - times[j][0]))
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dbDiff := math.Abs(float64(times[i][1] - times[j][1]))
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if math.Abs(sampleDiff-dbDiff) < 100 { // Allow some tolerance
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count++
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}
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}
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}
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scores[songID] = float64(count)
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}
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return scores
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}
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