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5e75573 1890b5d 5e75573 1890b5d 5e75573 1890b5d 5e75573 1890b5d 5e75573 1890b5d 5e75573 1890b5d 5e75573 1890b5d 5e75573 1890b5d 5e75573 1890b5d 5e75573 1890b5d 5e75573 1890b5d 5e75573 | 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 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | # streamlit_app.py
import streamlit as st
import torch
from diffusers import WanPipeline
from diffusers.utils import export_to_video
import os
st.set_page_config(page_title="Text-to-Video Generator", page_icon="🎬", layout="wide")
@st.cache_resource
def load_model():
"""Load and cache the model"""
pipe = WanPipeline.from_pretrained(
"alibaba-pai/Wan2.2-Fun-A14B-Control",
torch_dtype=torch.float16,
variant="fp16"
)
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = pipe.to(device)
pipe.enable_model_cpu_offload()
pipe.enable_vae_slicing()
return pipe
st.title("🎬 Text-to-Video Generator")
st.markdown("### Powered by Wan2.2-Fun-A14B-Control")
# Sidebar for settings
with st.sidebar:
st.header("⚙️ Settings")
num_frames = st.slider("Number of Frames", 16, 81, 81)
height = st.slider("Height", 256, 1024, 768, step=64)
width = st.slider("Width", 256, 1536, 1360, step=64)
num_inference_steps = st.slider("Inference Steps", 20, 100, 50)
guidance_scale = st.slider("Guidance Scale", 1.0, 20.0, 7.5, step=0.5)
seed = st.number_input("Seed (-1 for random)", value=-1, step=1)
# Main content
prompt = st.text_area(
"Prompt",
value="A cat playing piano in a sunlit room, cinematic lighting, 4k",
height=100
)
negative_prompt = st.text_area(
"Negative Prompt",
value="blurry, low quality, distorted",
height=80
)
if st.button("🎬 Generate Video", type="primary"):
with st.spinner("Loading model..."):
pipe = load_model()
with st.spinner("Generating video... This may take a few minutes."):
try:
# Set seed
generator = None
if seed != -1:
generator = torch.Generator(device="cuda" if torch.cuda.is_available() else "cpu")
generator.manual_seed(int(seed))
# Generate
output = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
num_frames=num_frames,
height=height,
width=width,
num_inference_steps=num_inference_steps,
guidance_scale=guidance_scale,
generator=generator,
)
# Save video
frames = output.frames[0]
output_path = "output_video.mp4"
export_to_video(frames, output_path, fps=8)
st.success("✅ Video generated successfully!")
st.video(output_path)
# Download button
with open(output_path, "rb") as file:
st.download_button(
label="📥 Download Video",
data=file,
file_name="generated_video.mp4",
mime="video/mp4"
)
except Exception as e:
st.error(f"❌ Error: {str(e)}") |