hmsearch
v0.1.0
Published
Efficiently find hashes within a certain hamming distance, typically used for perceptual hashing.
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Readme
hmsearch-node
Node API to HmSearch library. For more information on the library, see https://github.com/commonsmachinery/hmsearch
Installing
Currently the build only supports Linux. Pull requests for Mac and Windows are welcome!
Ensure that Kyoto Cabinet is installed. On Ubuntu:
apt-get install libkyotocabinet-dev kyotocabinet-util
When building from the git repository the hmsearch
submodule must be
initialised on first checkout:
git submodule init
git submodule update
API
For details on these methods, see the documentation for the C++ library: https://github.com/commonsmachinery/hmsearch/blob/master/hmsearch.h
The synchronous methods all throw an Error
if the operation fails,
with the message providing further details. The asynchronous methods
instead invoke the callback with the first argument set to an Error
instance.
Initialise a database
hmsearch.initdb(path, hash_bits, max_error, num_hashes, function(err) {...})
hmsearch.initdbSync(path, hash_bits, max_error, num_hashes)
Open a database
hmsearch.open(path, mode, function(err, db) {...})
db = hmsearch.openSync(path, mode)
Mode is either hmsearch.READONLY
or hmsearch.READWRITE
.
db
is a newly opened database object.
Close a database
db.close(function(err) {...})
db.closeSync()
Sync any changes to the database and close it. This must be done to release any locks on the database so other processes can access it.
It is safe to close the database multiple times.
The database is also closed when the database object is garbage collected.
Insert a hash
db.insert(hash, function(err) {...})
db.insertSync(hash)
hash
must be a hexadecimal string of the correct length.
Lookup a hash
db.lookupSync(query, [max_error], function(err, matches) {...})
matches = db.lookupSync(query, [max_error])
query
must be a hexadecimal string of the correct length. If
max_error
is provided and non-negative, it can further restrict the
accepted hamming distance than the database default.
matches
lists each matching hash as a hexadecimal string and the
hamming distance to the query
hash:
[ { hash: '0123456789abcdef', distance: 3 }, ... ]
matches
is an empty list if no hashes are found.
License
Copyright 2014 Commons Machinery http://commonsmachinery.se/
Distributed under an MIT license, please see LICENSE in the top dir.
Contact: [email protected]