ip_adapter_inpainting.py

from PIL import Image
import os
import torch


from segmentation import get_cropped, get_blurred_mask, init_body as init_body_seg, init_face as init_face_seg
from img2txt import derive_caption, init as init_img2txt
from utils import alpha_composite
from adapter_model import MODEL

init_face_seg()
init_body_seg()
init_img2txt()

ip_model = MODEL("inpaint")


def generate(img_openpose_gen: Image, img_human: Image, img_clothes: Image, segment_id: int):
    cropped_clothes = get_cropped(img_openpose_gen, segment_id, False).resize((512, 768)) 
    cropped_body = get_cropped(img_human, segment_id, True).resize((512, 768))

    composite = alpha_composite(cropped_body.convert('RGBA'),
                                cropped_clothes.convert('RGBA')
                                )
    composite = alpha_composite(composite)

    mask = get_blurred_mask(composite, segment_id, False)
    prompt = derive_caption(img_clothes)

    ip_gen = ip_model.model.generate(
        prompt=prompt,
        pil_image=img_clothes,
        num_samples=1,
        num_inference_steps=50,
        seed=42,
        image=composite,
        mask_image=mask,
        strength=0.8,
        guidance_scale=7,
        scale=0.8
        ).images[0]

    cropped_head = get_cropped(img_openpose_gen, 13, False)
    ip_gen_final = alpha_composite(ip_gen.convert("RGBA"),
                                   cropped_head.convert("RGBA")
                                   )
    torch.cuda.empty_cache()
    return ip_gen_final