bug fixed

.idea/sonarlint/issuestore/index.pb

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cb771d2e71f1c7b0a253bccda5df0922f65c71590347796dd86cce5a272c9e0c
-size 190
+oid sha256:4b4951c46d564e515a40d50a2cdf6b46376c146df6a56092e672ecc1f965a7f2
+size 123

0_Introduction.py

@@ -7,33 +7,47 @@ initialize_level()
 
 LEVEL = 0
 
+import cv2
+
+
 
 def intro_page():
-    st.header("Face Recognition")
-    st.subheader("Introduction")
-
-    st.write(
-        """
-        Welcome to the interactive tutorial on creating your very own Face Recognition Application!
-        """
-    )
-
-    st.image(
-        "https://static.wixstatic.com/media/abb909_35aa4b27e4b840659a20fd69f0a18354~mv2.gif",
-        use_column_width=True,
-    )
-        
-    st.write(
-        """
-        In this tutorial, you will learn how to build a simple application that can detect and recognise faces from a given photo. Face recognition has revolutionized 
-    various industries, including security, entertainment, and personal identification. Are you ready to dive into the exciting world of face recognition?
-    """
-    )
-
-    st.info(f"Click on the button below to start the tutorial!")
-
-    if st.button("I am Ready!"):
-        complete_level(LEVEL)
+    st.title("Webcam Live Feed")
+    run = st.checkbox('Run')
+    FRAME_WINDOW = st.image([])
+    camera = cv2.VideoCapture(0)
+
+    while run:
+        _, frame = camera.read()
+        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        FRAME_WINDOW.image(frame)
+    else:
+        st.write('Stopped')
+    # st.header("Face Recognition")
+    # st.subheader("Introduction")
+
+    # st.write(
+    #     """
+    #     Welcome to the interactive tutorial on creating your very own Face Recognition Application!
+    #     """
+    # )
+    #
+    # st.image(
+    #     "https://static.wixstatic.com/media/abb909_35aa4b27e4b840659a20fd69f0a18354~mv2.gif",
+    #     use_column_width=True,
+    # )
+    #
+    # st.write(
+    #     """
+    #     In this tutorial, you will learn how to build a simple application that can detect and recognise faces from a given photo. Face recognition has revolutionized
+    # various industries, including security, entertainment, and personal identification. Are you ready to dive into the exciting world of face recognition?
+    # """
+    # )
+    #
+    # st.info(f"Click on the button below to start the tutorial!")
+    #
+    # if st.button("I am Ready!"):
+    #     complete_level(LEVEL)
 
 
 render_page(intro_page, LEVEL)

pages/1_Technology Behind It.py

@@ -1,27 +1,12 @@
 import streamlit as st
 from utils.levels import complete_level, render_page, initialize_level
 from utils.login import initialize_login
-import cv2
 
 LEVEL = 1
 
 initialize_login()
 initialize_level()
 
-def returnCameraIndexes():
-    # checks the first 10 indexes.
-    index = 0
-    arr = []
-    i = 10
-    while i > 0:
-        cap = cv2.VideoCapture(index)
-        if cap.read()[0]:
-            arr.append(index)
-            cap.release()
-        index += 1
-        i -= 1
-    return arr
-
 def step1_page():
     st.header("Technology Behind It")
     st.markdown(
@@ -60,29 +45,6 @@ def step1_page():
 
     st.info("Click on the button below to continue!")
 
-    """TEST"""
-    input_type = st.radio("Select the Input Type", ["Image upload", "Camera", "Live Video"])
-    st.write(returnCameraIndexes())
-    if input_type == "Live Video":
-        cam = cv2.VideoCapture(0)
-        if not cam.isOpened():
-            print("Cannot open camera")
-            exit()
-        cam.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
-        cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
-        FRAME_WINDOW = st.image([])
-
-        while True:
-            ret, frame = cam.read()
-            if not ret:
-                st.error("Failed to capture frame from camera")
-                st.info("Please turn off the other app that is using the camera and restart app")
-                st.stop()
-            # image, name, face_id = recognize(frame, tolerance)
-            image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-            # Display name and ID of the person
-            FRAME_WINDOW.image(image)
-
     if st.button("Complete"):
         complete_level(LEVEL)