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feat(core): perceptual hashes for finding similar photos
A 64-bit difference hash of each thumbnail, stored in the new photos.similar_hash column (schema 34), and the queries the similar-photo finder needs: what is left to hash, progress, and the sets of shots that look alike. Sets made only of byte-identical copies are left to the duplicate finder. A refresh keeps a hash unless the photo's bytes changed. The daemon pass, the control request and the GUI are not built yet; see PLAN.md.
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@@ -9,7 +9,7 @@ use super::Db;
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use crate::Result;
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/// Current schema version. Bump on every forward migration added below.
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pub(super) const SCHEMA_VERSION: i64 = 33;
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pub(super) const SCHEMA_VERSION: i64 = 34;
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impl Db {
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pub(super) fn migrate(&self) -> Result<()> {
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@@ -300,6 +300,22 @@ impl Db {
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tx.execute_batch(MIGRATION_V33)?;
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}
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}
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if current < 34 {
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// Same guards as V26-V33.
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let has_column: bool = tx.query_row(
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"SELECT COUNT(*) FROM pragma_table_info('photos') WHERE name = 'similar_hash'",
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[],
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|row| row.get::<_, i64>(0),
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)? > 0;
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let has_photos: bool = tx.query_row(
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"SELECT COUNT(*) FROM sqlite_master WHERE type = 'table' AND name = 'photos'",
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[],
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|row| row.get::<_, i64>(0),
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)? > 0;
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if has_photos && !has_column {
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tx.execute_batch(MIGRATION_V34)?;
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}
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}
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tx.execute(
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"INSERT INTO sync_state (key, value) VALUES ('schema_version', ?1)
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ON CONFLICT(key) DO UPDATE SET value = excluded.value",
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@@ -1006,3 +1022,14 @@ ALTER TABLE photos ADD COLUMN place_id INTEGER;
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CREATE INDEX IF NOT EXISTS idx_photos_place ON photos(place_id);
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UPDATE photos SET resolved_at = NULL;
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";
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/// Schema v34: what each photo looks like, for finding similar ones.
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///
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/// `similar_hash` is a 64-bit difference hash of the photo's thumbnail (see
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/// `crate::similar`): resized and re-encoded copies of one picture land a few
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/// bits apart, where the server's `content_hash` only matches byte-identical
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/// files. `NULL` until the daemon has hashed the thumbnail, which it does as
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/// thumbnails arrive and when the similar-photo finder asks for the rest.
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const MIGRATION_V34: &str = "
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ALTER TABLE photos ADD COLUMN similar_hash INTEGER;
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";
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@@ -98,6 +98,8 @@ struct Learned {
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content_hash: Option<String>,
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main_uid: Option<String>,
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location: Option<(f64, f64)>,
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/// What its thumbnail looks like (see [`crate::similar`]).
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similar_hash: Option<i64>,
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/// When this photo's node was last resolved, kept so a refresh that skips it
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/// does not make it look unresolved again.
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resolved_at: Option<i64>,
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@@ -293,7 +295,7 @@ impl Db {
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let learned: HashMap<String, Learned> = {
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let mut stmt = tx.prepare(
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"SELECT uid, name, ratio, thumb_state, media_type, favorite, content_hash, \
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main_uid, resolved_at, latitude, longitude FROM photos",
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main_uid, resolved_at, latitude, longitude, similar_hash FROM photos",
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)?;
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let rows = stmt.query_map([], |r| {
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Ok((
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@@ -310,6 +312,7 @@ impl Db {
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location: r
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.get::<_, Option<f64>>(9)?
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.zip(r.get::<_, Option<f64>>(10)?),
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similar_hash: r.get(11)?,
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},
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))
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})?;
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@@ -332,6 +335,10 @@ impl Db {
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carried.name = row.name.clone();
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carried.media_type = row.media_type.clone();
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carried.favorite = row.favorite.unwrap_or(false);
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// New bytes may show another picture: hash it again.
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if row.content_hash != carried.content_hash {
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carried.similar_hash = None;
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}
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carried.content_hash = row.content_hash.clone();
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carried.main_uid = row.main_uid.clone();
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carried.location = row.location;
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@@ -373,9 +380,9 @@ impl Db {
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"INSERT INTO photos
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(uid, capture_time, name, ratio, thumb_state, seq, media_type, kind, favorite,
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content_hash, main_uid, group_key, resolved_at, latitude, longitude,
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place_id)
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place_id, similar_hash)
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VALUES (?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9, ?10, ?11, ?12, ?13, ?14, ?15,
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?16)",
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?16, ?17)",
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)?;
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for (seq, ((row, carried, kind), group_key)) in
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resolved.iter().zip(group_keys.iter()).enumerate()
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@@ -400,6 +407,7 @@ impl Db {
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.location
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.and_then(|(lat, lon)| crate::places::nearest(lat, lon))
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.map(|city| city.id),
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carried.similar_hash,
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])?;
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}
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}
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@@ -771,6 +779,106 @@ impl Db {
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Ok(sets)
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}
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/// Shots whose look hasn't been hashed yet, by the uid of the photo the
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/// grid shows for each, newest first, at most `limit`. Videos, and photos
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/// with no thumbnail to hash, are left out. A shot counts as hashed once
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/// any of its files is, since they all show one picture.
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pub fn photos_unhashed(&self, limit: usize) -> Result<Vec<StoredPhoto>> {
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let uids: Vec<String> = {
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let conn = self.read();
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let mut stmt = conn.prepare(
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"SELECT COALESCE(group_key, uid) AS k FROM photos \
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GROUP BY k \
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HAVING MAX(similar_hash) IS NULL \
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AND MAX(kind != ?1 AND thumb_state != ?2) \
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ORDER BY MAX(capture_time) DESC LIMIT ?3",
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)?;
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stmt.query_map(
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params![
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crate::control::PhotoKind::Video.as_i64(),
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THUMB_NONE,
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limit as i64
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],
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|r| r.get(0),
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)?
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.collect::<rusqlite::Result<_>>()?
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};
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self.photos_by_uid(&uids)
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}
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/// Record the look of photo `uid`: its difference hash, or
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/// [`crate::similar::NO_HASH`] when its thumbnail gave none.
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pub fn photo_set_similar_hash(&self, uid: &str, hash: u64) -> Result<()> {
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let conn = self.conn.lock();
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conn.execute(
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"UPDATE photos SET similar_hash = ?2 WHERE uid = ?1",
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params![uid, hash as i64],
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)?;
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Ok(())
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}
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/// How many shots have been hashed, out of how many could be.
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pub fn similar_progress(&self) -> Result<(usize, usize)> {
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let conn = self.read();
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let (hashed, total): (i64, i64) = conn.query_row(
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"SELECT COUNT(*) FILTER (WHERE hashed), COUNT(*) FROM \
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(SELECT MAX(similar_hash) IS NOT NULL AS hashed FROM photos \
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GROUP BY COALESCE(group_key, uid) \
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HAVING MAX(similar_hash) IS NOT NULL \
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OR MAX(kind != ?1 AND thumb_state != ?2))",
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params![crate::control::PhotoKind::Video.as_i64(), THUMB_NONE],
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|r| Ok((r.get(0)?, r.get(1)?)),
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)?;
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Ok((hashed.max(0) as usize, total.max(0) as usize))
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}
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/// Sets of shots that look alike (see [`crate::similar`]), one photo per
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/// shot in capture order, and the sets newest first. A set whose photos
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/// are all byte-identical copies is left to [`Self::photo_duplicates`].
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pub fn photo_similar(&self) -> Result<Vec<Vec<StoredPhoto>>> {
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let rows: Vec<(String, u64, Option<String>)> = {
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let conn = self.read();
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let mut stmt = conn.prepare(
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"SELECT COALESCE(group_key, uid) AS k, MAX(similar_hash), \
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MAX(content_hash) FILTER (WHERE uid = COALESCE(group_key, uid)) \
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FROM photos GROUP BY k \
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HAVING MAX(similar_hash) IS NOT NULL AND MAX(similar_hash) != ?1",
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)?;
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stmt.query_map(params![crate::similar::NO_HASH as i64], |r| {
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Ok((r.get(0)?, r.get::<_, i64>(1)? as u64, r.get(2)?))
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})?
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.collect::<rusqlite::Result<_>>()?
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};
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let hashes: Vec<u64> = rows.iter().map(|(_, hash, _)| *hash).collect();
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let found: Vec<Vec<usize>> = crate::similar::sets(&hashes)
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.into_iter()
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.filter(|set| {
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let first = &rows[set[0]].2;
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first.is_none() || set.iter().any(|&i| rows[i].2 != *first)
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})
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.collect();
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let uids: Vec<String> = found.iter().flatten().map(|&i| rows[i].0.clone()).collect();
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let mut stored: HashMap<String, StoredPhoto> = self
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.photos_by_uid(&uids)?
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.into_iter()
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.map(|photo| (photo.uid.clone(), photo))
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.collect();
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let mut sets: Vec<Vec<StoredPhoto>> = found
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.iter()
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.map(|set| {
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let mut photos: Vec<StoredPhoto> = set
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.iter()
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.filter_map(|&i| stored.remove(&rows[i].0))
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.collect();
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photos.sort_by_key(|p| p.capture_time);
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photos
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})
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.filter(|set| set.len() > 1)
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.collect();
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sets.sort_by_key(|set| std::cmp::Reverse(set.iter().map(|p| p.capture_time).max()));
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Ok(sets)
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}
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/// Per-tab counts for the Photos page subtitle: `(photos, videos, raw)`.
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pub fn photos_counts(&self) -> Result<(usize, usize, usize)> {
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use crate::control::PhotoKind;
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@@ -406,6 +406,76 @@ fn duplicates_list_the_copy_to_keep_first() {
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assert_eq!(uids, [vec!["filed", "copy"], vec!["jpeg", "stray"]]);
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}
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/// Shots that look alike form a set, one photo per shot, while a set of
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/// byte-identical copies is left to the duplicate finder.
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#[test]
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fn similar_photos_group_by_look_and_skip_exact_copies() {
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let db = Db::open_in_memory().unwrap();
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db.photos_replace(&[
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hashed("big", 500, "IMG_1.JPG", "h1"),
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hashed("small", 400, "IMG_1-small.JPG", "h2"),
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hashed("copy", 300, "IMG_2.JPG", "h3"),
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hashed("copy2", 200, "IMG_2(1).JPG", "h3"),
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hashed("other", 100, "IMG_3.JPG", "h4"),
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hashed("flat", 50, "IMG_4.JPG", "h5"),
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])
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.unwrap();
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let look = 0x0f0f_3c3c_5a5a_9696_u64;
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db.photo_set_similar_hash("big", look).unwrap();
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db.photo_set_similar_hash("small", look ^ 0b101).unwrap();
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db.photo_set_similar_hash("copy", !look).unwrap();
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db.photo_set_similar_hash("copy2", !look).unwrap();
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db.photo_set_similar_hash("other", look ^ 0xffff_ffff)
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.unwrap();
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db.photo_set_similar_hash("flat", crate::similar::NO_HASH)
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.unwrap();
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let sets = db.photo_similar().unwrap();
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let uids: Vec<Vec<&str>> = sets
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.iter()
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.map(|set| set.iter().map(|p| p.uid.as_str()).collect())
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.collect();
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assert_eq!(uids, [vec!["small", "big"]]);
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assert_eq!(db.similar_progress().unwrap(), (6, 6));
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}
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/// What is left to hash skips videos and hashed shots, and a hash survives a
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/// refresh unless the photo's bytes changed.
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#[test]
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fn similar_hashes_are_kept_until_the_photo_changes() {
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let db = Db::open_in_memory().unwrap();
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let resolved = |uid: &str, hash: &str| TimelineRow {
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resolved_at: Some(1),
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..hashed(uid, 100, &format!("{uid}.JPG"), hash)
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};
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db.photos_replace(&[
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resolved("a", "h1"),
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resolved("b", "h2"),
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hashed("clip", 50, "clip.mp4", "h3"),
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])
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.unwrap();
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db.photo_set_similar_hash("a", 7).unwrap();
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db.photo_set_similar_hash("b", 9).unwrap();
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let left = |db: &Db| -> Vec<String> {
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db.photos_unhashed(10)
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.unwrap()
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.into_iter()
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.map(|p| p.uid)
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.collect()
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};
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assert!(left(&db).is_empty());
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assert_eq!(db.similar_progress().unwrap(), (2, 2));
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db.photos_replace(&[
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resolved("a", "h1"),
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resolved("b", "h2-edited"),
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hashed("clip", 50, "clip.mp4", "h3"),
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])
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.unwrap();
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assert_eq!(left(&db), ["b"]);
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assert_eq!(db.similar_progress().unwrap(), (1, 2));
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}
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/// Trashing the file a group is shown as leaves the rest of the group on the
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/// timeline instead of pointing at a photo that is gone.
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#[test]
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@@ -20,6 +20,7 @@ pub mod sdkcache;
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pub mod search;
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pub mod service;
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pub mod shell;
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pub mod similar;
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pub mod syncignore;
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pub mod takeout;
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pub mod tray;
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@@ -0,0 +1,193 @@
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//! Telling photos apart by what they show rather than by their bytes.
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//!
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//! The server's content hash only matches byte-identical files. A photo that
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//! was resized, re-encoded or sent through a messenger is another file, so the
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//! similar-photo finder hashes each thumbnail instead: a 64-bit difference
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//! hash ("dHash"), which compares neighbouring brightness in a 9×8 grid. Two
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//! copies of one picture land a few bits apart, and different pictures about
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//! half of the bits apart.
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/// Hashes this many bits apart or fewer show the same picture.
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pub const SIMILAR_BITS: u32 = 6;
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/// Stored for a photo whose thumbnail was looked at and gave no usable hash
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/// (it couldn't be decoded, or is one flat colour), so it isn't looked at
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/// again. A real hash is never 0: a picture that would hash to 0 has no
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/// brightness changes, which [`difference_hash`] turns down as flat.
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pub const NO_HASH: u64 = 0;
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/// Samples of the grid that differ by less than this in brightness, all of
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/// them, make a flat picture — a black frame, a blank page — whose hash is
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/// noise and would match every other flat picture.
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const FLAT: u8 = 8;
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/// The difference hash of an 8-bit greyscale image `width` px wide, rows
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/// stored one after another in `luma`. `None` for an empty or flat image.
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pub fn difference_hash(width: usize, height: usize, luma: &[u8]) -> Option<u64> {
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if width == 0 || height == 0 || luma.len() < width * height {
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return None;
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}
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// Box-average down to 9×8, so every source pixel counts once and the hash
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// doesn't depend on which pixels a nearest-neighbour pick happens to hit.
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let mut grid = [[0u8; 9]; 8];
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for (gy, row) in grid.iter_mut().enumerate() {
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let (y0, y1) = span(gy, 8, height);
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for (gx, cell) in row.iter_mut().enumerate() {
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let (x0, x1) = span(gx, 9, width);
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let mut sum = 0u64;
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for y in y0..y1 {
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sum += luma[y * width + x0..y * width + x1]
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.iter()
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.map(|&v| u64::from(v))
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.sum::<u64>();
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}
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*cell = (sum / ((y1 - y0) * (x1 - x0)) as u64) as u8;
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}
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}
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let (min, max) = grid
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.iter()
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.flatten()
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.fold((u8::MAX, 0), |(min, max), &v| (min.min(v), max.max(v)));
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if max - min < FLAT {
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return None;
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}
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let mut hash = 0u64;
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for row in &grid {
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for pair in row.windows(2) {
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hash = hash << 1 | u64::from(pair[0] < pair[1]);
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}
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}
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(hash != NO_HASH).then_some(hash)
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}
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/// The source pixels `from..to` that cell `i` of `cells` covers along an edge
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/// of `len` px; never empty, even for an edge shorter than the grid.
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fn span(i: usize, cells: usize, len: usize) -> (usize, usize) {
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let from = (i * len / cells).min(len - 1);
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let to = ((i + 1) * len / cells).max(from + 1);
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(from, to)
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}
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/// Whether two hashes show the same picture.
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pub fn alike(a: u64, b: u64) -> bool {
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(a ^ b).count_ones() <= SIMILAR_BITS
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}
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/// Group `hashes` into sets of alike ones, by index, each set in index order
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/// and the sets by their first index. A hash alike to none other is in no
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/// set. Alike is taken as catching: a burst of shots each a little different
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/// from the last is one set.
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pub fn sets(hashes: &[u64]) -> Vec<Vec<usize>> {
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// Two hashes at most SIMILAR_BITS apart agree on at least one of their
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// eight bytes, as long as SIMILAR_BITS < 8. So only hashes sharing some
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// byte are compared, not every pair of the library.
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const _: () = assert!(SIMILAR_BITS < 8);
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let mut parent: Vec<usize> = (0..hashes.len()).collect();
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fn root(parent: &mut [usize], mut i: usize) -> usize {
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while parent[i] != i {
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parent[i] = parent[parent[i]];
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i = parent[i];
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}
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i
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}
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for byte in 0..8 {
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let mut buckets: Vec<Vec<usize>> = vec![Vec::new(); 256];
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for (i, &hash) in hashes.iter().enumerate() {
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buckets[(hash >> (byte * 8)) as u8 as usize].push(i);
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}
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for bucket in &buckets {
|
||||
for (n, &a) in bucket.iter().enumerate() {
|
||||
for &b in &bucket[n + 1..] {
|
||||
if alike(hashes[a], hashes[b]) {
|
||||
let (ra, rb) = (root(&mut parent, a), root(&mut parent, b));
|
||||
if ra != rb {
|
||||
parent[ra.max(rb)] = ra.min(rb);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
let mut by_root: std::collections::BTreeMap<usize, Vec<usize>> = Default::default();
|
||||
for i in 0..hashes.len() {
|
||||
let r = root(&mut parent, i);
|
||||
by_root.entry(r).or_default().push(i);
|
||||
}
|
||||
by_root.into_values().filter(|set| set.len() > 1).collect()
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
/// A 90×80 picture: a bright disc on a gradient.
|
||||
fn picture(width: usize, height: usize) -> Vec<u8> {
|
||||
let mut luma = Vec::with_capacity(width * height);
|
||||
for y in 0..height {
|
||||
for x in 0..width {
|
||||
let (fx, fy) = (x as f64 / width as f64, y as f64 / height as f64);
|
||||
let disc = ((fx - 0.3).powi(2) + (fy - 0.6).powi(2)).sqrt() < 0.2;
|
||||
let v = if disc { 240.0 } else { 40.0 + 120.0 * fx * fy };
|
||||
luma.push(v as u8);
|
||||
}
|
||||
}
|
||||
luma
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn a_resized_copy_hashes_alike() {
|
||||
let big = difference_hash(900, 800, &picture(900, 800)).unwrap();
|
||||
let small = difference_hash(91, 79, &picture(91, 79)).unwrap();
|
||||
assert!(
|
||||
alike(big, small),
|
||||
"{} bits apart",
|
||||
(big ^ small).count_ones()
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn a_different_picture_hashes_apart() {
|
||||
let one = difference_hash(90, 80, &picture(90, 80)).unwrap();
|
||||
let mirrored: Vec<u8> = picture(90, 80)
|
||||
.chunks(90)
|
||||
.flat_map(|row| row.iter().rev().copied().collect::<Vec<_>>())
|
||||
.collect();
|
||||
let other = difference_hash(90, 80, &mirrored).unwrap();
|
||||
assert!(!alike(one, other));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn a_flat_picture_has_no_hash() {
|
||||
assert_eq!(difference_hash(64, 64, &[17; 64 * 64]), None);
|
||||
assert_eq!(difference_hash(0, 0, &[]), None);
|
||||
assert_eq!(difference_hash(4, 4, &[0; 3]), None);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn a_picture_smaller_than_the_grid_still_hashes() {
|
||||
let luma: Vec<u8> = (0..4 * 3).map(|i| (i * 20) as u8).collect();
|
||||
assert!(difference_hash(4, 3, &luma).is_some());
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn alike_hashes_form_sets_and_catch_on() {
|
||||
let a = 0x0123_4567_89ab_cdef_u64;
|
||||
let hashes = [
|
||||
a,
|
||||
!a,
|
||||
a ^ 0b111,
|
||||
a ^ 0b111 ^ (0b1111 << 40),
|
||||
0x5555_0000_ffff_aaaa,
|
||||
];
|
||||
assert_eq!(sets(&hashes), vec![vec![0, 2, 3]]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn hashes_apart_in_most_bytes_are_still_found() {
|
||||
// One bit apart in each of six bytes: six bits in all, and only the
|
||||
// top two bytes agree.
|
||||
let a = 1u64 << 63;
|
||||
let b = (0..6).fold(a, |h, byte| h | 1 << (byte * 8));
|
||||
assert_eq!(sets(&[a, b]), vec![vec![0, 1]]);
|
||||
}
|
||||
}
|
||||
@@ -11,6 +11,9 @@ scratch (user data in `staging/` and `recovery/` is never touched by this).
|
||||
|
||||
## [Unreleased]
|
||||
|
||||
Schema: **34**. Photos gain a `similar_hash` column for the coming similar-photo finder. It
|
||||
stays empty until the daemon hashes thumbnails, so updating reads and downloads nothing.
|
||||
|
||||
## [2.3.0] — 2026-09-28
|
||||
|
||||
Schema: **33**. Photos gain their location; the first timeline refresh after updating reads
|
||||
|
||||
Reference in new issue
Block a user