feat(project): move edge_inference_service contents to root and update paths

- Moved all project files and directories (config, core, models, etc.) from
  edge_inference_service/ to the repository root ai_edge/
- Updated model path in config/settings.py to reflect new structure
- Revised usage paths in __init__.py documentation

tests/test_preprocessor.py

@@ -0,0 +1,212 @@
+"""
+预处理模块单元测试
+"""
+
+import unittest
+from unittest.mock import MagicMock, patch
+import sys
+import os
+import numpy as np
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+
+class TestROICropper(unittest.TestCase):
+    """测试ROI裁剪器"""
+    
+    def setUp(self):
+        """设置测试环境"""
+        from core.preprocessor import ROICropper
+        self.cropper = ROICropper()
+        
+        self.test_image = np.zeros((480, 640, 3), dtype=np.uint8)
+        self.test_image[100:200, 200:400] = 255
+    
+    def test_crop_rectangle(self):
+        """测试矩形裁剪"""
+        from config.config_models import ROIInfo, ROIType, AlgorithmType
+        from core.preprocessor import ROICropper
+        
+        roi = ROIInfo(
+            roi_id="roi001",
+            camera_id="cam001",
+            roi_type=ROIType.RECTANGLE,
+            coordinates=[[200, 100], [400, 200]],
+            algorithm_type=AlgorithmType.LEAVE_POST,
+        )
+        
+        cropper = ROICropper()
+        result = cropper.crop(self.test_image, roi)
+        
+        self.assertIsNotNone(result)
+        self.assertEqual(result.shape[1], 200)
+        self.assertEqual(result.shape[0], 100)
+    
+    def test_crop_polygon(self):
+        """测试多边形裁剪"""
+        from config.config_models import ROIInfo, ROIType, AlgorithmType
+        from core.preprocessor import ROICropper
+        
+        roi = ROIInfo(
+            roi_id="roi001",
+            camera_id="cam001",
+            roi_type=ROIType.POLYGON,
+            coordinates=[[200, 100], [400, 100], [400, 200], [200, 200]],
+            algorithm_type=AlgorithmType.LEAVE_POST,
+        )
+        
+        cropper = ROICropper()
+        result = cropper.crop(self.test_image, roi)
+        
+        self.assertIsNotNone(result)
+    
+    def test_create_mask(self):
+        """测试创建掩码"""
+        from config.config_models import ROIInfo, ROIType, AlgorithmType
+        from core.preprocessor import ROICropper
+        
+        roi = ROIInfo(
+            roi_id="roi001",
+            camera_id="cam001",
+            roi_type=ROIType.RECTANGLE,
+            coordinates=[[100, 100], [200, 200]],
+            algorithm_type=AlgorithmType.LEAVE_POST,
+        )
+        
+        cropper = ROICropper()
+        mask = cropper.create_mask((480, 640), roi)
+        
+        self.assertEqual(mask.shape, (480, 640))
+        self.assertTrue(mask[150, 150] > 0)
+
+
+class TestLetterboxPreprocessor(unittest.TestCase):
+    """测试Letterbox预处理器"""
+    
+    def test_preprocess_16_9(self):
+        """测试16:9图像预处理"""
+        from core.preprocessor import LetterboxPreprocessor
+        
+        preprocessor = LetterboxPreprocessor(target_size=(480, 480))
+        
+        image = np.zeros((720, 1280, 3), dtype=np.uint8)
+        image[:, :] = [100, 120, 140]
+        
+        result, scale_info = preprocessor.preprocess(image)
+        
+        self.assertEqual(result.shape, (480, 480, 3))
+        self.assertEqual(len(scale_info), 4)
+    
+    def test_preprocess_square(self):
+        """测试正方形图像预处理"""
+        from core.preprocessor import LetterboxPreprocessor
+        
+        preprocessor = LetterboxPreprocessor(target_size=(480, 480))
+        
+        image = np.zeros((640, 640, 3), dtype=np.uint8)
+        
+        result, scale_info = preprocessor.preprocess(image)
+        
+        self.assertEqual(result.shape, (480, 480, 3))
+    
+    def test_revert_coordinates(self):
+        """测试坐标还原"""
+        from core.preprocessor import LetterboxPreprocessor
+        
+        preprocessor = LetterboxPreprocessor(target_size=(480, 480))
+        
+        scale = 0.5
+        pad_x = 60
+        pad_y = 60
+        
+        scale_info = (scale, pad_x, pad_y, scale)
+        
+        box = [100, 100, 200, 200]
+        reverted = preprocessor.revert_coordinates(box, scale_info)
+        
+        self.assertEqual(len(reverted), 4)
+        self.assertGreater(reverted[0], 0)
+
+
+class TestBatchPreprocessor(unittest.TestCase):
+    """测试Batch预处理器"""
+    
+    def test_preprocess_batch(self):
+        """测试批次预处理"""
+        from core.preprocessor import BatchPreprocessor
+        
+        preprocessor = BatchPreprocessor(
+            target_size=(480, 480),
+            max_batch_size=4,
+            fp16_mode=True
+        )
+        
+        images = [
+            np.zeros((640, 640, 3), dtype=np.uint8)
+            for _ in range(2)
+        ]
+        
+        result, scale_info_list = preprocessor.preprocess_batch(images)
+        
+        self.assertEqual(result.shape[0], 2)
+        self.assertEqual(len(scale_info_list), 2)
+    
+    def test_memory_allocation(self):
+        """测试内存分配"""
+        from core.preprocessor import BatchPreprocessor
+        
+        preprocessor = BatchPreprocessor(
+            target_size=(480, 480),
+            max_batch_size=4,
+            fp16_mode=True
+        )
+        
+        mem = preprocessor.allocate_batch_memory(2)
+        
+        self.assertEqual(mem.shape[0], 2)
+        self.assertEqual(mem.dtype, np.float16)
+
+
+class TestImagePreprocessor(unittest.TestCase):
+    """测试图像预处理主类"""
+    
+    def test_preprocess_single(self):
+        """测试单张图像预处理"""
+        from core.preprocessor import ImagePreprocessor
+        
+        preprocessor = ImagePreprocessor()
+        
+        image = np.zeros((720, 1280, 3), dtype=np.uint8)
+        
+        result, scale_info = preprocessor.preprocess_single(image)
+        
+        self.assertEqual(result.shape, (480, 480, 3))
+    
+    def test_preprocess_batch(self):
+        """测试批次预处理"""
+        from core.preprocessor import ImagePreprocessor
+        
+        preprocessor = ImagePreprocessor()
+        
+        images = [
+            np.zeros((720, 1280, 3), dtype=np.uint8)
+            for _ in range(4)
+        ]
+        
+        result, scale_info_list = preprocessor.preprocess_batch(images)
+        
+        self.assertEqual(result.shape[0], 4)
+    
+    def test_get_statistics(self):
+        """测试获取统计"""
+        from core.preprocessor import ImagePreprocessor
+        
+        preprocessor = ImagePreprocessor()
+        stats = preprocessor.get_statistics()
+        
+        self.assertIn("config", stats)
+        self.assertIn("memory", stats)
+
+
+if __name__ == "__main__":
+    unittest.main()