Method binarize_image

ddddocr/preprocessing/image_processor.py:200–238

图像二值化 Args: image: 输入图像 threshold: 二值化阈值 method: 二值化方法 ('simple', 'otsu', 'adaptive') Returns: 二值化后的图像 Raises: ImageProcessError: 当处理失败时

(image: Image.Image, threshold: int = 128, 
                      method: str = 'simple')

    
    @staticmethod
    def binarize_image(image: Image.Image, threshold: int = 128, 
                      method: str = 'simple') -> Image.Image:
        """
        图像二值化
        
        Args:
            image: 输入图像
            threshold: 二值化阈值
            method: 二值化方法 ('simple', 'otsu', 'adaptive')
            
        Returns:
            二值化后的图像
            
        Raises:
            ImageProcessError: 当处理失败时
        """
        try:
            # 转换为灰度图
            if image.mode != 'L':
                gray_image = image.convert('L')
            else:
                gray_image = image
            
            img_array = image_to_numpy(gray_image)
            
            if method == 'simple':
                _, binary = cv2.threshold(img_array, threshold, 255, cv2.THRESH_BINARY)
            elif method == 'otsu':
                _, binary = cv2.threshold(img_array, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
            elif method == 'adaptive':
                binary = cv2.adaptiveThreshold(img_array, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, 
                                             cv2.THRESH_BINARY, 11, 2)
            else:
                raise ValueError(f"不支持的二值化方法: {method}")
            
            return numpy_to_image(binary, 'L')
            
        except Exception as e:
            raise ImageProcessError(f"图像二值化失败: {str(e)}") from e
    
    @staticmethod
    def preprocess_for_ocr(image: Image.Image, target_height: int = 64,