Update app.py

app.py

@@ -25,17 +25,17 @@ conf_threshold = float(st.sidebar.slider("신뢰도 임계값을 선택하세요
 input = None 
 if source_radio == "IMAGE":
     st.sidebar.header("이미지 파일 업로드")
-    input = st.sidebar.file_uploader("이미지 파일을 선택하세요", type=("jpg", "png"))
+    input = st.sidebar.file_uploader("이미지 파일을 선택하세요.", type=("jpg", "png"))
     if input is not None:
         uploaded_image = Image.open(input)
-        uploaded_image_cv = cv2.cvtColor(np.array(uploaded_image), cv2.COLOR_RGB2BGR)
+        uploaded_image_cv = cv2.cvtColor(numpy.array(uploaded_image), cv2.COLOR_RGB2BGR)
         boxes, resized_image = utils.predict_image(uploaded_image_cv, conf_threshold = conf_threshold)
         result_image = utils.convert_result_to_image(uploaded_image_cv, resized_image, boxes, conf_labels=False)
         st.image(result_image, channels = "RGB")
-        st.markdown(f"<h4 style='color: blue;'><strong>The result of running the AI inference on an image.</strong></h4>", unsafe_allow_html=True)
+        st.markdown(f"<h4 style='color: blue;'><strong>이미지에서 AI 추론을 실행한 결과 입니다.</strong></h4>", unsafe_allow_html=True)
     else: 
         st.image("data/intel_rnb.jpg")
-        st.write("Click on 'Browse Files' in the sidebar to run inference on an image." )
+        st.write("'Browse Files' 버튼을 클릭하여 이미지에서 AI 추론을 시작합니다." )
 
 def play_video(video_source):
     camera = cv2.VideoCapture(video_source)
@@ -55,7 +55,25 @@ def play_video(video_source):
                 visualized_image = utils.convert_result_to_image(frame, resized_image, boxes, conf_labels=False)
             except:
                 visualized_image = frame
-            st_frame요", type=("mp4"))
+            st_frame.image(visualized_image, channels = "BGR")
+            video_row.append(cv2.cvtColor(visualized_image,cv2.COLOR_BGR2RGB))
+            frame_count +=1 
+            progress_bar.progress(frame_count/total_frames, text=None)
+    
+        else:
+            progress_bar.empty()
+            camera.release()
+            st_frame.empty()
+            break
+        clip = mpy.ImageSequenceClip(video_row, fps = fps)
+        clip.write_videofile(temp_file_2.name)
+        st.video(temp_file_2.name)
+
+# 파일 업로드 처리
+temporary_location = None
+if source_radio == "VIDEO":
+    st.sidebar.header("비디오 파일 업로드")
+    input_file = st.sidebar.file_uploader("비디오 파일을 선택하세요.", type=("mp4"))
     if input_file is not None:
         # 파일을 임시 경로에 저장
         g = io.BytesIO(input_file.read())
@@ -68,12 +86,12 @@ def play_video(video_source):
         play_video(temporary_location)
     else:
         st.video("data/sample_video.mp4")
-        st.write("Click on 'Browse Files' in the sidebar to run inference on a video.")
+        st.write("'Browse Files' 버튼을 클릭하여 영상에서 AI 추론을 시작합니다.")
 
 if source_radio == "WEBCAM":
     input = camera_input_live()
     uploaded_image = Image.open(input)
-    uploaded_image_cv = cv2.cvtColor(np.array(uploaded_image), cv2.COLOR_RGB2BGR)
+    uploaded_image_cv = cv2.cvtColor(numpy.array(uploaded_image), cv2.COLOR_RGB2BGR)
     boxes, resized_image = utils.predict_image(uploaded_image_cv, conf_threshold)
     visualized_image = utils.convert_result_to_image(uploaded_image_cv, resized_image, boxes, conf_labels=False)
     st.image(visualized_image, channels = "RGB")