Merge develop

CMakeLists.txt

@@ -5,15 +5,13 @@ include_directories("${PROJECT_BINARY_DIR}")
 
 
 
-project(hello_world)                
-
 set(SOURCE_EXE main.cpp)            
 
-set(SOURCE_LIB1 sift_test.cpp)
-set(SOURCE_LIB2 sift_1b.cpp)
+set(SOURCE_LIB sift_1b.cpp)
+
+add_library(sift_test STATIC ${SOURCE_LIB})
 
-add_library(sift_test STATIC ${SOURCE_LIB1} ${SOURCE_LIB2})
 
-add_executable(main ${SOURCE_EXE})  
+add_executable(main ${SOURCE_EXE})
 SET( CMAKE_CXX_FLAGS  "-Ofast -lrt -DNDEBUG -std=c++11 -DHAVE_CXX0X -openmp -march=native -fpic -w -fopenmp -ftree-vectorize -ftree-vectorizer-verbose=0" )
 target_link_libraries(main sift_test) 

README.md

@@ -1,6 +1,10 @@
 # Hnsw - Approximate nearest neighbor search
 Hnsw paper code for the 200M SIFT experiment.
 
+NEW: Added simple python bindings with incremental construction(reusing some nmslib code, only L2 is now supported)
+
+
+####Test reproduction steps:
 To download and extract the bigann dataset:
 ```bash
 python3 download_bigann.py
@@ -18,6 +22,37 @@ To run the test on 200M SIFT subset:
 
 The size of the bigann subset (in millions) is controlled by the variable **subset_size_milllions** hardcoded in **sift_1b.cpp**.
 
+
+#### Python bindings example
+```python
+import hnswlib
+import numpy as np
+
+dim = 128
+num_elements = 10000
+
+data=np.float32(np.random.random((num_elements,dim)))
+data_labels=np.arange(num_elements)
+
+p = hnswlib.Index(space='l2', dim=dim) #Only l2 is supported currently
+p.init_index(max_elements=10000, ef_construction=200, M=16)
+
+# Element insertion be called several times:
+int_labels = p.add_items(data, data_labels)
+
+
+p.set_ef(50)
+# Query dataset, k - number of closest elements
+# Return numpy arrays 
+labels, distances = p.knn_query(data, k=1)
+
+```
+To compile run:
+```bash
+cd python_bindings
+python3 setup.py install
+```
+
 The repo contrains some parts of the Non-Metric Space Library's code https://github.com/searchivarius/nmslib
 
 References: