bug fixed

.idea/sonarlint/issuestore/index.pb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb771d2e71f1c7b0a253bccda5df0922f65c71590347796dd86cce5a272c9e0c
+size 190

pages/4_Trying It Out.py

@@ -30,15 +30,15 @@ def step4_page():
     )
     # Select input type
     st.info("Select your input type to analyze!")
-    input_type = st.radio("Select the Input Type", ["Image", "Camera"])
+    input_type = st.radio("Select the Input Type", ["Image upload", "Camera", "Live Video"])
     # Put slide to adjust tolerance
     tolerance = st.slider("Tolerance", 0.0, 1.0, 0.5, 0.01)
     st.info(
         "Tolerance is the threshold for face recognition. The lower the tolerance, the more strict the face recognition. The higher the tolerance, the more loose the face recognition.")
 
-    if input_type == "Image":
+    if input_type == "Image upload":
         st.title("Face Recognition App")
-        uploaded_images = st.file_uploader("Upload", type=['jpg', 'png', 'jpeg'], accept_multiple_files=True)
+        uploaded_images = st.file_uploader("Please upload image(s) to try it out!", type=['jpg', 'png', 'jpeg'], accept_multiple_files=True)
         if len(uploaded_images) != 0:
             # Read uploaded image with face_recognition
             for image in uploaded_images:
@@ -47,6 +47,16 @@ def step4_page():
                 st.image(image)
         else:
             st.info("Please upload an image")
+    elif input_type == "Camera":
+        st.title("Face Recognition App")
+        uploaded_image = st.camera_input("Take a picture")
+        if uploaded_image:
+            # Read uploaded image with face_recognition
+            image = face_recognition.load_image_file(uploaded_image)
+            image, name, face_id = recognize(image, tolerance)
+            st.image(image)
+        else:
+            st.info("Please take an image")
     else:
         st.title("Face Recognition App")
         # Camera Settings

utils/inference.py

@@ -10,7 +10,6 @@ PKL_PATH = 'dataset/database.pkl'
 
 def recognize(image,tolerance):
     database = get_database(PKL_PATH)
-    st.write(database)
     known_encoding = [database[id]['encoding'] for id in database.keys()]
     name = 'Unknown'
     face_id = 'Unknown'