An experimental vector storage, built for AID Project.
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Step 1/2: Install faiss-cpu or faiss-gpu based on your system.
pip install faiss-cpu # or pip install faiss-gpu -
Step 2/2: Install FaissDB
pip install faissdb
It should suffice on Ubuntu/Debian system.
from faissdb.faissdb import FaissDB
from faissdb.config import FaissDBSettings
settings = FaissDBSettings()
db = FaissDB(settings)
# For the first time, create a partition with any name
db.create_partition('voc')
# Create a one-dimensional vector
feature = np.random.random((4096,))
# Put it in database
# here 1.jpg could be any string, that you want to indicate the file
db.put('voc', feature, '1.jpg')
# build the index
db.create_index('voc')
# Now perform KNN Query
# First reshape the feature, such that it becomes (k*d)
# where k is the number of vectors you want to consider
# In our case, we have a single query vector, hence k=1
# d is the dimension of the vectors.
feature = feature.reshape((1, 4096))
D, keys = db.knn_query('voc', feature, k=1)
# Since k=1, we always get the vector itself, hence D should only contains 0.
print(D)
for each in keys:
value = db.getVal('voc', each)
# The value should be 1.jpg, or the string you specified above.
print(value)