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import gradio as gr
import spaces
import torch
from diffusers import AutoencoderKL, TCDScheduler
# (Assume ControlNet manual load or from_pretrained is already working)
from controlnet_union import ControlNetModel_Union
from pipeline_fill_sd_xl import StableDiffusionXLFillPipeline
from gradio_imageslider import ImageSlider
from huggingface_hub import hf_hub_download

from PIL import Image, ImageDraw
import numpy as np

# --- Load ControlNet and SDXL Fill Pipeline ---
# (Either manual download or via from_pretrained)
controlnet_model = ControlNetModel_Union.from_pretrained(
    "xinsir/controlnet-union-sdxl-1.0",
    torch_dtype=torch.float16,
    variant="fp16"
).to("cuda")

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=controlnet_model,
    variant="fp16",
).to("cuda")
pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)

# --- Utility functions ---
def can_expand(source_width, source_height, target_width, target_height, 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 = (width, height)
    scale = min(target[0] / image.width, target[1] / image.height)
    w, h = int(image.width * scale), int(image.height * scale)
    src = image.resize((w, h), Image.LANCZOS)

    # Resize percentage
    if resize_option == "Full": pct = 100
    elif resize_option == "50%": pct = 50
    elif resize_option == "33%": pct = 33
    elif resize_option == "25%": pct = 25
    else: pct = custom_resize_percentage

    rw, rh = max(int(src.width * pct / 100), 64), max(int(src.height * pct / 100), 64)
    src = src.resize((rw, rh), Image.LANCZOS)

    ox = max(int(rw * overlap_percentage / 100), 1)
    oy = max(int(rh * overlap_percentage / 100), 1)

    # Margins
    if alignment == "Middle": mx, my = (width - rw)//2, (height - rh)//2
    elif alignment == "Left": mx, my = 0, (height - rh)//2
    elif alignment == "Right": mx, my = width - rw, (height - rh)//2
    elif alignment == "Top": mx, my = (width - rw)//2, 0
    else: mx, my = (width - rw)//2, height - rh

    mx, my = max(0, min(mx, width - rw)), max(0, min(my, height - rh))

    bg = Image.new("RGB", target, (255,255,255))
    bg.paste(src, (mx, my))

    mask = Image.new("L", target, 255)
    d = ImageDraw.Draw(mask)

    lx = mx + (ox if overlap_left else 2)
    rx = mx + rw - (ox if overlap_right else 2)
    ty = my + (oy if overlap_top else 2)
    by = my + rh - (oy if overlap_bottom else 2)

    # Edge adjustments
    if alignment == "Left": lx = mx + (ox if overlap_left else 0)
    if alignment == "Right": rx = mx + rw - (ox if overlap_right else 0)
    if alignment == "Top": ty = my + (oy if overlap_top else 0)
    if alignment == "Bottom": by = my + rh - (oy if overlap_bottom else 0)

    d.rectangle([(lx, ty), (rx, by)], fill=0)
    return bg, mask


def preview_image_and_mask(*args):
    bg, mask = prepare_image_and_mask(*args)
    vis = bg.copy().convert("RGBA")
    red = Image.new("RGBA", bg.size, (255,0,0,64))
    overlay = Image.new("RGBA", bg.size, (0,0,0,0))
    overlay.paste(red, (0,0), mask)
    return Image.alpha_composite(vis, overlay)

# --- Fixed infer: return list for slider ---
@spaces.GPU(duration=24)
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"

    hole = background.copy()
    hole.paste(0, (0,0), mask)

    final_prompt = f"{prompt_input} , high quality, 4k"
    embeds = pipe.encode_prompt(final_prompt, "cuda", True)

    # Run pipeline and grab last frame
    gen = pipe(
        prompt_embeds=embeds[0],
        negative_prompt_embeds=embeds[1],
        pooled_prompt_embeds=embeds[2],
        negative_pooled_prompt_embeds=embeds[3],
        image=hole,
        num_inference_steps=num_inference_steps
    )
    last = None
    for img in gen:
        last = img

    out = last.convert("RGBA")
    hole.paste(out, (0,0), mask)

    # Return a list: [input_hole_image, final_output]
    return [background, hole]


def clear_result():
    return gr.update(value=None)

def preload_presets(ratio, w, h):
    if ratio == "9:16": return 720, 1280, gr.update()
    if ratio == "16:9": return 1280, 720, gr.update()
    if ratio == "1:1": return 1024, 1024, gr.update()
    return w, h, gr.update(open=True)

def select_the_right_preset(w, h):
    if (w,h) == (720,1280): return "9:16"
    if (w,h) == (1280,720): return "16:9"
    if (w,h) == (1024,1024): return "1:1"
    return "Custom"

def toggle_custom_resize_slider(opt):
    return gr.update(visible=(opt=="Custom"))

def update_history(img, history):
    history = history or []
    history.insert(0, img)
    return history

css = ".gradio-container { width: 1200px !important; }"
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)