Update app.py

app.py

@@ -11,43 +11,84 @@ import cv2
 # Set page configuration
 st.set_page_config(page_title="Traffic Violation Detection", layout="wide")
 
-# Streamlit app layout
-st.title("Motorbike Violation Detection")
+st.title("🚦 Motorbike Violation Detection App")
+
+
+# Sidebar options
+option = st.sidebar.radio("Select Option:", ("Image", "Video", "Live Camera"))
+
 
-option = st.selectbox(
-    "Choose Input Type",
-    ("Image", "Video", "Live Camera")
-)
 
 if option == "Image":
+    st.header("🖼️ Upload and Process Image")
     uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
-    if uploaded_file is not None:
-        image = cv2.imread(uploaded_file)
-        process_image(image)
-        st.download_button("Download Result", data=image, file_name="result_image.jpg")
+    if uploaded_file:
+        image = Image.open(uploaded_file)
+        st.image(image, caption='Uploaded Image.', use_column_width=True)
+        if st.button("Process Image"):
+            with st.spinner("Processing..."):
+                with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp:
+                    image.save(tmp.name)
+                    frame = cv2.imread(tmp.name)
+                processed = process_image(tmp.name, "alfont_com_arial-1.ttf")
+                if processed is not None:
+                    st.image(processed, caption='Processed Image.', use_column_width=True)
+                    # Save processed image to temporary file for download
+                    _, img_encoded = cv2.imencode('.jpg', processed)
+                    st.download_button(
+                        label="📥 Download Image",
+                        data=img_encoded.tobytes(),
+                        file_name="processed_image.jpg",
+                        mime="image/jpeg"
+                    )
+                else:
+                    st.error("Failed to process the image.")
 
 elif option == "Video":
-    # Dynamically load video files from 'videos/' folder
-    video_folder = 'videos/'
-    video_files = [f for f in os.listdir(video_folder) if f.endswith(('.mp4', '.avi','.mov'))]
-    if video_files:
-        video_file = st.selectbox("Select a video", video_files)
-        if st.button("Process Video"):
-            process_video(os.path.join(video_folder, video_file))
-            st.download_button("Download Result", data=video_file, file_name="result_video.mp4")
-    else:
+    st.header("🎥 Select and Process Video")
+    video_files = [f for f in os.listdir("videos/") if f.endswith(('.mp4', '.avi', '.mov'))]
+    if not video_files:
         st.warning("No videos found in the 'videos/' folder.")
+    else:
+        selected_video = st.selectbox("Choose a video to process:", video_files)
+        video_path = os.path.join("videos/", selected_video)
+        st.video(video_path)
+        if st.button("Process Video"):
+            with st.spinner("Processing Video..."):
+                processed_path = process_video(video_path, "alfont_com_arial-1.ttf")
+                if processed_path and os.path.exists(processed_path):
+                    st.success("Video processed successfully!")
+                    st.video(processed_path)
+                    with open(processed_path, "rb") as file:
+                        st.download_button(
+                            label="📥 Download Processed Video",
+                            data=file,
+                            file_name="processed_video.mp4",
+                            mime="video/mp4"
+                        )
+                else:
+                    st.error("Failed to process the video.")
 
 elif option == "Live Camera":
-    st.write("Starting live camera...")
-    run = st.checkbox('Run Camera')
-    camera = cv2.VideoCapture(0)
-    FRAME_WINDOW = st.image([])
-
-    while run:
-        ret, frame = camera.read()
-        if ret:
-            process_frame(frame)
-            FRAME_WINDOW.image(frame)
-
-    camera.release()
+    st.header("📷 Live Camera Feed")
+    st.info("Live processing is active. Detected violations will be annotated on the video feed.")
+
+    # RTC Configuration for streamlit-webrtc
+    RTC_CONFIGURATION = RTCConfiguration({"iceServers": [{"urls": ["stun:stun.l.google.com:19302"]}]})
+
+    class VideoTransformer(VideoTransformerBase):
+        def __init__(self):
+            self.font_path = "alfont_com_arial-1.ttf"
+
+        def transform(self, frame):
+            img = frame.to_ndarray(format="bgr24")
+            processed_img = process_frame(img, self.font_path)
+            return processed_img
+
+    webrtc_ctx = webrtc_streamer(
+        key="live-camera",
+        rtc_configuration=RTC_CONFIGURATION,
+        video_transformer_factory=VideoTransformer,
+        media_stream_constraints={"video": True, "audio": False},
+        async_transform=True
+    )