Update streamlit_app.py
Browse files- streamlit_app.py +186 -197
streamlit_app.py
CHANGED
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@@ -30,12 +30,45 @@ def custom_excepthook(type, value, tb):
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# --- Streamlit Page Config ---
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st.set_page_config(
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page_title="
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page_icon="🎥",
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layout="wide",
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initial_sidebar_state="expanded"
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)
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# --- Custom CSS ---
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st.markdown("""
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<style>
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@@ -59,21 +92,6 @@ def custom_excepthook(type, value, tb):
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.stAlert {
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border-radius: 10px;
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}
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.stTabs [data-baseweb="tab-list"] {
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gap: 10px;
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}
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.stTabs [data-baseweb="tab"] {
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height: 50px;
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white-space: pre;
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background-color: #f0f2f6;
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border-radius: 4px 4px 0 0;
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padding: 10px 20px;
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margin-right: 5px;
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}
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.stTabs [aria-selected="true"] {
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background-color: #4CAF50;
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color: white;
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}
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.video-container {
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border: 2px dashed #4CAF50;
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border-radius: 10px;
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@@ -86,35 +104,26 @@ def custom_excepthook(type, value, tb):
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# --- Session State Initialization ---
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def initialize_session_state():
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"""Initialize all session state variables"""
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'last_bg_image_id': None,
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'process_complete': False
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}
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for key, value in defaults.items():
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if key not in st.session_state:
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st.session_state[key] = value
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# --- Video Processing ---
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def process_video(input_file, background, bg_type="image"):
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"""
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Process video with the selected background using SAM2 and MatAnyone pipeline.
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Returns the video bytes.
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"""
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logger.info("=" * 60)
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logger.info("
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logger.info("=" * 60)
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try:
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@@ -124,77 +133,78 @@ def process_video(input_file, background, bg_type="image"):
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temp_dir = temp_base / f"session_{int(time.time())}"
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temp_dir.mkdir(exist_ok=True)
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logger.info(f"
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# Save the uploaded video
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input_path = str(temp_dir / "input.mp4")
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logger.info(f"
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with open(input_path, "wb") as f:
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written = f.write(input_file.
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logger.info(f"
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if not os.path.exists(input_path):
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raise FileNotFoundError(f"
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logger.info(f"
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# Prepare background
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bg_path = None
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if bg_type == "image" and background is not None:
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logger.info("
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bg_cv = cv2.cvtColor(np.array(background), cv2.COLOR_RGB2BGR)
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bg_path = str(temp_dir / "background.jpg")
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cv2.imwrite(bg_path, bg_cv)
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logger.info(f"
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elif bg_type == "color"
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logger.info(f"
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color_hex = st.session_state.bg_color.lstrip('#')
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color_rgb = tuple(int(color_hex[i:i+2], 16) for i in (0, 2, 4))
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bg_path = str(temp_dir / "background.jpg")
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cv2.imwrite(bg_path, np.ones((100, 100, 3), dtype=np.uint8) * color_rgb[::-1])
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logger.info(f"
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#
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progress_placeholder = st.empty()
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status_placeholder = st.empty()
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def progress_callback(progress, message):
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progress = max(0, min(1, float(progress)))
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logger.info(f"
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progress_placeholder.progress(progress)
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status_placeholder.text(f"Status: {message}")
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#
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if torch.cuda.is_available():
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else:
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logger.
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# Process the video
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output_path = str(temp_dir / "output.mp4")
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click_points = [[0.5, 0.5]]
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logger.info("
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from pipeline.integrated_pipeline import TwoStageProcessor
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# Cache processor
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@st.cache_resource
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def load_processor(temp_dir_str):
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logger.info(f"
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return TwoStageProcessor(temp_dir=temp_dir_str)
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processor = load_processor(str(temp_dir))
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logger.info("
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try:
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logger.info("
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logger.info(f"
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logger.info(f"
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logger.info(f"
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logger.info(f" - Click points: {click_points}")
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success = processor.process_video(
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input_video=input_path,
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progress_callback=progress_callback
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)
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logger.info(f"
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except Exception as e:
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logger.error(f"
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raise
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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logger.info("🧹 GPU cache cleared")
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if not success:
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raise RuntimeError("
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#
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if not os.path.exists(output_path):
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logger.error(f"
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raise FileNotFoundError(f"Output video not created: {output_path}")
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output_size = os.path.getsize(output_path)
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logger.info(f"
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# Read
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logger.info("
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with open(output_path, 'rb') as f:
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video_bytes = f.read()
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logger.info(f"
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#
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try:
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logger.info(f"🧹 Cleaning up temp directory: {temp_dir}")
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shutil.rmtree(temp_dir)
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logger.info("
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except Exception as e:
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logger.warning(f"
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logger.info("=" * 60)
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logger.info("
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logger.info("=" * 60)
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return video_bytes
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except Exception as e:
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logger.error("=" * 60)
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logger.error(f"
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logger.error(traceback.format_exc())
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logger.error("=" * 60)
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st.error(f"An error occurred during processing: {str(e)}")
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# --- Main Application ---
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def main():
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st.title("
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st.markdown("---")
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# Initialize session state
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initialize_session_state()
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# Main layout
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col1, col2 = st.columns([1, 1], gap="large")
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st.header("1. Upload Video")
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uploaded = st.file_uploader(
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type=["mp4", "mov", "avi"],
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key="video_uploader"
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)
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#
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st.session_state.process_complete = False
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# Video preview
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st.markdown("### Video Preview")
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st.video(st.session_state.video_bytes_cache)
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else:
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st.info("No video uploaded yet")
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with col2:
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st.header("2. Background Settings")
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"Select Background Type:",
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["Image", "Color", "Blur"],
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horizontal=True,
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index=0,
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key="bg_type_radio"
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)
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if bg_type == "Image":
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bg_image = st.file_uploader(
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type=["jpg", "png", "jpeg"],
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key="bg_image_uploader"
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logger.info(f"🖼️ New background image: {bg_image.name if bg_image else 'None'}")
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st.session_state.last_bg_image_id = current_bg_id
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if bg_image is not None:
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st.session_state.bg_image_cache = Image.open(bg_image)
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st.session_state.
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# Background preview
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bg_preview_container = st.container()
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with bg_preview_container:
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if st.session_state.bg_image_cache is not None:
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st.image(
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st.session_state.bg_image_cache,
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caption="Selected Background",
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use_container_width=True
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)
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else:
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st.info("No background image uploaded yet")
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elif bg_type == "Color":
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selected_color = st.color_picker(
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st.session_state.bg_color,
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key="color_picker"
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logger.info(f"🎨 Color changed to: {selected_color}")
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st.session_state.bg_color = selected_color
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st.session_state.cached_color = selected_color
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color_rgb = tuple(int(selected_color.lstrip('#')[i:i+2], 16) for i in (0, 2, 4))
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color_display = np.zeros((100, 100, 3), dtype=np.uint8)
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color_display[:, :] = color_rgb[::-1]
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st.session_state.color_display_cache = color_display
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with color_preview_container:
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if st.session_state.color_display_cache is not None:
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st.image(st.session_state.color_display_cache, caption="Selected Color", width=200)
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st.header("3. Process & Download")
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background
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st.error("❌ Failed to process video. Please check the logs for details.")
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except Exception as e:
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logger.error(f"❌ Exception during processing: {str(e)}")
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logger.error(traceback.format_exc())
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st.error(f"❌ An error occurred: {str(e)}")
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finally:
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st.session_state.processing = False
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logger.info(f"🏁 Processing finished. Success: {st.session_state.process_complete}")
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# Show processed video
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if st.session_state.processed_video_bytes is not None and len(st.session_state.processed_video_bytes) > 0:
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st.markdown("---")
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st.markdown("###
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try:
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logger.info(f"
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st.video(st.session_state.processed_video_bytes)
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st.download_button(
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label="
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data=st.session_state.processed_video_bytes,
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file_name="processed_video.mp4",
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mime="video/mp4",
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use_container_width=True
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key="download_button"
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logger.info("✅ Video displayed successfully")
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except Exception as e:
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logger.error(f"
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logger.error(traceback.format_exc())
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st.error(f"Error displaying video: {str(e)}")
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if __name__ == "__main__":
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# --- Streamlit Page Config ---
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st.set_page_config(
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page_title="Advanced Video Background Replacer",
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page_icon="🎥",
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layout="wide",
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initial_sidebar_state="expanded"
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# --- GPU Diagnostic ---
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def check_gpu():
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"""Check GPU availability and log details"""
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logger.info("=" * 60)
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logger.info("GPU DIAGNOSTIC")
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logger.info("=" * 60)
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cuda_available = torch.cuda.is_available()
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logger.info(f"torch.cuda.is_available(): {cuda_available}")
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if cuda_available:
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logger.info(f"CUDA Version: {torch.version.cuda}")
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logger.info(f"Device Count: {torch.cuda.device_count()}")
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logger.info(f"Current Device: {torch.cuda.current_device()}")
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logger.info(f"Device Name: {torch.cuda.get_device_name(0)}")
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logger.info(f"Device Capability: {torch.cuda.get_device_capability(0)}")
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# Test GPU tensor
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try:
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test_tensor = torch.randn(100, 100).cuda()
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logger.info(f"GPU Test Tensor Created Successfully on: {test_tensor.device}")
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del test_tensor
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torch.cuda.empty_cache()
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except Exception as e:
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logger.error(f"GPU Test Failed: {e}")
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else:
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logger.warning("CUDA NOT AVAILABLE")
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logger.info(f"PyTorch Version: {torch.__version__}")
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logger.info(f"CUDA Built Version: {torch.version.cuda}")
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logger.info("=" * 60)
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return cuda_available
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# --- Custom CSS ---
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st.markdown("""
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<style>
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.stAlert {
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border-radius: 10px;
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}
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.video-container {
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border: 2px dashed #4CAF50;
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border-radius: 10px;
|
|
|
|
| 104 |
# --- Session State Initialization ---
|
| 105 |
def initialize_session_state():
|
| 106 |
"""Initialize all session state variables"""
|
| 107 |
+
if 'initialized' not in st.session_state:
|
| 108 |
+
st.session_state.initialized = True
|
| 109 |
+
st.session_state.uploaded_video = None
|
| 110 |
+
st.session_state.video_bytes_cache = None
|
| 111 |
+
st.session_state.bg_image_cache = None
|
| 112 |
+
st.session_state.bg_color = "#00FF00"
|
| 113 |
+
st.session_state.color_display_cache = None
|
| 114 |
+
st.session_state.processed_video_bytes = None
|
| 115 |
+
st.session_state.processing = False
|
| 116 |
+
st.session_state.process_complete = False
|
| 117 |
+
|
| 118 |
+
# Run GPU check on first init
|
| 119 |
+
gpu_available = check_gpu()
|
| 120 |
+
st.session_state.gpu_available = gpu_available
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 121 |
|
| 122 |
# --- Video Processing ---
|
| 123 |
def process_video(input_file, background, bg_type="image"):
|
| 124 |
+
"""Process video with the selected background using SAM2 and MatAnyone pipeline."""
|
|
|
|
|
|
|
|
|
|
| 125 |
logger.info("=" * 60)
|
| 126 |
+
logger.info("STARTING VIDEO PROCESSING")
|
| 127 |
logger.info("=" * 60)
|
| 128 |
|
| 129 |
try:
|
|
|
|
| 133 |
temp_dir = temp_base / f"session_{int(time.time())}"
|
| 134 |
temp_dir.mkdir(exist_ok=True)
|
| 135 |
|
| 136 |
+
logger.info(f"Temp directory: {temp_dir}")
|
| 137 |
|
| 138 |
+
# Save the uploaded video
|
| 139 |
input_path = str(temp_dir / "input.mp4")
|
| 140 |
+
logger.info(f"Writing video to {input_path}")
|
| 141 |
|
| 142 |
+
input_file.seek(0) # Ensure we're at the start
|
| 143 |
with open(input_path, "wb") as f:
|
| 144 |
+
written = f.write(input_file.read())
|
| 145 |
+
logger.info(f"Wrote {written/1e6:.2f}MB")
|
| 146 |
|
| 147 |
+
if not os.path.exists(input_path) or os.path.getsize(input_path) == 0:
|
| 148 |
+
raise FileNotFoundError(f"Input video not saved properly: {input_path}")
|
| 149 |
|
| 150 |
+
logger.info(f"Video file verified: {os.path.getsize(input_path)} bytes")
|
| 151 |
|
| 152 |
# Prepare background
|
| 153 |
bg_path = None
|
| 154 |
if bg_type == "image" and background is not None:
|
| 155 |
+
logger.info("Processing background IMAGE")
|
| 156 |
bg_cv = cv2.cvtColor(np.array(background), cv2.COLOR_RGB2BGR)
|
| 157 |
bg_path = str(temp_dir / "background.jpg")
|
| 158 |
cv2.imwrite(bg_path, bg_cv)
|
| 159 |
+
logger.info(f"Background image written: {bg_path}")
|
| 160 |
|
| 161 |
+
elif bg_type == "color":
|
| 162 |
+
logger.info(f"Processing background COLOR: {st.session_state.bg_color}")
|
| 163 |
color_hex = st.session_state.bg_color.lstrip('#')
|
| 164 |
color_rgb = tuple(int(color_hex[i:i+2], 16) for i in (0, 2, 4))
|
| 165 |
bg_path = str(temp_dir / "background.jpg")
|
| 166 |
cv2.imwrite(bg_path, np.ones((100, 100, 3), dtype=np.uint8) * color_rgb[::-1])
|
| 167 |
+
logger.info(f"Background color image written: {bg_path}")
|
| 168 |
|
| 169 |
+
# Progress tracking
|
| 170 |
progress_placeholder = st.empty()
|
| 171 |
status_placeholder = st.empty()
|
| 172 |
|
| 173 |
def progress_callback(progress, message):
|
| 174 |
progress = max(0, min(1, float(progress)))
|
| 175 |
+
logger.info(f"Progress: {progress*100:.1f}% - {message}")
|
| 176 |
progress_placeholder.progress(progress)
|
| 177 |
status_placeholder.text(f"Status: {message}")
|
| 178 |
|
| 179 |
+
# GPU check
|
| 180 |
if torch.cuda.is_available():
|
| 181 |
+
device = torch.cuda.get_device_name(0)
|
| 182 |
+
mem_before = torch.cuda.memory_allocated()/1e9
|
| 183 |
+
logger.info(f"CUDA Device: {device}")
|
| 184 |
+
logger.info(f"GPU Memory Before: {mem_before:.2f}GB")
|
| 185 |
else:
|
| 186 |
+
logger.warning("CUDA NOT AVAILABLE - Processing on CPU")
|
| 187 |
|
| 188 |
# Process the video
|
| 189 |
output_path = str(temp_dir / "output.mp4")
|
| 190 |
click_points = [[0.5, 0.5]]
|
| 191 |
|
| 192 |
+
logger.info("Importing TwoStageProcessor...")
|
| 193 |
from pipeline.integrated_pipeline import TwoStageProcessor
|
| 194 |
|
|
|
|
| 195 |
@st.cache_resource
|
| 196 |
def load_processor(temp_dir_str):
|
| 197 |
+
logger.info(f"Loading processor with temp_dir: {temp_dir_str}")
|
| 198 |
return TwoStageProcessor(temp_dir=temp_dir_str)
|
| 199 |
|
| 200 |
processor = load_processor(str(temp_dir))
|
| 201 |
+
logger.info("Processor loaded")
|
| 202 |
|
| 203 |
try:
|
| 204 |
+
logger.info("Calling process_video...")
|
| 205 |
+
logger.info(f" Input: {input_path}")
|
| 206 |
+
logger.info(f" Background: {bg_path}")
|
| 207 |
+
logger.info(f" Output: {output_path}")
|
|
|
|
| 208 |
|
| 209 |
success = processor.process_video(
|
| 210 |
input_video=input_path,
|
|
|
|
| 215 |
progress_callback=progress_callback
|
| 216 |
)
|
| 217 |
|
| 218 |
+
logger.info(f"Processing returned: {success}")
|
| 219 |
|
| 220 |
except Exception as e:
|
| 221 |
+
logger.error(f"Pipeline processing failed: {traceback.format_exc()}")
|
| 222 |
raise
|
| 223 |
|
| 224 |
if torch.cuda.is_available():
|
| 225 |
+
mem_after = torch.cuda.memory_allocated()/1e9
|
| 226 |
+
logger.info(f"GPU Memory After: {mem_after:.2f}GB")
|
| 227 |
torch.cuda.empty_cache()
|
|
|
|
| 228 |
|
| 229 |
if not success:
|
| 230 |
+
raise RuntimeError("Video processing returned False")
|
| 231 |
|
| 232 |
+
# Verify output
|
| 233 |
if not os.path.exists(output_path):
|
| 234 |
+
logger.error(f"Output file does not exist: {output_path}")
|
| 235 |
raise FileNotFoundError(f"Output video not created: {output_path}")
|
| 236 |
|
| 237 |
output_size = os.path.getsize(output_path)
|
| 238 |
+
logger.info(f"Output file exists: {output_size} bytes ({output_size/1e6:.2f}MB)")
|
| 239 |
|
| 240 |
+
# Read output into memory
|
| 241 |
+
logger.info("Reading output video into memory...")
|
| 242 |
with open(output_path, 'rb') as f:
|
| 243 |
video_bytes = f.read()
|
| 244 |
|
| 245 |
+
logger.info(f"Read {len(video_bytes)/1e6:.2f}MB into memory")
|
| 246 |
|
| 247 |
+
# Cleanup
|
| 248 |
try:
|
|
|
|
| 249 |
shutil.rmtree(temp_dir)
|
| 250 |
+
logger.info("Temp directory cleaned")
|
| 251 |
except Exception as e:
|
| 252 |
+
logger.warning(f"Could not clean temp directory: {e}")
|
| 253 |
|
| 254 |
logger.info("=" * 60)
|
| 255 |
+
logger.info("VIDEO PROCESSING COMPLETED")
|
| 256 |
logger.info("=" * 60)
|
| 257 |
|
| 258 |
return video_bytes
|
| 259 |
|
| 260 |
except Exception as e:
|
| 261 |
logger.error("=" * 60)
|
| 262 |
+
logger.error(f"ERROR IN VIDEO PROCESSING: {str(e)}")
|
| 263 |
logger.error(traceback.format_exc())
|
| 264 |
logger.error("=" * 60)
|
| 265 |
st.error(f"An error occurred during processing: {str(e)}")
|
|
|
|
| 267 |
|
| 268 |
# --- Main Application ---
|
| 269 |
def main():
|
| 270 |
+
st.title("Advanced Video Background Replacer")
|
| 271 |
st.markdown("---")
|
| 272 |
|
| 273 |
# Initialize session state
|
| 274 |
initialize_session_state()
|
| 275 |
|
| 276 |
+
# GPU Status in sidebar
|
| 277 |
+
with st.sidebar:
|
| 278 |
+
st.subheader("System Status")
|
| 279 |
+
if st.session_state.gpu_available:
|
| 280 |
+
st.success(f"GPU: {torch.cuda.get_device_name(0)}")
|
| 281 |
+
else:
|
| 282 |
+
st.error("GPU: Not Available (using CPU)")
|
| 283 |
+
|
| 284 |
+
logger.info(f"Rerun - Processing: {st.session_state.processing}, Complete: {st.session_state.process_complete}")
|
| 285 |
|
| 286 |
# Main layout
|
| 287 |
col1, col2 = st.columns([1, 1], gap="large")
|
|
|
|
| 290 |
st.header("1. Upload Video")
|
| 291 |
|
| 292 |
uploaded = st.file_uploader(
|
| 293 |
+
"Upload Video",
|
| 294 |
type=["mp4", "mov", "avi"],
|
| 295 |
key="video_uploader"
|
| 296 |
)
|
| 297 |
|
| 298 |
+
# Store uploaded video
|
| 299 |
+
if uploaded is not None:
|
| 300 |
+
if st.session_state.uploaded_video is None or uploaded.name != getattr(st.session_state.uploaded_video, 'name', ''):
|
| 301 |
+
logger.info(f"New video: {uploaded.name} ({uploaded.size} bytes)")
|
| 302 |
+
st.session_state.uploaded_video = uploaded
|
| 303 |
+
st.session_state.video_bytes_cache = None
|
| 304 |
+
st.session_state.processed_video_bytes = None
|
| 305 |
+
st.session_state.process_complete = False
|
|
|
|
| 306 |
|
| 307 |
+
# Video preview
|
| 308 |
st.markdown("### Video Preview")
|
| 309 |
+
if st.session_state.uploaded_video is not None:
|
| 310 |
+
if st.session_state.video_bytes_cache is None:
|
| 311 |
+
logger.info("Caching video bytes...")
|
| 312 |
+
st.session_state.uploaded_video.seek(0)
|
| 313 |
+
st.session_state.video_bytes_cache = st.session_state.uploaded_video.read()
|
| 314 |
+
logger.info(f"Cached {len(st.session_state.video_bytes_cache)/1e6:.2f}MB")
|
| 315 |
+
|
| 316 |
+
st.video(st.session_state.video_bytes_cache)
|
| 317 |
+
else:
|
| 318 |
+
st.info("No video uploaded yet")
|
|
|
|
|
|
|
|
|
|
| 319 |
|
| 320 |
with col2:
|
| 321 |
st.header("2. Background Settings")
|
|
|
|
| 324 |
"Select Background Type:",
|
| 325 |
["Image", "Color", "Blur"],
|
| 326 |
horizontal=True,
|
|
|
|
| 327 |
key="bg_type_radio"
|
| 328 |
)
|
| 329 |
|
| 330 |
if bg_type == "Image":
|
| 331 |
bg_image = st.file_uploader(
|
| 332 |
+
"Upload Background Image",
|
| 333 |
type=["jpg", "png", "jpeg"],
|
| 334 |
key="bg_image_uploader"
|
| 335 |
)
|
| 336 |
|
| 337 |
+
if bg_image is not None:
|
| 338 |
+
if st.session_state.bg_image_cache is None or bg_image.name != getattr(st.session_state.bg_image_cache, 'name', ''):
|
| 339 |
+
logger.info(f"New background: {bg_image.name}")
|
|
|
|
|
|
|
|
|
|
| 340 |
st.session_state.bg_image_cache = Image.open(bg_image)
|
| 341 |
+
st.session_state.bg_image_cache.name = bg_image.name
|
| 342 |
+
|
| 343 |
+
st.image(st.session_state.bg_image_cache, caption="Selected Background", use_container_width=True)
|
| 344 |
+
else:
|
| 345 |
+
st.info("No background image uploaded yet")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 346 |
|
| 347 |
elif bg_type == "Color":
|
| 348 |
selected_color = st.color_picker(
|
| 349 |
+
"Choose Background Color",
|
| 350 |
st.session_state.bg_color,
|
| 351 |
key="color_picker"
|
| 352 |
)
|
| 353 |
|
| 354 |
+
if selected_color != st.session_state.bg_color:
|
| 355 |
+
logger.info(f"Color changed to: {selected_color}")
|
|
|
|
| 356 |
st.session_state.bg_color = selected_color
|
|
|
|
| 357 |
|
| 358 |
color_rgb = tuple(int(selected_color.lstrip('#')[i:i+2], 16) for i in (0, 2, 4))
|
| 359 |
color_display = np.zeros((100, 100, 3), dtype=np.uint8)
|
| 360 |
color_display[:, :] = color_rgb[::-1]
|
| 361 |
st.session_state.color_display_cache = color_display
|
| 362 |
|
| 363 |
+
if st.session_state.color_display_cache is not None:
|
| 364 |
+
st.image(st.session_state.color_display_cache, caption="Selected Color", width=200)
|
|
|
|
|
|
|
|
|
|
| 365 |
|
| 366 |
st.header("3. Process & Download")
|
| 367 |
|
| 368 |
+
# Simple button instead of form
|
| 369 |
+
if st.button(
|
| 370 |
+
"Process Video",
|
| 371 |
+
disabled=st.session_state.uploaded_video is None or st.session_state.processing,
|
| 372 |
+
use_container_width=True
|
| 373 |
+
):
|
| 374 |
+
logger.info("PROCESS BUTTON CLICKED")
|
| 375 |
+
st.session_state.processing = True
|
| 376 |
+
st.session_state.process_complete = False
|
| 377 |
+
st.session_state.processed_video_bytes = None
|
| 378 |
|
| 379 |
+
with st.spinner("Processing video..."):
|
| 380 |
+
try:
|
| 381 |
+
background = None
|
| 382 |
+
if bg_type == "Image" and st.session_state.bg_image_cache is not None:
|
| 383 |
+
background = st.session_state.bg_image_cache
|
| 384 |
+
logger.info("Using background IMAGE")
|
| 385 |
+
elif bg_type == "Color":
|
| 386 |
+
background = st.session_state.bg_color
|
| 387 |
+
logger.info(f"Using background COLOR: {background}")
|
| 388 |
+
|
| 389 |
+
video_bytes = process_video(
|
| 390 |
+
st.session_state.uploaded_video,
|
| 391 |
+
background,
|
| 392 |
+
bg_type=bg_type.lower()
|
| 393 |
+
)
|
| 394 |
+
|
| 395 |
+
if video_bytes and len(video_bytes) > 0:
|
| 396 |
+
st.session_state.processed_video_bytes = video_bytes
|
| 397 |
+
st.session_state.process_complete = True
|
| 398 |
+
logger.info(f"Processing complete! {len(video_bytes)/1e6:.2f}MB")
|
| 399 |
+
st.success("Video processing complete!")
|
| 400 |
+
else:
|
| 401 |
+
logger.error("Processing returned empty or None")
|
| 402 |
+
st.error("Failed to process video")
|
| 403 |
|
| 404 |
+
except Exception as e:
|
| 405 |
+
logger.error(f"Exception: {str(e)}")
|
| 406 |
+
logger.error(traceback.format_exc())
|
| 407 |
+
st.error(f"An error occurred: {str(e)}")
|
| 408 |
+
finally:
|
| 409 |
+
st.session_state.processing = False
|
| 410 |
+
logger.info(f"Processing finished. Success: {st.session_state.process_complete}")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 411 |
|
| 412 |
+
# Show processed video
|
| 413 |
if st.session_state.processed_video_bytes is not None and len(st.session_state.processed_video_bytes) > 0:
|
| 414 |
st.markdown("---")
|
| 415 |
+
st.markdown("### Processed Video")
|
| 416 |
|
| 417 |
try:
|
| 418 |
+
logger.info(f"Displaying video: {len(st.session_state.processed_video_bytes)/1e6:.2f}MB")
|
| 419 |
st.video(st.session_state.processed_video_bytes)
|
| 420 |
|
| 421 |
st.download_button(
|
| 422 |
+
label="Download Processed Video",
|
| 423 |
data=st.session_state.processed_video_bytes,
|
| 424 |
file_name="processed_video.mp4",
|
| 425 |
mime="video/mp4",
|
| 426 |
+
use_container_width=True
|
|
|
|
| 427 |
)
|
|
|
|
| 428 |
|
| 429 |
except Exception as e:
|
| 430 |
+
logger.error(f"Error displaying video: {str(e)}")
|
|
|
|
| 431 |
st.error(f"Error displaying video: {str(e)}")
|
| 432 |
|
| 433 |
if __name__ == "__main__":
|