Spaces:
Running
on
Zero
Running
on
Zero
File size: 2,807 Bytes
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import gradio as gr
import spaces
from pit import PiTDemoPipeline
BLOCK_WIDTH = 300
BLOCK_HEIGHT = 360
FONT_SIZE = 3.5
pit_pipeline = PiTDemoPipeline(
prior_repo="kfirgold99/Piece-it-Together", prior_path="models/characters_ckpt/prior.ckpt"
)
@spaces.GPU
def run_character_generation(part_1, part_2, part_3, seed=None):
crops_paths = [part_1, part_2, part_3]
image = pit_pipeline.run(crops_paths=crops_paths, seed=seed, n_images=1)[0]
return image
with gr.Blocks(css="style.css") as demo:
gr.HTML(
"""<div style="text-align: center;"><h1>Piece it Together: Part-Based Concepting with IP-Priors</h1></div>"""
)
gr.HTML(
'<div style="text-align: center;"><h3><a href="https://eladrich.github.io/PiT/">https://eladrich.github.io/PiT/</a></h3></div>'
)
gr.HTML(
'<div style="text-align: center;">Piece it Together (PiT) combines different input parts to generate a complete concept in a prior domain.</div>'
)
with gr.Row(equal_height=True, elem_classes="justified-element"):
with gr.Column(scale=0, min_width=BLOCK_WIDTH):
part_1 = gr.Image(
label="Upload part 1 (or keep empty)", type="filepath", width=BLOCK_WIDTH, height=BLOCK_HEIGHT
)
with gr.Column(scale=0, min_width=BLOCK_WIDTH):
part_2 = gr.Image(
label="Upload part 2 (or keep empty)", type="filepath", width=BLOCK_WIDTH, height=BLOCK_HEIGHT
)
with gr.Column(scale=0, min_width=BLOCK_WIDTH):
part_3 = gr.Image(
label="Upload part 3 (or keep empty)", type="filepath", width=BLOCK_WIDTH, height=BLOCK_HEIGHT
)
with gr.Column(scale=0, min_width=BLOCK_WIDTH):
output_eq_1 = gr.Image(label="Output", width=BLOCK_WIDTH, height=BLOCK_HEIGHT)
with gr.Row(equal_height=True, elem_classes="justified-element"):
run_button = gr.Button("Create your character!", elem_classes="small-elem")
run_button.click(fn=run_character_generation, inputs=[part_1, part_2, part_3], outputs=[output_eq_1])
with gr.Row(equal_height=True, elem_classes="justified-element"):
pass
with gr.Row(equal_height=True, elem_classes="justified-element"):
with gr.Column(scale=1):
examples = [
[
"assets/characters_parts/part_a.jpg",
"assets/characters_parts/part_b.jpg",
"assets/characters_parts/part_c.jpg",
]
]
gr.Examples(
examples=examples,
inputs=[part_1, part_2, part_3],
outputs=[output_eq_1],
fn=run_character_generation,
cache_examples=False,
)
demo.queue().launch(share=True)
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