AiDA_Python/app/service/design_batch/pipeline/split.py

import io
import logging

import cv2
import numpy as np
from PIL import Image
from cv2 import cvtColor, COLOR_BGR2RGBA

from app.core.config import AIDA_CLOTHING
from app.service.design_fast.utils.conversion_image import rgb_to_rgba
from app.service.design_fast.utils.transparent import sketch_to_transparent
from app.service.design_fast.utils.upload_image import upload_png_mask
from app.service.utils.generate_uuid import generate_uuid
from app.service.utils.new_oss_client import oss_upload_image, oss_get_image


class Split(object):
    def __init__(self, minio_client):
        self.minio_client = minio_client

    def __call__(self, result):
        try:

            if result['name'] in ('outwear', 'dress', 'blouse', 'skirt', 'trousers', 'tops', 'bottoms','accessories'):
                front_mask = result['front_mask']
                back_mask = result['back_mask']
                rgba_image = rgb_to_rgba(result['final_image'], front_mask + back_mask)
                new_size = (int(rgba_image.shape[1] * result["scale"] * result["resize_scale"][0]), int(rgba_image.shape[0] * result["scale"] * result["resize_scale"][1]))
                rgba_image = cv2.resize(rgba_image, new_size)
                result_front_image = np.zeros_like(rgba_image)
                front_mask = cv2.resize(front_mask, new_size)
                result_front_image[front_mask != 0] = rgba_image[front_mask != 0]
                result_front_image_pil = Image.fromarray(cvtColor(result_front_image, COLOR_BGR2RGBA))
                if 'transparent' in result.keys():
                    #  用户自选区域transparent
                    transparent = result['transparent']
                    if transparent['mask_url'] is not None and transparent['mask_url'] != "":
                        # 预处理用户自选区mask
                        seg_mask = oss_get_image(oss_client=self.minio_client, bucket=transparent['mask_url'].split('/')[0], object_name=transparent['mask_url'][transparent['mask_url'].find('/') + 1:], data_type="cv2")
                        seg_mask = cv2.resize(seg_mask, new_size, interpolation=cv2.INTER_NEAREST)
                        # 转换颜色空间为 RGB（OpenCV 默认是 BGR）
                        image_rgb = cv2.cvtColor(seg_mask, cv2.COLOR_BGR2RGB)

                        r, g, b = cv2.split(image_rgb)
                        blue_mask = b > r

                        # 创建红色和绿色掩码
                        transparent_mask = np.array(blue_mask, dtype=np.uint8) * 255
                        result_front_image_pil = sketch_to_transparent(result_front_image_pil, transparent_mask, transparent["scale"])
                    else:
                        result_front_image_pil = sketch_to_transparent(result_front_image_pil, front_mask, transparent["scale"])
                result['front_image'], result["front_image_url"], _ = upload_png_mask(self.minio_client, result_front_image_pil, f'{generate_uuid()}', mask=None)

                height, width = front_mask.shape
                mask_image = np.zeros((height, width, 3))
                mask_image[front_mask != 0] = [0, 0, 255]

                if result["name"] in ('blouse', 'dress', 'outwear', 'tops'):
                    result_back_image = np.zeros_like(rgba_image)
                    back_mask = cv2.resize(back_mask, new_size)
                    result_back_image[back_mask != 0] = rgba_image[back_mask != 0]
                    result_back_image_pil = Image.fromarray(cvtColor(result_back_image, COLOR_BGR2RGBA))
                    result['back_image'], result["back_image_url"], _ = upload_png_mask(self.minio_client, result_back_image_pil, f'{generate_uuid()}', mask=None)
                    mask_image[back_mask != 0] = [0, 255, 0]

                    rbga_mask = rgb_to_rgba(mask_image, front_mask + back_mask)
                    mask_pil = Image.fromarray(cvtColor(rbga_mask.astype(np.uint8), COLOR_BGR2RGBA))
                    image_data = io.BytesIO()
                    mask_pil.save(image_data, format='PNG')
                    image_data.seek(0)
                    image_bytes = image_data.read()
                    req = oss_upload_image(oss_client=self.minio_client, bucket=AIDA_CLOTHING, object_name=f"mask/mask_{generate_uuid()}.png", image_bytes=image_bytes)
                    result['mask_url'] = req.bucket_name + "/" + req.object_name
                else:
                    rbga_mask = rgb_to_rgba(mask_image, front_mask)
                    mask_pil = Image.fromarray(cvtColor(rbga_mask.astype(np.uint8), COLOR_BGR2RGBA))
                    image_data = io.BytesIO()
                    mask_pil.save(image_data, format='PNG')
                    image_data.seek(0)
                    image_bytes = image_data.read()
                    req = oss_upload_image(oss_client=self.minio_client, bucket=AIDA_CLOTHING, object_name=f"mask/mask_{generate_uuid()}.png", image_bytes=image_bytes)
                    result['mask_url'] = req.bucket_name + "/" + req.object_name
                    result['back_image'] = None
                    result["back_image_url"] = None
                    # result["back_mask_url"] = None
                    # result['back_mask_image'] = None
            # 创建中间图层
            result_pattern_image_rgba = rgb_to_rgba(result['pattern_image'], result['mask'])
            result_pattern_image_pil = Image.fromarray(cvtColor(result_pattern_image_rgba, COLOR_BGR2RGBA))
            result['pattern_image'], result['pattern_image_url'], _ = upload_png_mask(self.minio_client, result_pattern_image_pil, f'{generate_uuid()}')
            return result
        except Exception as e:
            logging.warning(f"split runtime exception : {e} image_id : {result['image_id']}")