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import torch
import gradio as gr
from diffusers import FluxInpaintPipeline
MARKDOWN = """
# FLUX.1 Inpainting 🔥
"""
DEVICE = torch.device("cuda")
# DEVICE = torch.device("cpu")
pipe = FluxInpaintPipeline.from_pretrained(
"black-forest-labs/FLUX.1-schnell",
torch_dtype=torch.bfloat16)
pipe.to(DEVICE)
@spaces.GPU()
def process(input_image_editor, input_text, progress=gr.Progress(track_tqdm=True)):
if not input_text:
gr.Info("Please enter a text prompt.")
return None
image = input_image_editor['background']
mask_image = input_image_editor['layers'][0]
if not image:
gr.Info("Please upload an image.")
return None
if not mask_image:
gr.Info("Please draw a mask on the image.")
return None
generator = torch.Generator().manual_seed(42)
return pipe(
prompt=input_text,
image=image,
mask_image=mask_image,
width=1024,
height=1024,
strength=0.9
).images[0]
with gr.Blocks() as demo:
gr.Markdown(MARKDOWN)
with gr.Row():
with gr.Column():
input_image_editor_component = gr.ImageEditor(
label='Image',
type='pil',
sources=["upload", "webcam"],
image_mode='RGB',
layers=False,
brush=gr.Brush(colors=["#000000"], color_mode="fixed"))
input_text_component = gr.Textbox(
label='Text prompt',
placeholder='Cartoon cactus',)
submit_button_component = gr.Button(
value='Submit', variant='primary')
with gr.Column():
output_image_component = gr.Image(
type='pil', image_mode='RGB', label='Generated image')
submit_button_component.click(
fn=process,
inputs=[
input_image_editor_component,
input_text_component
],
outputs=[
output_image_component
]
)
demo.launch(debug=False, show_error=True)
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