Update app.py

app.py

@@ -1,53 +1,75 @@
 import streamlit as st
-import logging
+import cv2
 from utils import object_detection_brainai as odb
-
-# Setup logging
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
-
 object_detection = odb.ObjectDetectionModel()
 
 st.set_page_config(
-    page_title="객체 인식",
-    page_icon=":black_cat:",
-    layout="wide"
-)
+    page_title = "객체 인식", 
+    page_icon = ":black_cat:",
+    layout = "wide")
 
 st.title(":blue[Object Detection] :black_cat:")
 st.sidebar.header("메뉴")
 source_radio = st.sidebar.radio("선택하세요", ["IMAGE", "VIDEO", "GAME"])
-
-# Track when the random class is assigned
 if 'random_class' not in st.session_state:
     st.session_state.random_class = object_detection.call_class()
-    logging.info(f"Initialized random_class: {st.session_state.random_class}")
+    st.write('initialize')
 
-elif source_radio == "GAME":
+if source_radio == "IMAGE":
+    st.write(":green[왼쪽 메뉴 'Browse files' 버튼을 클릭하여 이미지 파일을 선택하면 AI 추론이 시작됩니다.]" )
+    st.sidebar.header("이미지 파일 업로드")
     input_img = st.sidebar.file_uploader("이미지 파일을 선택하세요.", type=("jpg", "png"))
-    col1, col2 = st.columns([3, 1])  
 
-    logging.info(f"Current random_class: {st.session_state.random_class}")
+    if input_img is not None:
+        result_img, detected_object = object_detection.process_image(input_img)
+        col1, col2 = st.columns(2)
+        with col1:
+            st.image(result_img)
+        with col2:
+            st.header(detected_object)
+    else:
+        col1, col2 = st.columns(2)
+        with col1:
+            st.image("data/table.jpg")
+        with col2:
+            st.header("Objects detected: chair, potted plant, vase, dining table")
+        
+elif source_radio == "VIDEO":
+    st.write(":green[왼쪽 메뉴 'Browse files' 버튼을 클릭하여 비디오 파일을 선택하면 AI 추론이 시작됩니다.]" )
+    st.sidebar.header("비디오 파일 업로드")
+    input_video = st.sidebar.file_uploader("비디오 파일을 선택하세요..", type=("mp4"))
+    if input_video is not None:
+        temp_file = object_detection.play_video(input_video)
+        st.video(temp_file)
+    else:
+        st.video("data/breakfast.mp4")
+
 
+elif source_radio == "GAME":
+    input_img = st.sidebar.file_uploader("이미지 파일을 선택하세요.", type=("jpg", "png"))
+    col1, col2 = st.columns([3, 1])  # Adjust the column widths as needed
     if input_img is None:
+        
+    
         with col1:
-            st.title(f':{st.session_state.random_class}: 있는 이미지를 업로드') 
-
+            st.title(f':{st.session_state.random_class}: 있는 이미지를 업로드')  # Display the header
+        
+        with col2:
+            if st.button('새로운 객체'):
+                st.session_state.random_class = object_detection.call_class()
     else:
         result_img, detected_object = object_detection.process_image(input_img)
-        logging.info(f"Detected objects: {detected_object}")
 
         with col1:
-            if st.session_state.random_class in detected_object:
+               
+            if st.session_state.random_class  in detected_object:
                 st.header(f':{st.session_state.random_class}: 찾습니다!')
-                logging.info(f"Correct object {st.session_state.random_class} found!")
+            
             else:
                 st.header(f':{st.session_state.random_class}: 찾을 수 없습니다')
-                logging.info(f"Object {st.session_state.random_class} NOT found!")
-
-            st.image(result_img)
-
-    with col2:
-        if st.button('새로운 객체'):
-            old_class = st.session_state.random_class
-            st.session_state.random_class = object_detection.call_class()
-            logging.info(f"Random class changed from {old_class} to {st.session_state.random_class}")
+            st.image(result_img) 
+        
+        with col2:
+            if st.button('새로운 객체'):
+                st.session_state.random_class = object_detection.call_class()
+                st.write("new object")