Create app.py

app.py

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+import gradio as gr
+import torch
+from diffusers import StableVideoDiffusionPipeline
+from PIL import Image
+import imageio
+import os
+import uuid
+
+# Load model (automatically uses GPU if available)
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+pipe = StableVideoDiffusionPipeline.from_pretrained(
+    "stabilityai/stable-video-diffusion-img2vid-xt",
+    torch_dtype=torch.float16 if device == "cuda" else torch.float32
+)
+
+pipe = pipe.to(device)
+
+def generate_video(image, fps):
+    if image is None:
+        return None
+
+    image = image.convert("RGB")
+
+    # Generate frames
+    frames = pipe(image, num_frames=25).frames[0]
+
+    # Save video
+    filename = f"output_{uuid.uuid4().hex}.mp4"
+    imageio.mimsave(filename, frames, fps=fps)
+
+    return filename
+
+# UI
+with gr.Blocks() as demo:
+    gr.Markdown("# 🎬 StuffMotion AI (Image → Video)")
+    gr.Markdown("Upload an image and generate AI motion video")
+
+    with gr.Row():
+        image_input = gr.Image(type="pil", label="Input Image")
+
+    fps = gr.Slider(5, 30, value=12, step=1, label="FPS")
+
+    generate_btn = gr.Button("Generate Video")
+
+    video_output = gr.Video()
+
+    generate_btn.click(
+        fn=generate_video,
+        inputs=[image_input, fps],
+        outputs=video_output
+    )
+
+demo.launch()