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Running
on
Zero
import gradio as gr | |
import spaces | |
import torch | |
from diffusers import AutoencoderKL, TCDScheduler | |
from diffusers.models.model_loading_utils import load_state_dict | |
from gradio_imageslider import ImageSlider | |
from huggingface_hub import hf_hub_download | |
from controlnet_union import ControlNetModel_Union | |
from pipeline_fill_sd_xl import StableDiffusionXLFillPipeline | |
from PIL import Image, ImageDraw | |
import numpy as np | |
config_file = hf_hub_download( | |
"xinsir/controlnet-union-sdxl-1.0", | |
filename="config_promax.json", | |
) | |
config = ControlNetModel_Union.load_config(config_file) | |
controlnet_model = ControlNetModel_Union.from_config(config) | |
model_file = hf_hub_download( | |
"xinsir/controlnet-union-sdxl-1.0", | |
filename="diffusion_pytorch_model_promax.safetensors", | |
) | |
sstate_dict = load_state_dict(model_file) | |
model, _, _, _, _ = ControlNetModel_Union._load_pretrained_model( | |
controlnet_model, sstate_dict, model_file, "xinsir/controlnet-union-sdxl-1.0" | |
) | |
model.to(device="cuda", dtype=torch.float16) | |
#---------------------- | |
vae = AutoencoderKL.from_pretrained( | |
"madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16 | |
).to("cuda") | |
pipe = StableDiffusionXLFillPipeline.from_pretrained( | |
"SG161222/RealVisXL_V5.0_Lightning", | |
torch_dtype=torch.float16, | |
vae=vae, | |
controlnet=model, | |
variant="fp16", | |
).to("cuda") | |
pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config) | |
def can_expand(source_width, source_height, target_width, target_height, alignment): | |
"""Checks if the image can be expanded based on the alignment.""" | |
if alignment in ("Left", "Right") and source_width >= target_width: | |
return False | |
if alignment in ("Top", "Bottom") and source_height >= target_height: | |
return False | |
return True | |
def prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom): | |
target_size = (width, height) | |
# Calculate the scaling factor to fit the image within the target size | |
scale_factor = min(target_size[0] / image.width, target_size[1] / image.height) | |
new_width = int(image.width * scale_factor) | |
new_height = int(image.height * scale_factor) | |
# Resize the source image to fit within target size | |
source = image.resize((new_width, new_height), Image.LANCZOS) | |
# Apply resize option using percentages | |
if resize_option == "Full": | |
resize_percentage = 100 | |
elif resize_option == "50%": | |
resize_percentage = 50 | |
elif resize_option == "33%": | |
resize_percentage = 33 | |
elif resize_option == "25%": | |
resize_percentage = 25 | |
else: # Custom | |
resize_percentage = custom_resize_percentage | |
# Calculate new dimensions based on percentage | |
resize_factor = resize_percentage / 100 | |
new_width = int(source.width * resize_factor) | |
new_height = int(source.height * resize_factor) | |
# Ensure minimum size of 64 pixels | |
new_width = max(new_width, 64) | |
new_height = max(new_height, 64) | |
# Resize the image | |
source = source.resize((new_width, new_height), Image.LANCZOS) | |
# Calculate the overlap in pixels based on the percentage | |
overlap_x = int(new_width * (overlap_percentage / 100)) | |
overlap_y = int(new_height * (overlap_percentage / 100)) | |
# Ensure minimum overlap of 1 pixel | |
overlap_x = max(overlap_x, 1) | |
overlap_y = max(overlap_y, 1) | |
# Calculate margins based on alignment | |
if alignment == "Middle": | |
margin_x = (target_size[0] - new_width) // 2 | |
margin_y = (target_size[1] - new_height) // 2 | |
elif alignment == "Left": | |
margin_x = 0 | |
margin_y = (target_size[1] - new_height) // 2 | |
elif alignment == "Right": | |
margin_x = target_size[0] - new_width | |
margin_y = (target_size[1] - new_height) // 2 | |
elif alignment == "Top": | |
margin_x = (target_size[0] - new_width) // 2 | |
margin_y = 0 | |
elif alignment == "Bottom": | |
margin_x = (target_size[0] - new_width) // 2 | |
margin_y = target_size[1] - new_height | |
# Adjust margins to eliminate gaps | |
margin_x = max(0, min(margin_x, target_size[0] - new_width)) | |
margin_y = max(0, min(margin_y, target_size[1] - new_height)) | |
# Create a new background image and paste the resized source image | |
background = Image.new('RGB', target_size, (255, 255, 255)) | |
background.paste(source, (margin_x, margin_y)) | |
# Create the mask | |
mask = Image.new('L', target_size, 255) | |
mask_draw = ImageDraw.Draw(mask) | |
# Calculate overlap areas | |
white_gaps_patch = 2 | |
left_overlap = margin_x + overlap_x if overlap_left else margin_x + white_gaps_patch | |
right_overlap = margin_x + new_width - overlap_x if overlap_right else margin_x + new_width - white_gaps_patch | |
top_overlap = margin_y + overlap_y if overlap_top else margin_y + white_gaps_patch | |
bottom_overlap = margin_y + new_height - overlap_y if overlap_bottom else margin_y + new_height - white_gaps_patch | |
if alignment == "Left": | |
left_overlap = margin_x + overlap_x if overlap_left else margin_x | |
elif alignment == "Right": | |
right_overlap = margin_x + new_width - overlap_x if overlap_right else margin_x + new_width | |
elif alignment == "Top": | |
top_overlap = margin_y + overlap_y if overlap_top else margin_y | |
elif alignment == "Bottom": | |
bottom_overlap = margin_y + new_height - overlap_y if overlap_bottom else margin_y + new_height | |
# Draw the mask | |
mask_draw.rectangle([ | |
(left_overlap, top_overlap), | |
(right_overlap, bottom_overlap) | |
], fill=0) | |
return background, mask | |
def preview_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom): | |
background, mask = prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom) | |
# Create a preview image showing the mask | |
preview = background.copy().convert('RGBA') | |
# Create a semi-transparent red overlay | |
red_overlay = Image.new('RGBA', background.size, (255, 0, 0, 64)) # Reduced alpha to 64 (25% opacity) | |
# Convert black pixels in the mask to semi-transparent red | |
red_mask = Image.new('RGBA', background.size, (0, 0, 0, 0)) | |
red_mask.paste(red_overlay, (0, 0), mask) | |
# Overlay the red mask on the background | |
preview = Image.alpha_composite(preview, red_mask) | |
return preview | |
def infer(image, width, height, overlap_percentage, num_inference_steps, resize_option, custom_resize_percentage, prompt_input, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom): | |
background, mask = prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom) | |
if not can_expand(background.width, background.height, width, height, alignment): | |
alignment = "Middle" | |
cnet_image = background.copy() | |
cnet_image.paste(0, (0, 0), mask) | |
final_prompt = f"{prompt_input} , high quality, 4k" | |
( | |
prompt_embeds, | |
negative_prompt_embeds, | |
pooled_prompt_embeds, | |
negative_pooled_prompt_embeds, | |
) = pipe.encode_prompt(final_prompt, "cuda", True) | |
for image in pipe( | |
prompt_embeds=prompt_embeds, | |
negative_prompt_embeds=negative_prompt_embeds, | |
pooled_prompt_embeds=pooled_prompt_embeds, | |
negative_pooled_prompt_embeds=negative_pooled_prompt_embeds, | |
image=cnet_image, | |
num_inference_steps=num_inference_steps | |
): | |
yield cnet_image, image | |
image = image.convert("RGBA") | |
cnet_image.paste(image, (0, 0), mask) | |
yield background, cnet_image | |
def clear_result(): | |
"""Clears the result ImageSlider.""" | |
return gr.update(value=None) | |
def preload_presets(target_ratio, ui_width, ui_height): | |
"""Updates the width and height sliders based on the selected aspect ratio.""" | |
if target_ratio == "9:16": | |
changed_width = 720 | |
changed_height = 1280 | |
return changed_width, changed_height, gr.update() | |
elif target_ratio == "16:9": | |
changed_width = 1280 | |
changed_height = 720 | |
return changed_width, changed_height, gr.update() | |
elif target_ratio == "1:1": | |
changed_width = 1024 | |
changed_height = 1024 | |
return changed_width, changed_height, gr.update() | |
elif target_ratio == "Custom": | |
return ui_width, ui_height, gr.update(open=True) | |
def select_the_right_preset(user_width, user_height): | |
if user_width == 720 and user_height == 1280: | |
return "9:16" | |
elif user_width == 1280 and user_height == 720: | |
return "16:9" | |
elif user_width == 1024 and user_height == 1024: | |
return "1:1" | |
else: | |
return "Custom" | |
def toggle_custom_resize_slider(resize_option): | |
return gr.update(visible=(resize_option == "Custom")) | |
def update_history(new_image, history): | |
"""Updates the history gallery with the new image.""" | |
if history is None: | |
history = [] | |
history.insert(0, new_image) | |
return history | |
css = """ | |
.gradio-container { | |
width: 1200px !important; | |
} | |
h1 { text-align: center; } | |
footer { visibility: hidden; } | |
""" | |
title = """<h1 align="center">Diffusers Image Outpaint Lightning</h1> | |
""" | |
with gr.Blocks(css=css) as demo: | |
gr.HTML(title) | |
with gr.Row(): | |
with gr.Column(): | |
input_image = gr.Image(type="pil", label="Input Image") | |
prompt_input = gr.Textbox(label="Prompt (Optional)") | |
run_button = gr.Button("Generate") | |
target_ratio = gr.Radio(["9:16","16:9","1:1","Custom"], value="9:16", label="Expected Ratio") | |
alignment_dropdown = gr.Dropdown(["Middle","Left","Right","Top","Bottom"], value="Middle", label="Alignment") | |
with gr.Accordion("Advanced settings", open=False) as adv: | |
width_slider = gr.Slider(720,1536,step=8, value=720, label="Target Width") | |
height_slider = gr.Slider(720,1536,step=8, value=1280, label="Target Height") | |
num_steps = gr.Slider(4,12,step=1, value=8, label="Steps") | |
overlap_pct = gr.Slider(1,50,step=1, value=10, label="Mask overlap (%)") | |
overlap_top = gr.Checkbox(label="Overlap Top", value=True) | |
overlap_right = gr.Checkbox(label="Overlap Right", value=True) | |
overlap_left = gr.Checkbox(label="Overlap Left", value=True) | |
overlap_bottom= gr.Checkbox(label="Overlap Bottom", value=True) | |
resize_opt = gr.Radio(["Full","50%","33%","25%","Custom"], value="Full", label="Resize input image") | |
custom_resize = gr.Slider(1,100,step=1, value=50, visible=False, label="Custom resize (%)") | |
preview_btn = gr.Button("Preview alignment and mask") | |
gr.Examples( | |
examples=[ | |
["./examples/example_1.webp",1280,720,"Middle"], | |
["./examples/example_2.jpg",1440,810,"Left"], | |
["./examples/example_3.jpg",1024,1024,"Top"], | |
["./examples/example_3.jpg",1024,1024,"Bottom"] | |
], | |
inputs=[input_image,width_slider,height_slider,alignment_dropdown] | |
) | |
with gr.Column(): | |
result = ImageSlider(label="Comparison", interactive=False, type="pil", slider_color="pink") | |
history_gallery = gr.Gallery(label="History", columns=6, object_fit="contain") | |
preview_image = gr.Image(label="Preview") | |
# Callbacks | |
run_button.click(clear_result, None, result) | |
run_button.click( | |
infer, | |
inputs=[ input_image, width_slider, height_slider, overlap_pct, num_steps, | |
resize_opt, custom_resize, prompt_input, alignment_dropdown, | |
overlap_left, overlap_right, overlap_top, overlap_bottom], | |
outputs=result | |
).then(update_history, inputs=[result, history_gallery], outputs=history_gallery) | |
target_ratio.change(preload_presets, [target_ratio, width_slider, height_slider], [width_slider, height_slider, adv]) | |
width_slider.change(select_the_right_preset, [width_slider, height_slider], target_ratio) | |
height_slider.change(select_the_right_preset, [width_slider, height_slider], target_ratio) | |
resize_opt.change(toggle_custom_resize_slider, resize_opt, custom_resize) | |
preview_btn.click(preview_image_and_mask, | |
[input_image, width_slider, height_slider, overlap_pct, resize_opt, custom_resize, alignment_dropdown, | |
overlap_left, overlap_right, overlap_top, overlap_bottom], | |
preview_image) | |
demo.queue(max_size=20).launch(share=False, ssr_mode=False, show_error=True) |