Create app.py

app.py

@@ -0,0 +1,133 @@
+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()