test

.idea/sonarlint/issuestore/index.pb

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:87862bf18d4db63602fc54955aabfc69f91a027a381476ed3f14861ad89db28c
-size 254
+oid sha256:98baa20a68c7cd3b08884b0ec10d7c0e70c67528fd2364fbdef7501776bfd332
+size 321

pages/3_Training the Model.py

@@ -21,7 +21,7 @@ PKL_PATH = 'dataset/database.pkl'
 
 def step3_page():
     st.header("Training the Model")
-    st.subheader("Face encoding")
+    st.subheader("Face encoding and training")
     st.markdown(
         """
     ### What is Face Encoding?
@@ -59,17 +59,17 @@ def step3_page():
             face_name = img.split("_")[0]
             cols[i].image(os.path.join(img_dir, img), use_column_width=True)
             cols[i].write(face_name)
-    st.info("Now it's your turn to train the model! Click on the button below to train the model with your data to generate face encodings!")
+    st.info("Now it's your turn to train the model and generate face encodings! Click on the button below to train the model with your data to generate face encodings!")
     if st.button("Train Model"):
-        my_bar = st.progress(0, text="Training....")
+        # my_bar = st.progress(0, text="Training....")
         if len(images) > 0:
             database = get_database(PKL_PATH)
-            for i in range(100):
-                time.sleep(0.1)
-                my_bar.progress(i, text="Training....")
-            my_bar.progress(100, text="Successfully Trained!")
-            st.success("Model trained successfully!")
-            st.info("Now, lets generate face encodings for each face in known-face database using the model you just trained!")
+            # for i in range(100):
+            #     time.sleep(0.1)
+            #     my_bar.progress(i, text="Training....")
+            # my_bar.progress(100, text="Successfully Trained!")
+            # st.success("Model trained successfully!")
+            # st.info("Now, lets generate face encodings for each face in known-face database using the model you just trained!")
             my_bar = st.progress(0, text="Generating face encodings...")
             for i, img in enumerate(images):
                 face_image = face_recognition.load_image_file(os.path.join(img_dir, img))
@@ -87,7 +87,7 @@ def step3_page():
                                    'encoding': my_face_encoding}
                     with open(PKL_PATH, 'wb') as f:
                         pkl.dump(database, f)
-                time.sleep(0.5)
+                time.sleep(1)
                 my_bar.progress(int((i + 1) / len(images) * 100), text="Generating face encodings...")
             my_bar.progress(100, text="Successfully encoded all the known faces!")
             st.success("Face encoding completed successfully!")