app.py

import os
import sys
import subprocess
import base64
import datetime
from io import BytesIO

import streamlit as st
from PIL import Image

# Set Streamlit page configuration (centered content via CSS)
st.set_page_config(
    page_title="Metamorph: DiffMorpher + LCM-LoRA + FILM",
    layout="wide",
    page_icon="🌀"
)

def save_uploaded_file(uploaded_file, dst_path):
    """Save an uploaded file to a destination path."""
    with open(dst_path, "wb") as f:
        f.write(uploaded_file.getbuffer())

def get_img_as_base64(img):
    """Convert PIL Image to base64 for embedding in HTML."""
    buffered = BytesIO()
    img.save(buffered, format="PNG")
    return base64.b64encode(buffered.getvalue()).decode("utf-8")

def ensure_scripts_exist():
    """Check if the required script files exist."""
    required_scripts = ["run_morphing.py", "FILM.py"]
    missing_scripts = [script for script in required_scripts if not os.path.exists(script)]
    
    if missing_scripts:
        error_msg = f"Missing required script(s): {', '.join(missing_scripts)}"
        return False, error_msg
    return True, ""

def create_temp_folder():
    """Create a persistent temporary folder in the repo for processing."""
    base_folder = os.path.join(os.getcwd(), "temp_run")
    os.makedirs(base_folder, exist_ok=True)
    # Create a subfolder with a timestamp to avoid collisions
    run_folder = os.path.join(base_folder, datetime.datetime.now().strftime("run_%Y%m%d_%H%M%S"))
    os.makedirs(run_folder)
    return run_folder

def main():
    # Initialize session state variables
    if 'page' not in st.session_state:
        st.session_state.page = 'input'  # States: 'input', 'processing', 'result'
    
    if 'temp_dir' not in st.session_state:
        st.session_state.temp_dir = None
    
    if 'final_video_path' not in st.session_state:
        st.session_state.final_video_path = None
    
    if 'process_started' not in st.session_state:
        st.session_state.process_started = False
        
    # Function to switch to processing page and start morphing
    def start_processing():
        st.session_state.page = 'processing'
        st.session_state.process_started = False  # Will be set to True when processing starts
        
    # Function to return to input page
    def return_to_input():
        st.session_state.page = 'input'
        st.session_state.temp_dir = None
        st.session_state.final_video_path = None
        st.session_state.process_started = False

    # ---------------- CUSTOM CSS FOR A PROFESSIONAL, DARK THEME ----------------
    st.markdown(
        """
        <style>
        /* Import Google Font */
        @import url('https://fonts.googleapis.com/css2?family=Roboto:wght@400;700&display=swap');

        /* Global styling */
        body {
            font-family: 'Roboto', sans-serif;
            color: #f1f1f1;
        }
        h1, h2, h3, h4 {
            color: #ffffff;
        }
        p, span, label {
            color: #f1f1f1;
        }
        body, p {
            line-height: 1.6;
            letter-spacing: 0.3px;
        }
        /* Header: Centered large logo and title */
        .header-logo-large {
            display: block;
            margin-left: auto;
            margin-right: auto;
            width: 200px;
        }
        /* Left-aligned logo for results page */
        .header-logo-left {
            display: block;
            margin-right: auto;
            width: 200px;
        }
        .header-title {
            text-align: center;
            font-size: 2.8rem;
            font-weight: bold;
            color: #ffffff;
            margin-top: 0.5rem;
        }
        /* Dark animated background */
        .stApp {
            background: linear-gradient(315deg, #000428, #004e92);
            animation: gradient 30s ease infinite;
            background-size: 400% 400%;
            background-attachment: fixed;
        }
        @keyframes gradient {
            0% { background-position: 0% 0%; }
            50% { background-position: 100% 100%; }
            100% { background-position: 0% 0%; }
        }
        /* Main container styling */
        .main .block-container {
            max-width: 900px;
            margin: 0 auto;
            padding: 2rem 1rem;
            background-color: transparent;
            color: #f1f1f1;
        }
        /* Run button styling */
        div.stButton > button {
            background-image: linear-gradient(45deg, #8e44ad, #732d91);
            box-shadow: 0 0 10px rgba(142,68,173,0.6), 0 0 20px rgba(114,45,145,0.4);
            border: none;
            color: #ffffff;
            padding: 0.6rem 1.2rem;
            border-radius: 5px;
            cursor: pointer;
            font-family: 'Roboto', sans-serif;
            transition: transform 0.2s ease, box-shadow 0.2s ease;
        }
        div.stButton > button:hover {
            transform: scale(1.02);
            box-shadow: 0 0 20px rgba(142,68,173,0.8), 0 0 30px rgba(114,45,145,0.6);
        }
        /* Processing animation */
        .processing-container {
            text-align: center;
            padding: 3rem 0;
        }
        .processing-text {
            font-size: 1.8rem;
            margin-bottom: 2rem;
            animation: pulse 2s infinite;
        }
        @keyframes pulse {
            0% { opacity: 0.6; }
            50% { opacity: 1; }
            100% { opacity: 0.6; }
        }
        /* Left-aligned results content */
        .results-container h2 {
            text-align: left;
        }
        .results-container p {
            text-align: left;
        }
        /* Disabled checkbox and label styling */
        .disabled-checkbox {
            opacity: 0.5;
            cursor: not-allowed;
        }
        </style>
        """,
        unsafe_allow_html=True
    )

    # Check if required scripts exist
    scripts_exist, error_msg = ensure_scripts_exist()
    if not scripts_exist:
        st.error(error_msg)
        st.error("Please make sure all required scripts are in the same directory as this Streamlit app.")
        return

    # Load logo path for all pages
    logo_path = "metamorphLogo_nobg.png"
    logo_exists = os.path.exists(logo_path)
    logo_base64 = None
    
    if logo_exists:
        try:
            logo = Image.open(logo_path)
            logo_base64 = get_img_as_base64(logo)
        except Exception as e:
            st.warning(f"Logo could not be loaded: {e}")

    # =============== INPUT PAGE ===============
    if st.session_state.page == 'input':
        # Display centered logo and title for input page
        if logo_exists and logo_base64:
            st.markdown(
                f"""
                <div style="text-align: center;">
                    <img src="data:image/png;base64,{logo_base64}" class="header-logo-large" alt="Metamorph Logo">
                </div>
                """,
                unsafe_allow_html=True
            )
        
        st.markdown("<h1 class='header-title'>Metamorph Web App</h1>", unsafe_allow_html=True)
        
        st.markdown(
            """
            <p style='text-align: center; font-size: 1.1rem;'>
                DiffMorpher is used for keyframe generation by default, with FILM for interpolation.
                Optionally, you can enable LCM-LoRA for accelerated inference (with slight decrease in quality).
                Upload two images, optionally provide descriptions, and fine-tune the settings to create a smooth, high-quality morphing video.
            </p>
            <p style='text-align: center; font-size: 1rem; margin-top: 0.5rem;'>
                For further information on how to configure the parameters, please refer to the <a href="https://nalin0503.github.io/FYP_ImageMorpher/" target="_blank" style="color: #8e44ad; text-decoration: underline;">User Documentation</a>.
            </p>
            <hr>
            """,
            unsafe_allow_html=True
        )

        # ---------------- SECTION 1: IMAGE & PROMPT INPUTS ----------------
        st.subheader("1. Upload Source Images & Prompts")
        st.markdown("**Note:** Your uploaded images must be of similar topology and same size to achieve the best results.")
        col_imgA, col_imgB = st.columns(2)
        with col_imgA:
            st.markdown("#### Image A")
            uploaded_image_A = st.file_uploader("Upload your first image", type=["png", "jpg", "jpeg"], key="imgA")
            if uploaded_image_A is not None:
                st.image(uploaded_image_A, caption="Preview - Image A", use_container_width=True)
            prompt_A = st.text_input("Short Description for Image A (optional)", value="", key="promptA", 
                                  help="For added interpolation between the two descriptions")
        with col_imgB:
            st.markdown("#### Image B")
            uploaded_image_B = st.file_uploader("Upload your second image", type=["png", "jpg", "jpeg"], key="imgB")
            if uploaded_image_B is not None:
                st.image(uploaded_image_B, caption="Preview - Image B", use_container_width=True)
            prompt_B = st.text_input("Short Description for Image B (optional)", value="", key="promptB",
                                  help="For added interpolation between the two descriptions")

        st.markdown("<hr>", unsafe_allow_html=True)

        # ---------------- SECTION 2: CONFIGURE MORPHING PIPELINE ----------------
        st.subheader("2. Configure Morphing Pipeline")
        st.markdown(
            """
            <p style="font-size: 1rem;">
                Select a preset below to automatically adjust quality and inference time. 
                If you choose <strong>Custom ⚙️</strong>, the advanced settings will automatically expand so you can fine-tune the configuration.
            </p>
            """,
            unsafe_allow_html=True
        )

        # Preset Options (Dropdown)
        st.markdown("**Preset Options**")
        preset_option = st.selectbox(
            "Select a preset for quality and inference time",
            options=[
                "Maximum quality, longest inference time 🏆",
                "Medium quality, medium inference time ⚖️",
                "Low quality, shortest inference time ⚡",
                "Creative morph 🎨",
                "Custom ⚙️"
            ],
            index=0,
            label_visibility="collapsed"
        )

        # Determine preset defaults based on selection
        if preset_option.startswith("Maximum quality"):
            preset_model = "Base Stable Diffusion V2-1"
            preset_film = False  # Changed to False as FILM is disabled
            preset_lcm = False
            preset_frames = 48  # Increased for maximum quality
            preset_fps = 16     # Increased for maximum quality
        elif preset_option.startswith("Medium quality"):
            preset_model = "Base Stable Diffusion V2-1"
            preset_film = False
            preset_lcm = False
            preset_frames = 24  # Default frame count
            preset_fps = 10     # Default FPS
        elif preset_option.startswith("Low quality"):
            preset_model = "Base Stable Diffusion V2-1"
            preset_film = False
            preset_lcm = True
            preset_frames = 24  # Default frame count
            preset_fps = 10     # Default FPS
        elif preset_option.startswith("Creative morph"):
            preset_model = "Dreamshaper-7 (fine-tuned SD V1-5)"
            preset_film = False  # Changed to False as FILM is disabled
            preset_lcm = True
            preset_frames = 24  # Default frame count
            preset_fps = 10     # Default FPS
        else:
            # "Custom"
            preset_model = None
            preset_film = None
            preset_lcm = None
            preset_frames = None
            preset_fps = None

        advanced_expanded = True if preset_option.endswith("⚙️") else False

        # Advanced Options for fine-tuning
        with st.expander("Advanced Options", expanded=advanced_expanded):
            options_list = [
                "Base Stable Diffusion V1-5",
                "Dreamshaper-7 (fine-tuned SD V1-5)",
                "Base Stable Diffusion V2-1"
            ]
            default_model = preset_model if preset_model is not None else "Base Stable Diffusion V1-5"
            default_index = options_list.index(default_model)
            model_option = st.selectbox("Select Model Card", options=options_list, index=default_index)
            
            col_left, col_right = st.columns(2)
            # Left Column: Keyframe Generator Parameters
            with col_left:
                st.markdown("##### Keyframe Generator Parameters")
                # Set default based on preset
                default_frames = preset_frames if preset_frames is not None else 24
                num_frames = st.number_input("Number of keyframes (2–50)", min_value=2, max_value=50, value=default_frames)
                lcm_default = preset_lcm if preset_lcm is not None else False
                enable_lcm_lora = st.checkbox(
                    "Enable LCM-LoRA",
                    value=lcm_default,
                    help="Accelerates inference with slight quality decrease"
                )
                use_adain = st.checkbox("Use AdaIN", value=True, help="Adaptive Instance Normalization for improved generation")
                use_reschedule = st.checkbox("Use reschedule sampling", value=True, help="Better sampling strategy")
            
            # Right Column: Inter-frame Interpolator Parameters (FILM)
            with col_right:
                st.markdown("<div class='right-column-divider'>", unsafe_allow_html=True)
                st.markdown("##### Inter-frame Interpolator Parameters")
                
                # Disabled FILM checkbox with warning message
                st.markdown(
                    """
                    <div class="disabled-checkbox">
                        <input type="checkbox" disabled>
                        <span>Use FILM interpolation</span>
                    </div>
                    """,
                    unsafe_allow_html=True
                )
                
                # Always set use_film to False since it's disabled
                use_film = False
                # Disabled FILM recursion parameter with warning message
                st.markdown(
                    """
                    <div class="disabled-checkbox">
                        <span>FILM recursion passes (1–6)</span>
                    </div>
                    """,
                    unsafe_allow_html=True
                )
                st.info("Unfortunately, FILM is not available for use on the HF Demo, please select other choices.")
                film_recursions = 3  # placeholder value, but it won't be used since FILM is disabled
                                    
                # Set default FPS based on preset
                default_fps = preset_fps if preset_fps is not None else 10
                output_fps = st.number_input("Output FPS (1–60)", min_value=1, max_value=60, value=default_fps, 
                                        help="Output video frames per second")
                st.markdown("</div>", unsafe_allow_html=True)

        st.markdown("<hr>", unsafe_allow_html=True)

        # ---------------- SECTION 3: EXECUTE MORPH PIPELINE ----------------
        st.subheader("3. Generate Morphing Video")
        st.markdown("Once satisfied with your inputs, click below to start the process.")

        # Create a container for the run button
        run_container = st.container()
        
        with run_container:
            # Save values to session state so we can access them in the processing page
            if st.button("Run Morphing Pipeline", key="run_pipeline"):
                if not (uploaded_image_A and uploaded_image_B):
                    st.error("Please upload both images before running the morphing pipeline.")
                else:
                    # Save all settings to session state
                    st.session_state.uploaded_image_A = uploaded_image_A
                    st.session_state.uploaded_image_B = uploaded_image_B
                    st.session_state.prompt_A = prompt_A
                    st.session_state.prompt_B = prompt_B
                    st.session_state.model_option = model_option
                    st.session_state.num_frames = num_frames
                    st.session_state.enable_lcm_lora = enable_lcm_lora
                    st.session_state.use_adain = use_adain
                    st.session_state.use_reschedule = use_reschedule
                    st.session_state.use_film = use_film  # Always False now
                    st.session_state.film_recursions = film_recursions
                    st.session_state.output_fps = output_fps
                    
                    # Switch to processing page
                    start_processing()
                    st.rerun()

    # =============== PROCESSING PAGE ===============
    elif st.session_state.page == 'processing':
        # Display centered logo for processing page
        if logo_exists and logo_base64:
            st.markdown(
                f"""
                <div style="text-align: center;">
                    <img src="data:image/png;base64,{logo_base64}" class="header-logo-large" alt="Metamorph Logo">
                </div>
                """,
                unsafe_allow_html=True
            )
            
        st.markdown("<h1 class='header-title'>Metamorph Web App</h1>", unsafe_allow_html=True)
        
        st.markdown(
            """
            <div class="processing-container">
                <h2 class="processing-text">Processing Your Morphing Request</h2>
                <p>Please wait while we generate your morphing video...</p>
            </div>
            """, 
            unsafe_allow_html=True
        )
        
        # Use a progress bar for visual feedback
        progress_bar = st.progress(0)
        
        # Only start processing if not already started
        if not st.session_state.process_started:
            st.session_state.process_started = True
            
            # Create a temporary folder for processing
            temp_dir = create_temp_folder()
            st.session_state.temp_dir = temp_dir
            
            try:
                # Update progress
                progress_bar.progress(10)
                
                # Extract variables from session state
                uploaded_image_A = st.session_state.uploaded_image_A
                uploaded_image_B = st.session_state.uploaded_image_B
                prompt_A = st.session_state.prompt_A
                prompt_B = st.session_state.prompt_B
                model_option = st.session_state.model_option
                num_frames = st.session_state.num_frames
                enable_lcm_lora = st.session_state.enable_lcm_lora
                use_adain = st.session_state.use_adain
                use_reschedule = st.session_state.use_reschedule
                use_film = st.session_state.use_film  # Always False now
                film_recursions = st.session_state.film_recursions
                output_fps = st.session_state.output_fps
                
                # Save uploaded images
                imgA_path = os.path.join(temp_dir, "imageA.png")
                imgB_path = os.path.join(temp_dir, "imageB.png")
                save_uploaded_file(uploaded_image_A, imgA_path)
                save_uploaded_file(uploaded_image_B, imgB_path)
                
                # Update progress
                progress_bar.progress(20)
                
                # Create output directories
                timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
                output_dir = os.path.join(temp_dir, f"morph_results_{timestamp}")
                film_output_dir = os.path.join(temp_dir, f"film_output_{timestamp}")
                os.makedirs(output_dir, exist_ok=True)
                os.makedirs(film_output_dir, exist_ok=True)
                
                actual_model_path = (
                    "lykon/dreamshaper-7" if model_option == "Dreamshaper-7 (fine-tuned SD V1-5)" 
                    else "stabilityai/stable-diffusion-2-1-base" if model_option == "Base Stable Diffusion V2-1"
                    else "sd-legacy/stable-diffusion-v1-5"
                )
                
                # Update progress
                progress_bar.progress(30)
                
                # Build the command for run_morphing.py
                cmd = [
                    sys.executable, "run_morphing.py",
                    "--model_path", actual_model_path,
                    "--image_path_0", imgA_path,
                    "--image_path_1", imgB_path,
                    "--prompt_0", prompt_A,
                    "--prompt_1", prompt_B,
                    "--output_path", output_dir,
                    "--film_output_folder", film_output_dir,
                    "--num_frames", str(num_frames),
                    "--fps", str(output_fps)
                ]
                
                if enable_lcm_lora:
                    cmd.append("--use_lcm")
                if use_adain:
                    cmd.append("--use_adain")
                if use_reschedule:
                    cmd.append("--use_reschedule")
                if use_film:  # disabled, no cudnn on hf
                    cmd.append("--use_film")
                
                # Add film recursion parameter
                cmd.extend(["--film_num_recursions", str(film_recursions)])
                
                # Run the morphing process
                try:
                    # Update progress - processing takes the longest
                    progress_bar.progress(40)
                    
                    subprocess.run(cmd, check=True)
                    
                    # Update progress
                    progress_bar.progress(90)
                    
                    # Check for output video
                    video_found = False
                    possible_outputs = [f for f in os.listdir(film_output_dir) if f.endswith(".mp4")]
                    if possible_outputs:
                        final_video_path = os.path.join(film_output_dir, possible_outputs[0])
                        video_found = True
                    
                    if not video_found:
                        possible_outputs = [f for f in os.listdir(output_dir) if f.endswith(".mp4")]
                        if possible_outputs:
                            final_video_path = os.path.join(output_dir, possible_outputs[0])
                            video_found = True
                    
                    if video_found:
                        st.session_state.final_video_path = final_video_path
                        st.session_state.page = 'result'
                        progress_bar.progress(100)
                        st.rerun()
                    else:
                        st.error("No output video was generated. Check logs for details.")
                        
                except subprocess.CalledProcessError as e:
                    st.error(f"Error running morphing pipeline: {e}")
                
            except Exception as e:
                st.error(f"An error occurred during processing: {e}")

    # =============== RESULT PAGE ===============
    elif st.session_state.page == 'result':
        # Display left-aligned logo for results page (no title)
        if logo_exists and logo_base64:
            st.markdown(
                f"""
                <div>
                    <img src="data:image/png;base64,{logo_base64}" class="header-logo-left" alt="Metamorph Logo">
                </div>
                """,
                unsafe_allow_html=True
            )
        
        # Left-aligned content for results page
        st.markdown(
            """
            <div class="results-container">
                <h2>Morphing Complete! 🎉</h2>
                <p>Your morphing video has been successfully generated. You can download it below.</p>
            </div>
            """,
            unsafe_allow_html=True
        )
        
        # Show the result video and download button
        try:
            if st.session_state.final_video_path:
                # Display video preview
                video_file = open(st.session_state.final_video_path, 'rb')
                video_bytes = video_file.read()
                video_file.close()
                
                # st.video(video_bytes)
                
                # Download button
                st.download_button(
                    "Download Morphing Video",
                    data=video_bytes,
                    file_name="metamorph_result.mp4",
                    mime="video/mp4"
                )
        except Exception as e:
            st.error(f"Error preparing video for download: {e}")
        
        # Button to start a new project
        if st.button("Start New Morphing Project"):
            return_to_input()
            st.rerun()

if __name__ == "__main__":
    main()