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075c786 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | import gradio as gr
import torch
from diffusers import StableDiffusionPipeline
import imageio
from moviepy.editor import ImageSequenceClip
# Load the text-to-video model
def load_model():
model = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-v1-4")
model.to("cuda") # Ensure the model runs on GPU
return model
model = load_model()
# Generate video frames
def generate_video(prompt, num_frames=30, fps=10):
frames = []
for i in range(num_frames):
# Add variation to the prompt for each frame
frame_prompt = f"{prompt}, frame {i}"
image = model(frame_prompt).images[0]
frames.append(image)
# Save frames as video
video_path = "generated_video.mp4"
clip = ImageSequenceClip([f for f in frames], fps=fps)
clip.write_videofile(video_path, codec="libx264")
return video_path
# Gradio Interface
def process_prompt(prompt):
video_path = generate_video(prompt)
return video_path
interface = gr.Interface(
fn=process_prompt,
inputs="text",
outputs="video",
title="Text-to-Video Generator",
description="Enter a prompt to generate a video based on your description."
)
# Launch the app
interface.launch()
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