| import time |
| from typing import Optional, Tuple |
|
|
| import cv2 |
| import numpy as np |
|
|
| from config import logger, REMBG_AVAILABLE |
|
|
| if REMBG_AVAILABLE: |
| import rembg |
| from rembg import new_session |
| from PIL import Image |
|
|
|
|
| class RembgProcessor: |
| """rembg抠图处理器""" |
|
|
| def __init__(self): |
| start_time = time.perf_counter() |
| self.session = None |
| self.available = False |
| self.model_name = "u2net" |
|
|
| if REMBG_AVAILABLE: |
| try: |
| |
| self.session = new_session(self.model_name) |
| self.available = True |
| logger.info(f"rembg background removal processor initialized successfully, using model: {self.model_name}") |
| except Exception as e: |
| logger.error(f"rembg background removal processor initialization failed: {e}") |
| self.available = False |
| else: |
| logger.warning("rembg is not available, background removal function will be disabled") |
| init_time = time.perf_counter() - start_time |
| if self.available: |
| logger.info(f"RembgProcessor initialized successfully, time: {init_time:.3f}s") |
| else: |
| logger.info(f"RembgProcessor initialization completed but not available, time: {init_time:.3f}s") |
|
|
| def is_available(self) -> bool: |
| """检查抠图处理器是否可用""" |
| return self.available and self.session is not None |
|
|
| def remove_background(self, image: np.ndarray, background_color: Optional[Tuple[int, int, int]] = None) -> np.ndarray: |
| """ |
| 移除图片背景 |
| :param image: 输入的OpenCV图像(BGR格式) |
| :param background_color: 替换的背景颜色(BGR格式),如果为None则保持透明背景 |
| :return: 处理后的图像 |
| """ |
| if not self.is_available(): |
| raise Exception("rembg抠图处理器不可用") |
|
|
| try: |
| |
| image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) |
| pil_image = Image.fromarray(image_rgb) |
|
|
| |
| logger.info("Starting to remove background using rembg...") |
| output_image = rembg.remove(pil_image, session=self.session) |
|
|
| |
| if background_color is not None: |
| |
| background = Image.new('RGB', output_image.size, background_color[::-1]) |
| |
| background.paste(output_image, mask=output_image) |
| result_array = np.array(background) |
| result_bgr = cv2.cvtColor(result_array, cv2.COLOR_RGB2BGR) |
| else: |
| |
| result_array = np.array(output_image) |
| if result_array.shape[2] == 4: |
| |
| result_bgr = cv2.cvtColor(result_array, cv2.COLOR_RGBA2BGRA) |
| else: |
| result_bgr = cv2.cvtColor(result_array, cv2.COLOR_RGB2BGR) |
|
|
| logger.info("rembg background removal completed") |
| return result_bgr |
|
|
| except Exception as e: |
| logger.error(f"rembg background removal failed: {e}") |
| raise Exception(f"背景移除失败: {str(e)}") |
|
|
| def create_id_photo(self, image: np.ndarray, background_color: Tuple[int, int, int] = (255, 255, 255)) -> np.ndarray: |
| """ |
| 创建证件照(移除背景并添加纯色背景) |
| :param image: 输入的OpenCV图像 |
| :param background_color: 背景颜色,默认白色(BGR格式) |
| :return: 处理后的证件照 |
| """ |
| logger.info(f"Starting to create ID photo, background color: {background_color}") |
|
|
| |
| id_photo = self.remove_background(image, background_color) |
|
|
| logger.info("ID photo creation completed") |
| return id_photo |
|
|
| def get_supported_models(self) -> list: |
| """获取支持的模型列表""" |
| if not REMBG_AVAILABLE: |
| return [] |
|
|
| |
| return [ |
| "u2net", |
| "u2net_human_seg", |
| "silueta", |
| "isnet-general-use" |
| ] |
|
|
| def switch_model(self, model_name: str) -> bool: |
| """ |
| 切换rembg模型 |
| :param model_name: 模型名称 |
| :return: 是否切换成功 |
| """ |
| if not REMBG_AVAILABLE: |
| return False |
|
|
| try: |
| if model_name in self.get_supported_models(): |
| self.session = new_session(model_name) |
| self.model_name = model_name |
| logger.info(f"rembg model switched to: {model_name}") |
| return True |
| else: |
| logger.error(f"Unsupported model: {model_name}") |
| return False |
| except Exception as e: |
| logger.error(f"Failed to switch model: {e}") |
| return False |
|
|