import streamlit as st
import torch
from transformers import pipeline
from PIL import Image
import numpy as np
import tempfile
import os
from diffusers import VideoToVideoSDPipeline
from diffusers.utils import export_to_video

def generate_video_from_image(image, duration_seconds=10, progress_bar=None):
    """
    Generate a video from an image using VideoToVideoSDPipeline.
    """
    try:
        if progress_bar:
            progress_bar.progress(0.1, "Generating image caption...")
            
        # Setup image captioning pipeline
        captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
        
        # Generate caption
        caption = captioner(image)[0]['generated_text']
        st.write(f"Generated caption: *{caption}*")
        
        if progress_bar:
            progress_bar.progress(0.3, "Loading Video Generation model...")
            
        # Initialize Video Generation pipeline
        pipeline = VideoToVideoSDPipeline.from_pretrained(
            "cerspense/zeroscope_v2_576w",
            torch_dtype=torch.float16
        ).to("cuda" if torch.cuda.is_available() else "cpu")
        
        if progress_bar:
            progress_bar.progress(0.4, "Processing image...")
            
        # Prepare image
        if image.mode != "RGB":
            image = image.convert("RGB")
        image = image.resize((576, 320))  # Resize to model's expected size
        
        if progress_bar:
            progress_bar.progress(0.5, "Generating video frames...")
            
        # Generate video
        num_frames = duration_seconds * 8  # 8 FPS for this model
        video_frames = pipeline(
            image,
            num_inference_steps=50,
            num_frames=num_frames,
            guidance_scale=7.5,
            prompt=caption,
        ).videos[0]
        
        if progress_bar:
            progress_bar.progress(0.8, "Creating final video...")
            
        # Create temporary file for video
        with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as tmp_file:
            output_path = tmp_file.name
            
        # Export video frames
        export_to_video(video_frames, output_path, fps=8)
        
        if progress_bar:
            progress_bar.progress(1.0, "Video generation complete!")
            
        return output_path, caption
        
    except Exception as e:
        st.error(f"Error generating video: {str(e)}")
        raise

def main():
    st.set_page_config(page_title="AI Video Generator", page_icon="🎥")
    
    st.title("🎥 AI Video Generator")
    st.write("""
    Upload an image to generate a video with AI-powered motion and transitions.
    The app will automatically generate a caption for your image and use it as inspiration for the video.
    """)
    
    # Add warning about computational requirements
    st.warning("Note: Video generation may take several minutes depending on the duration and available computing resources.")
    
    # File uploader
    uploaded_file = st.file_uploader("Choose an image", type=['png', 'jpg', 'jpeg'])
    
    # Duration selector (adjusted for this model's capabilities)
    duration = st.slider("Video duration (seconds)", min_value=1, max_value=15, value=5)
    
    if uploaded_file is not None:
        # Display uploaded image
        image = Image.open(uploaded_file)
        st.image(image, caption="Uploaded Image", use_column_width=True)
        
        # Generate button
        if st.button("Generate Video"):
            try:
                # Create a progress bar
                progress_text = "Operation in progress. Please wait..."
                my_bar = st.progress(0, text=progress_text)
                
                # Generate video
                video_path, caption = generate_video_from_image(image, duration, my_bar)
                
                if video_path and os.path.exists(video_path):
                    # Read the video file
                    with open(video_path, 'rb') as video_file:
                        video_bytes = video_file.read()
                    
                    # Create download button
                    st.download_button(
                        label="Download Video",
                        data=video_bytes,
                        file_name="generated_video.mp4",
                        mime="video/mp4"
                    )
                    
                    # Display video
                    st.video(video_bytes)
                    
                    # Clean up temporary file
                    os.unlink(video_path)
                else:
                    st.error("Failed to generate video. Please try again.")
            
            except Exception as e:
                st.error(f"An error occurred: {str(e)}")

if __name__ == "__main__":
    main()