anns / process /to_fvecs.py
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Update: generate efanna graph
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import numpy as np
def npy_to_fvecs(npy_file, fvecs_file):
# 从npy文件中加载数组
array = np.load(npy_file)
data_to_fvecs(array, fvecs_file)
def data_to_fvecs(array, fvecs_file):
# 打开fvecs文件进行写入
with open(fvecs_file, 'wb') as f:
# 获取数组的形状
num_vectors, vector_dim = array.shape
# 将每个向量写入fvecs文件
for vector in array:
# 向量的维度
f.write(np.array(vector_dim, dtype=np.int32).tobytes())
# 向量
f.write(vector.astype(np.float32).tobytes())
print("转换完成!")
# 调用函数进行转换
# npy_file = "input.npy" # 输入的npy文件路径
# fvecs_file = "output.fevecs"
# npy_to_fvecs(npy_file, fvecs_file)
if __name__=='__main__':
npy_file = '/tmp/test.npy' # 输入的npy文件路径
origin_file = "sift1m/sift_query.fvecs"
from sift1m.loading import fvecs_read
dataset,_,_ = fvecs_read(origin_file)
np.save(npy_file, dataset)
fvecs_file = "/tmp/output.fevecs"
npy_to_fvecs(npy_file, fvecs_file)