import gradio as gr
import torch
from PIL import Image, ImageDraw, ImageFont
from src.condition import Condition
from diffusers.pipelines import FluxPipeline
import numpy as np

from src.generate import seed_everything, generate

pipe = None


def init_pipeline():
    global pipe
    pipe = FluxPipeline.from_pretrained(
        "black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16
    )
    pipe = pipe.to("cuda")
    pipe.load_lora_weights(
        "Yuanshi/OminiControl",
        weight_name=f"omini/subject_512.safetensors",
        adapter_name="subject",
    )


def process_image_and_text(image, text):
    # center crop image
    w, h, min_size = image.size[0], image.size[1], min(image.size)
    image = image.crop(
        (
            (w - min_size) // 2,
            (h - min_size) // 2,
            (w + min_size) // 2,
            (h + min_size) // 2,
        )
    )
    image = image.resize((512, 512))

    condition = Condition("subject", image)

    if pipe is None:
        init_pipeline()

    result_img = generate(
        pipe,
        prompt=text.strip(),
        conditions=[condition],
        num_inference_steps=8,
        height=512,
        width=512,
    ).images[0]

    return result_img


def get_samples():
    sample_list = [
        {
            "image": "assets/oranges.jpg",
            "text": "A very close up view of this item. It is placed on a wooden table. The background is a dark room, the TV is on, and the screen is showing a cooking show. With text on the screen that reads 'Omini Control!'",
        },
        {
            "image": "assets/penguin.jpg",
            "text": "On Christmas evening, on a crowded sidewalk, this item sits on the road, covered in snow and wearing a Christmas hat, holding a sign that reads 'Omini Control!'",
        },
        {
            "image": "assets/rc_car.jpg",
            "text": "A film style shot. On the moon, this item drives across the moon surface. The background is that Earth looms large in the foreground.",
        },
        {
            "image": "assets/clock.jpg",
            "text": "In a Bauhaus style room, this item is placed on a shiny glass table, with a vase of flowers next to it. In the afternoon sun, the shadows of the blinds are cast on the wall.",
        },
    ]
    return [[Image.open(sample["image"]), sample["text"]] for sample in sample_list]


demo = gr.Interface(
    fn=process_image_and_text,
    inputs=[
        gr.Image(type="pil"),
        gr.Textbox(lines=2),
    ],
    outputs=gr.Image(type="pil"),
    title="OminiControl / Subject driven generation",
    examples=get_samples(),
)

if __name__ == "__main__":
    init_pipeline()
    demo.launch(
        debug=True,
        ssr_mode=False
    )