From 066f039a45e28cb35e1f0e3c8e1d8c8ecb5b4878 Mon Sep 17 00:00:00 2001
From: p82b7rtam <1761133400@qq.com>
Date: Mon, 29 Dec 2025 17:05:58 +0800
Subject: [PATCH] ADD file via upload

---
 feature_extractor.py | 103 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 103 insertions(+)
 create mode 100644 feature_extractor.py

diff --git a/feature_extractor.py b/feature_extractor.py
new file mode 100644
index 0000000..32d85b6
--- /dev/null
+++ b/feature_extractor.py
@@ -0,0 +1,103 @@
+"""
+风格特征提取器模块 - 基础版本和传统方法。
+"""
+
+import numpy as np
+from typing import Tuple, Dict, Any
+from abc import ABC, abstractmethod
+
+
+class BaseFeatureExtractor(ABC):
+    """特征提取器基类"""
+
+    @abstractmethod
+    def extract(self, image: np.ndarray) -> Dict[str, Any]:
+        """提取特征抽象方法"""
+        pass
+
+    @abstractmethod
+    def get_features(self) -> Dict[str, Any]:
+        """获取特征抽象方法"""
+        pass
+
+
+class StyleFeatureExtractor(BaseFeatureExtractor):
+    """
+    传统风格特征提取器。
+    通过计算图像的直方图和局部纹理特征来定义"风格"。
+    """
+
+    def __init__(self, config: Dict[str, Any]):
+        """
+        初始化提取器。
+
+        Args:
+            config: 配置字典，包含特征提取参数。
+        """
+        self.config = config
+        self.style_features: Dict[str, Any] = {}
+
+    def extract(self, image: np.ndarray) -> Dict[str, Any]:
+        """
+        从图像中提取风格特征。
+
+        Args:
+            image: 输入图像，形状为 (H, W, C)，值域 [0, 255]。
+
+        Returns:
+            一个包含各种风格特征的字典。
+        """
+        # 确保图像在[0, 1]范围
+        image_normalized = image.astype(np.float32) / 255.0
+
+        features = {}
+
+        # 1. 颜色直方图 (RGB通道)
+        hist_r, _ = np.histogram(image_normalized[:, :, 0].ravel(), bins=32, range=(0, 1))
+        hist_g, _ = np.histogram(image_normalized[:, :, 1].ravel(), bins=32, range=(0, 1))
+        hist_b, _ = np.histogram(image_normalized[:, :, 2].ravel(), bins=32, range=(0, 1))
+        features['color_histogram'] = np.concatenate([hist_r, hist_g, hist_b])
+
+        # 2. 局部纹理特征
+        diff_h = np.abs(np.diff(image_normalized, axis=1)).mean()
+        diff_v = np.abs(np.diff(image_normalized, axis=0)).mean()
+        features['texture_strength'] = np.array([diff_h, diff_v])
+
+        # 3. 平均颜色
+        features['mean_color'] = image_normalized.mean(axis=(0, 1))
+
+        # 4. 颜色标准差
+        features['color_std'] = image_normalized.std(axis=(0, 1))
+
+        self.style_features = features
+        return features
+
+    def get_features(self) -> Dict[str, Any]:
+        """
+        获取最近一次提取的风格特征。
+
+        Returns:
+            风格特征字典。
+        """
+        return self.style_features.copy()
+
+
+# 工厂函数，便于创建不同类型的提取器
+def create_feature_extractor(extractor_type: str, config: Dict[str, Any]) -> BaseFeatureExtractor:
+    """
+    创建特征提取器工厂函数。
+
+    Args:
+        extractor_type: 提取器类型 ('traditional' 或 'neural')
+        config: 配置字典
+
+    Returns:
+        特征提取器实例
+    """
+    if extractor_type == 'traditional':
+        return StyleFeatureExtractor(config)
+    elif extractor_type == 'neural':
+        from .neural_feature_extractor import NeuralStyleFeatureExtractor
+        return NeuralStyleFeatureExtractor(config)
+    else:
+        raise ValueError(f"不支持的提取器类型: {extractor_type}")
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