Update app.py

app.py

@@ -25,7 +25,7 @@ def show_autoplay_video(video_bytes: bytes, title: str = "Video"):
     st.markdown(video_html, unsafe_allow_html=True)
 
 ###############################################################################
-# Session state initialization (for uploaded processing results)
+# Session state initialization (for processed results)
 ###############################################################################
 if "processed_frames" not in st.session_state:
     st.session_state["processed_frames"] = []
@@ -45,22 +45,6 @@ st.set_page_config(
     initial_sidebar_state="expanded"
 )
 
-st.title("Fire Watch: Detecting fire using AI vision models")
-col1, col2 = st.columns(2)
-with col1:
-    st.image("https://huggingface.co/spaces/tstone87/ccr-colorado/resolve/main/Fire_1.jpeg", use_column_width=True)
-with col2:
-    st.image("https://huggingface.co/spaces/tstone87/ccr-colorado/resolve/main/Fire_3.png", use_column_width=True)
-
-st.markdown("""
-Fires in Colorado present a serious challenge, threatening urban communities, highways, and even remote areas. 
-Early detection is critical. Fire Watch uses the model YOLOv8 for real-time fire and smoke detection 
-in images and videos.
-""")
-st.markdown("---")
-st.header("Fire Detection:")
-
-
 ###############################################################################
 # SIDEBAR: Video input options, confidence, sampling options, and example selection
 ###############################################################################
@@ -106,7 +90,6 @@ processed_video_data = None  # For example pairs
 if example_option != "None":
     # Use example videos from remote URLs.
     if example_option == "T Example":
-        # For T Example: set your URLs for original and processed videos.
         orig_url = "https://huggingface.co/spaces/tstone87/ccr-colorado/resolve/main/T1.mp4"
         proc_url = "https://huggingface.co/spaces/tstone87/ccr-colorado/resolve/main/T2.mpg"
     elif example_option == "LA Example":
@@ -122,14 +105,12 @@ else:
     if source_file:
         file_type = source_file.type.split('/')[0]
         if file_type == 'image':
-            # For images, convert to video-like display (or you could run image detection).
             original_image = PIL.Image.open(source_file)
             buf = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
             original_image.save(buf.name, format="PNG")
             with open(buf.name, "rb") as f:
                 original_video_data = f.read()
         else:
-            # For video uploads, save to a temp file.
             tfile = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
             tfile.write(source_file.read())
             tfile.flush()
@@ -155,13 +136,11 @@ with col1:
 with col2:
     st.subheader("Result File")
     if example_option != "None":
-        # For example pairs, the processed video is already available.
         if processed_video_data:
             show_autoplay_video(processed_video_data, title="Processed Video")
         else:
             st.info("No processed video available in example.")
     else:
-        # For uploaded files, if a processed video is ready, show it.
         if st.session_state["shortened_video_ready"] and st.session_state["shortened_video_data"]:
             show_autoplay_video(st.session_state["shortened_video_data"], title="Processed Video")
         else:
@@ -172,7 +151,7 @@ with col2:
 ###############################################################################
 if example_option == "None" and source_file and source_file.type.split('/')[0] != 'image':
     if st.sidebar.button("Let's Detect Wildfire"):
-        # Reset any previous processed results.
+        # Reset previous processed results.
         st.session_state["processed_frames"] = []
         st.session_state["shortened_video_data"] = None
         st.session_state["shortened_video_ready"] = False
@@ -185,7 +164,7 @@ if example_option == "None" and source_file and source_file.type.split('/')[0] !
         width  = int(vidcap.get(cv2.CAP_PROP_FRAME_WIDTH))
         height = int(vidcap.get(cv2.CAP_PROP_FRAME_HEIGHT))
 
-        # Determine sampling interval based on option.
+        # Determine sampling interval.
         if video_option == "Original FPS":
             sample_interval = 1
             output_fps = orig_fps
@@ -211,7 +190,6 @@ if example_option == "None" and source_file and source_file.type.split('/')[0] !
                 res = model.predict(image, conf=confidence)
                 res_plotted = res[0].plot()[:, :, ::-1]
                 processed_frames.append(res_plotted)
-                # Update progress
                 if total_frames > 0:
                     progress_pct = int((frame_count / total_frames) * 100)
                     progress_text.text(f"Processing frame {frame_count} / {total_frames} ({progress_pct}%)")
@@ -227,10 +205,12 @@ if example_option == "None" and source_file and source_file.type.split('/')[0] !
         # Create shortened video from processed frames.
         if processed_frames:
             temp_video_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
-            fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+            # Use the 'avc1' codec (H.264) for better compatibility
+            fourcc = cv2.VideoWriter_fourcc(*'avc1')
             out = cv2.VideoWriter(temp_video_file.name, fourcc, output_fps, (width, height))
             for frame in processed_frames:
-                out.write(frame)
+                frame_out = cv2.convertScaleAbs(frame)
+                out.write(frame_out)
             out.release()
 
             with open(temp_video_file.name, 'rb') as video_file:
@@ -242,7 +222,7 @@ if example_option == "None" and source_file and source_file.type.split('/')[0] !
             st.error("No frames were processed from the video.")
 
 ###############################################################################
-# Always show the download button if a processed video is ready.
+# Always display the download button if a processed video is ready.
 ###############################################################################
 if st.session_state["shortened_video_ready"] and st.session_state["shortened_video_data"]:
     st.download_button(