Integrate SVD into professional production pipelines for scalable video content creation.

Production Pipeline

Batch Processing

import os
from pathlib import Path

def batch_generate_videos(input_dir, output_dir, pipe):
    Path(output_dir).mkdir(exist_ok=True)
    
    for img_file in sorted(os.listdir(input_dir)):
        if img_file.endswith(('.png', '.jpg', '.jpeg')):
            image = Image.open(f"{input_dir}/{img_file}").resize((1024, 576))
            
            frames = pipe(
                image,
                num_frames=25,
                motion_bucket_id=127,
                decode_chunk_size=8
            ).frames[0]
            
            output_name = img_file.rsplit('.', 1)[0] + '.mp4'
            export_to_video(frames, f"{output_dir}/{output_name}", fps=6)
            print(f"Generated: {output_name}")

API Server Setup

from fastapi import FastAPI, UploadFile
from fastapi.responses import FileResponse
import uuid

app = FastAPI()

@app.post("/generate-video")
async def generate_video(
    image: UploadFile,
    motion: int = 127,
    frames: int = 25
):
    img = Image.open(image.file).resize((1024, 576))
    
    result = pipe(
        img,
        num_frames=frames,
        motion_bucket_id=motion
    ).frames[0]
    
    output_path = f"/tmp/{uuid.uuid4()}.mp4"
    export_to_video(result, output_path, fps=6)
    
    return FileResponse(output_path, media_type="video/mp4")

Post-Production Integration

Combining with Video Editors

• Export individual frames as PNG sequence for maximum flexibility
• Import frame sequences into DaVinci Resolve, Premiere Pro, or After Effects
• Apply color grading and effects in professional editing software
• Composite SVD output with live footage for hybrid content

Upscaling Pipeline

• Use Real-ESRGAN or similar for frame-by-frame upscaling
• Interpolate with RIFE for higher frame rates (6fps → 24/30fps)
• Apply temporal consistency filters to reduce flickering
• Final encode at target resolution and codec

Comparison with Commercial Solutions