bug fixed images

pages/3_Face Encodings.py

@@ -8,12 +8,21 @@ import time
 import face_recognition
 import json
 import numpy as np
+from collections import defaultdict
 
 initialize_login()
 initialize_level()
 
 LEVEL = 3
 
+PKL_PATH = 'dataset/database.pkl'
+information = defaultdict(dict)
+
+def get_database():
+    with open(PKL_PATH,'rb') as f:
+        database = pkl.load(f)
+    return database
+
 def step3_page():
     st.header("Feature encoding")
     st.markdown(
@@ -58,16 +67,31 @@ def step3_page():
     st.subheader("Lets create face encodings for the known-faces.")
     # face_encodings_dict = {}
     if st.button("Create Face Encodings"):
+        database = get_database()
         my_bar = st.progress(0, text="Generating face encodings...")
         if len(images) > 0:
             for i, img in enumerate(images):
                 face_image = face_recognition.load_image_file(os.path.join(img_dir, img))
                 my_face_encoding = face_recognition.face_encodings(face_image)
+                face_name = img.split("_")[0]
+                face_id = img.split(".")[0]
+
+                # check if id already exists
+                existing_id = [i for i in database.keys()]
+                if face_id in existing_id:
+                    st.error(f"Encoding already created for : {face_id}")
+                else:
+                    database[face_id] = {'name': face_name,
+                                         'encoding': my_face_encoding}
+                    with open(PKL_PATH, 'wb') as f:
+                        pkl.dump(database, f)
+
                 my_bar.progress(int((i + 1) / len(images) * 100), text="Generating face encodings...")
-                np.save(os.path.join(face_encodings_dir, img.split("_")[0]+".npy"), my_face_encoding)
-                # face_encodings_dict[img.split("_")[1]] = my_face_encoding.tolist()
+                # np.save(os.path.join(face_encodings_dir, img.split("_")[0]+".npy"), my_face_encoding)
+                # # face_encodings_dict[img.split("_")[1]] = my_face_encoding.tolist()
             my_bar.progress(100, text="Successfully encoded all the known faces!")
             st.success("Face encoding completed successfully!")
+            st.write(database)
             # with open(os.path.join(".sessions", get_login()["username"], "face_encodings.json"), "w") as write_file:
             #     json.dump(face_encodings_dict, write_file, indent=4)
             complete_level(LEVEL)