get faiss result

.gitignore

+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+.static_storage/
+.media/
+local_settings.py
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
+_index/
\ No newline at end of file

src/diary_cover_similarity.py

+import json
 import os
 import time
 
 import dlib
+import faiss
+import numpy as np
 
 from utils.images import face_to_vec, url_to_ndarray
 
@@ -9,28 +12,45 @@ from utils.images import face_to_vec, url_to_ndarray
 def main():
     img_url = "https://pic.igengmei.com/2020/07/03/1437/1b9975bb0b81-w"
     img = url_to_ndarray(img_url)
-    print(img)
 
     base_dir = os.getcwd()
     print("base_dir: " + base_dir)
     model_diry = os.path.join(base_dir, "_models")
     facerec_model_path = os.path.join(model_diry, "dlib_face_recognition_resnet_model_v1.dat")
     shape_model_path = os.path.join(model_diry, "shape_predictor_68_face_landmarks.dat")
+    faiss_index_path = os.path.join(base_dir, "_index", "current.index")
 
     face_rec = dlib.face_recognition_model_v1(facerec_model_path)
     face_detector = dlib.get_frontal_face_detector()
     shape_predictor = dlib.shape_predictor(shape_model_path)
 
-    faces = face_to_vec(img, face_rec, face_detector, shape_predictor)
-
-    print("faces:")
-    print(faces)
-    print("============")
-
-    for face in faces:
-        print(face)
-        print("\n")
-        print("-------------")
+    if img:
+        faces = face_to_vec(img, face_rec, face_detector, shape_predictor)
+
+        if faces:
+            for face in faces:
+                print(face)
+                print("\n")
+                print("-------------")
+                face_feature = np.array(json.loads(face["feature"]))
+
+            ids = [17418645]
+            ids_np = np.array(ids).astype("int")
+            faces_np = np.array([face_feature]).astype("float32")
+            print(ids_np)
+            print(faces_np)
+
+            index = faiss.IndexHNSWFlat(128, 32)
+            print("index: ")
+            print(index)
+            index2 = faiss.IndexIDMap(index)
+            print("index2: ")
+            print(index2)
+            index2.add_with_ids(faces_np, ids_np)
+            print("index2: ")
+            print(index2)
+        else:
+            print("no faces")
 
 
 if __name__ == "__main__":
@@ -38,4 +58,4 @@ if __name__ == "__main__":
 
     main()
 
-    print("total cost: " + str(time.time() - begin_time))
+    print("total cost: {:.2f}s".format(time.time() - begin_time))

src/utils/images.py

@@ -31,7 +31,7 @@ def file_to_ndarray(path):
 def face_to_vec(img, face_rec_f, face_detector_f, shape_predictor_f, max_size=700):
     start = time.time()
     orig_img = img
-    print("detect image...")
+    # print("detect image...")
     scale = 1
 
     height, width = img.shape[:2]