Update app.py
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app.py
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import
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import torch
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from diffusers import StableDiffusionPipeline, StableVideoDiffusionPipeline
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from diffusers.utils import export_to_video
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from PIL import Image
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text2img_pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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video_pipe = StableVideoDiffusionPipeline.from_pretrained(
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"stabilityai/stable-video-diffusion-img2vid-xt",
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image = text2img_pipe(prompt).images[0]
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if
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image = image.resize((1024, 576))
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else:
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image = image.resize((576, 1024))
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# Generate video
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generator = torch.manual_seed(42)
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frames = video_pipe(image, decode_chunk_size=8, generator=generator).frames[0]
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export_to_video(frames, "output.mp4", fps=7)
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return "output.mp4"
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fn=generate_video,
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inputs=[
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gr.Textbox(label="Scene Prompt", placeholder="e.g. A 3D Islamic city at sunset, 4K"),
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gr.Radio(["16:9", "9:16"], label="Aspect Ratio", value="16:9")
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],
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outputs=gr.Video(label="Generated Video"),
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title="Text → Image → Video Generator",
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description="Enter a scene prompt and get a cinematic video. Powered by Stable Diffusion + Stable Video Diffusion."
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).launch()
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from fastapi import FastAPI, Form
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from fastapi.responses import FileResponse
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import torch
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from diffusers import StableDiffusionPipeline, StableVideoDiffusionPipeline
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from diffusers.utils import export_to_video
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from PIL import Image
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app = FastAPI()
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# Check device
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device = "cuda" if torch.cuda.is_available() else "cpu"
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dtype = torch.float16 if device == "cuda" else torch.float32
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variant = "fp16" if device == "cuda" else None
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# Load text-to-image model
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text2img_pipe = StableDiffusionPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5",
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torch_dtype=dtype
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).to(device)
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# Load image-to-video model
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video_pipe = StableVideoDiffusionPipeline.from_pretrained(
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"stabilityai/stable-video-diffusion-img2vid-xt",
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torch_dtype=dtype,
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variant=variant
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).to(device)
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@app.post("/generate")
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def generate_video(prompt: str = Form(...), aspect: str = Form("16:9")):
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image = text2img_pipe(prompt).images[0]
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image = image.resize((1024, 576) if aspect == "16:9" else (576, 1024))
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generator = torch.manual_seed(42)
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frames = video_pipe(image, decode_chunk_size=8, generator=generator).frames[0]
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export_to_video(frames, "output.mp4", fps=7)
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return FileResponse("output.mp4", media_type="video/mp4", filename="output.mp4")
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