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import random
from PIL import Image
from diffusers import StableDiffusionPipeline
import gradio as gr
import torch
from spectro import wav_bytes_from_spectrogram_image
device = "cuda" if torch.cuda.is_available() else "cpu"
dtype = torch.float16 if device == "cuda" else torch.float32
model_id = "runwayml/stable-diffusion-v1-5"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=dtype)
pipe = pipe.to(device)
model_id2 = "riffusion/riffusion-model-v1"
pipe2 = StableDiffusionPipeline.from_pretrained(model_id2, torch_dtype=dtype)
pipe2 = pipe2.to(device)
COLORS = [
["#ff0000", "#00ff00"],
["#00ff00", "#0000ff"],
["#0000ff", "#ff0000"],
]
title = """
<div style="text-align: center; max-width: 650px; margin: 0 auto 10px;">
<div style="display: inline-flex; align-items: center; gap: 0.8rem; font-size: 1.75rem;">
<h1 style="font-weight: 950; margin-bottom: 7px; color: #000; font-weight: bold;">Riffusion and Stable Diffusion</h1>
</div>
<p style="margin-bottom: 10px; font-size: 98%; color: #666;">Text to music player.</p>
</div>
"""
def get_bg_image(prompt):
images = pipe(prompt)
print("Image generated!")
image_output = images.images[0] if not images.nsfw_content_detected[0] else Image.open("nsfw_placeholder.jpg")
return image_output
def get_music(prompt):
spec = pipe2(prompt).images[0]
print(spec)
wav = wav_bytes_from_spectrogram_image(spec)
with open("output.wav", "wb") as f:
f.write(wav[0].getbuffer())
return 'output.wav'
def infer(prompt):
image = get_bg_image(prompt)
audio = get_music(prompt)
return (
gr.make_waveform(audio, bg_image=image, bars_color=random.choice(COLORS)),
)
css = """
#col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
#prompt-in {
border: 2px solid #666;
border-radius: 2px;
padding: 8px;
}
#btn-container {
display: flex;
align-items: center;
justify-content: center;
width: calc(15% - 16px);
height: calc(15% - 16px);
}
/* Style the submit button */
#submit-btn {
background-color: #382a1d;
color: #fff;
border: 1px solid #000;
border-radius: 4px;
padding: 8px;
font-size: 16px;
cursor: pointer;
}
"""
with gr.Blocks(css=css) as demo:
gr.HTML(title)
with gr.Column(elem_id="col-container"):
prompt_input = gr.Textbox(placeholder="a cat diva singing in a New York jazz club",
elem_id="prompt-in",
show_label=False)
with gr.Row(elem_id="btn-container"):
send_btn = gr.Button(value="Send", elem_id="submit-btn")
video_output = gr.Video()
send_btn.click(infer, inputs=[prompt_input], outputs=[video_output])
demo.queue().launch(debug=True) |