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Make image similarity search significantly faster. (#72)

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Syfaro 2020-10-15 08:43:59 -07:00 committed by GitHub
parent d2c7398bdd
commit a55fe3de9a
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3 changed files with 37 additions and 16 deletions

7
Cargo.lock generated
View file

@ -358,6 +358,7 @@ dependencies = [
"bk-tree",
"blake3",
"crossbeam-channel",
"hamming",
"humansize",
"image",
"img_hash",
@ -831,6 +832,12 @@ dependencies = [
"system-deps",
]
[[package]]
name = "hamming"
version = "0.1.3"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "65043da274378d68241eb9a8f8f8aa54e349136f7b8e12f63e3ef44043cc30e1"
[[package]]
name = "heck"
version = "0.3.1"

View file

@ -19,4 +19,5 @@ crossbeam-channel = "0.4.4"
# Needed by similar images
img_hash = "3.1"
bk-tree = "0.3"
image = "0.23"
image = "0.23"
hamming = "0.1"

View file

@ -3,7 +3,7 @@ use crate::common_directory::Directories;
use crate::common_items::ExcludedItems;
use crate::common_messages::Messages;
use crate::common_traits::{DebugPrint, PrintResults, SaveResults};
use bk_tree::{metrics, BKTree};
use bk_tree::BKTree;
use crossbeam_channel::Receiver;
use humansize::{file_size_opts as options, FileSize};
use img_hash::HasherConfig;
@ -36,17 +36,29 @@ pub struct StructSimilar {
pub similar_images: Vec<FileEntry>,
}
/// Type to store for each entry in the similarity BK-tree.
type Node = [u8; 8];
/// Distance metric to use with the BK-tree.
struct Hamming;
impl bk_tree::Metric<Node> for Hamming {
fn distance(&self, a: &Node, b: &Node) -> u64 {
hamming::distance_fast(a, b).unwrap()
}
}
/// Struct to store most basics info about all folder
pub struct SimilarImages {
information: Info,
text_messages: Messages,
directories: Directories,
excluded_items: ExcludedItems,
bktree: BKTree<String>,
bktree: BKTree<Node, Hamming>,
similar_vectors: Vec<StructSimilar>,
recursive_search: bool,
minimal_file_size: u64,
image_hashes: HashMap<String, Vec<FileEntry>>, // Hashmap with image hashes and Vector with names of files
image_hashes: HashMap<Node, Vec<FileEntry>>, // Hashmap with image hashes and Vector with names of files
stopped_search: bool,
}
@ -78,7 +90,7 @@ impl SimilarImages {
text_messages: Messages::new(),
directories: Directories::new(),
excluded_items: Default::default(),
bktree: BKTree::new(metrics::Levenshtein),
bktree: BKTree::new(Hamming),
similar_vectors: vec![],
recursive_search: true,
minimal_file_size: 1024 * 16, // 16 KB should be enough to exclude too small images from search
@ -233,18 +245,19 @@ impl SimilarImages {
similarity: Similarity::None,
};
let hasher = HasherConfig::new().to_hasher();
let hasher = HasherConfig::with_bytes_type::<[u8; 8]>().to_hasher();
let image = match image::open(current_file_name) {
Ok(t) => t,
Err(_) => continue 'dir, // Something is wrong with image
};
let hash = hasher.hash_image(&image);
let string_hash = hash.to_base64();
let mut buf = [0u8; 8];
buf.copy_from_slice(&hash.as_bytes());
self.bktree.add(string_hash.clone());
self.image_hashes.entry(string_hash.clone()).or_insert_with(Vec::<FileEntry>::new);
self.image_hashes.get_mut(&string_hash).unwrap().push(fe);
self.bktree.add(buf);
self.image_hashes.entry(buf).or_insert_with(Vec::<FileEntry>::new);
self.image_hashes.get_mut(&buf).unwrap().push(fe);
self.information.size_of_checked_images += metadata.len();
self.information.number_of_checked_files += 1;
@ -262,11 +275,11 @@ impl SimilarImages {
let hash_map_modification = SystemTime::now();
let mut new_vector: Vec<StructSimilar> = Vec::new();
for (string_hash, vec_file_entry) in &self.image_hashes {
for (hash, vec_file_entry) in &self.image_hashes {
if rx.is_some() && rx.unwrap().try_recv().is_ok() {
return false;
}
let vector_with_found_similar_hashes = self.bktree.find(string_hash.as_str(), 3).collect::<Vec<_>>();
let vector_with_found_similar_hashes = self.bktree.find(hash, 3).collect::<Vec<_>>();
if vector_with_found_similar_hashes.len() == 1 && vec_file_entry.len() == 1 {
// Exists only 1 unique picture, so there is no need to use it
continue;
@ -290,15 +303,15 @@ impl SimilarImages {
vec_similarity_struct.push(similar_struct);
}
for (similarity, hash) in vector_with_found_similar_hashes.iter() {
if *similarity == 0 && string_hash == *hash {
for (similarity, similar_hash) in vector_with_found_similar_hashes.iter() {
if *similarity == 0 && hash == *similar_hash {
// This was already readed before
continue;
} else if string_hash == *hash {
} else if hash == *similar_hash {
panic!("I'm not sure if same hash can have distance > 0");
}
for file_entry in self.image_hashes.get(*hash).unwrap() {
for file_entry in self.image_hashes.get(*similar_hash).unwrap() {
let mut file_entry = file_entry.clone();
file_entry.similarity = match similarity {
0 => Similarity::VeryHigh,