File size: 1,233 Bytes
8b81391 091d05d ed1f3d9 8b81391 091d05d 8b81391 ed1f3d9 b9db5fb ed1f3d9 b9db5fb 8b81391 e47304c 8b81391 f40690a 8b81391 ed1f3d9 8b81391 ed1f3d9 8b81391 |
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 |
from diffusers import StableDiffusionPipeline, DiffusionPipeline
import torch
import gradio as gr
import spaces
css = """
#img-display-output {
max-height: 60vh;
}
#img-display-output *{
max-height: 60vh;
}
"""
DEVICE = 'cuda'
model_id = "Onodofthenorth/SD_PixelArt_SpriteSheet_Generator"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe.to("cuda")
@spaces.GPU(enable_queue=True)
def generate_sprite(prompt):
# pipe = pipe.to(DEVICE)
# image = pipe(prompt).images[0]
images = pipe(prompt).images
return images
title = "# SD_PixelArt_SpriteSheet_Generator"
description = """Pixel Art Sprite Sheet Generator with Stable Diffusion Checkpoint."""
with gr.Blocks(css=css) as API:
gr.Markdown(title)
gr.Markdown(description)
with gr.Column():
inputs=gr.TextArea(label="Prompt", placeholder="Prompt")
# outputs=gr.Image(label="Ouput Image", type='pil', elem_id="img-display-output")
outputs=gr.Gallery(label="Ouput Images", columns=4, elem_id="img-display-output")
generate_btn = gr.Button(value="Generate")
generate_btn.click(generate_sprite, inputs=inputs, outputs=outputs, api_name="generate_mesh")
API.launch() |