Spaces:
Running
on
Zero
Running
on
Zero
advanced settings
Browse files
app.py
CHANGED
@@ -1,5 +1,7 @@
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from typing import Tuple
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import gradio as gr
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import spaces
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import torch
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@@ -14,6 +16,8 @@ creating this amazing model, and a big thanks to [Gothos](https://github.com/Got
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for taking it to the next level by enabling inpainting with the FLUX.
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"""
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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pipe = FluxInpaintPipeline.from_pretrained(
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@@ -44,7 +48,15 @@ def resize_image_dimensions(
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@spaces.GPU()
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def process(
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if not input_text:
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gr.Info("Please enter a text prompt.")
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return None
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@@ -64,14 +76,18 @@ def process(input_image_editor, input_text, progress=gr.Progress(track_tqdm=True
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resized_image = image.resize((width, height), Image.LANCZOS)
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resized_mask = mask.resize((width, height), Image.NEAREST)
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return pipe(
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prompt=input_text,
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image=resized_image,
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mask_image=resized_mask,
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width=width,
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height=height,
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strength=
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-
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).images[0], resized_mask
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@@ -86,6 +102,7 @@ with gr.Blocks() as demo:
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image_mode='RGB',
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layers=False,
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brush=gr.Brush(colors=["#FFFFFF"], color_mode="fixed"))
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with gr.Row():
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input_text_component = gr.Text(
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label="Prompt",
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@@ -96,6 +113,35 @@ with gr.Blocks() as demo:
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)
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submit_button_component = gr.Button(
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value='Submit', variant='primary', scale=0)
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with gr.Column():
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output_gallery_component = gr.Gallery(
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columns=[1],
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@@ -110,7 +156,11 @@ with gr.Blocks() as demo:
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fn=process,
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inputs=[
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input_image_editor_component,
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input_text_component
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],
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outputs=[
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output_gallery_component
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from typing import Tuple
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import random
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import numpy as np
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import gradio as gr
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import spaces
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import torch
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for taking it to the next level by enabling inpainting with the FLUX.
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"""
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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 2048
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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pipe = FluxInpaintPipeline.from_pretrained(
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@spaces.GPU()
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def process(
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input_image_editor: dict,
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input_text: str,
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seed_slicer: int,
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randomize_seed_checkbox: bool,
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strength_slider: float,
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num_inference_steps_slider: int,
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progress=gr.Progress(track_tqdm=True)
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):
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if not input_text:
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gr.Info("Please enter a text prompt.")
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return None
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resized_image = image.resize((width, height), Image.LANCZOS)
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resized_mask = mask.resize((width, height), Image.NEAREST)
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if randomize_seed_checkbox:
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seed_slicer = random.randint(0, MAX_SEED)
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generator = torch.Generator().manual_seed(seed_slicer)
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return pipe(
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prompt=input_text,
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image=resized_image,
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mask_image=resized_mask,
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width=width,
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height=height,
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strength=strength_slider,
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generator=generator,
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num_inference_steps=num_inference_steps_slider
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).images[0], resized_mask
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image_mode='RGB',
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layers=False,
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brush=gr.Brush(colors=["#FFFFFF"], color_mode="fixed"))
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with gr.Row():
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input_text_component = gr.Text(
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label="Prompt",
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)
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submit_button_component = gr.Button(
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value='Submit', variant='primary', scale=0)
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with gr.Accordion("Advanced Settings", open=False):
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seed_slicer_component = gr.Slider(
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label="Seed",
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minimum=0,
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maximum=MAX_SEED,
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step=1,
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value=0,
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)
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randomize_seed_checkbox_component = gr.Checkbox(
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label="Randomize seed", value=True)
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with gr.Row():
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strength_slider_component = gr.Slider(
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label="Strength",
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minimum=0,
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maximum=1,
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step=0.01,
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value=0.75,
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)
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num_inference_steps_slider_component = gr.Slider(
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label="Number of inference steps",
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minimum=1,
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maximum=50,
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step=1,
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value=20,
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)
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with gr.Column():
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output_gallery_component = gr.Gallery(
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columns=[1],
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fn=process,
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inputs=[
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input_image_editor_component,
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input_text_component,
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seed_slicer_component,
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randomize_seed_checkbox_component,
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strength_slider_component,
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num_inference_steps_slider_component
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],
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outputs=[
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output_gallery_component
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