1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
| import cv2
import numpy as np
class ImageAnonymizer:
"""图像匿名化工具"""
def __init__(self,
face_detector=None,
plate_detector=None):
self.face_detector = face_detector or self._load_face_detector()
self.plate_detector = plate_detector
def anonymize(self, image: np.ndarray, method: str = 'blur') -> np.ndarray:
"""匿名化图像
Args:
image: BGR 图像
method: 'blur' | 'pixelate' | 'solid' | 'silhouette'
Returns:
匿名化后的图像
"""
result = image.copy()
faces = self._detect_faces(image)
for (x, y, w, h) in faces:
if method == 'blur':
result = self._blur_region(result, x, y, w, h)
elif method == 'pixelate':
result = self._pixelate_region(result, x, y, w, h)
elif method == 'solid':
result = self._solid_region(result, x, y, w, h)
elif method == 'silhouette':
result = self._silhouette_region(result, x, y, w, h)
return result
def _detect_faces(self, image: np.ndarray) -> list:
"""检测人脸"""
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
faces = self.face_detector.detectMultiScale(gray, 1.1, 4)
return faces
def _blur_region(self, image, x, y, w, h, ksize: int = 51) -> np.ndarray:
"""模糊区域"""
roi = image[y:y+h, x:x+w]
blurred = cv2.GaussianBlur(roi, (ksize, ksize), 0)
image[y:y+h, x:x+w] = blurred
return image
def _pixelate_region(self, image, x, y, w, h, block_size: int = 10) -> np.ndarray:
"""像素化区域"""
roi = image[y:y+h, x:x+w]
h_blocks = max(1, h // block_size)
w_blocks = max(1, w // block_size)
small = cv2.resize(roi, (w_blocks, h_blocks), interpolation=cv2.INTER_LINEAR)
pixelated = cv2.resize(small, (w, h), interpolation=cv2.INTER_NEAREST)
image[y:y+h, x:x+w] = pixelated
return image
def _solid_region(self, image, x, y, w, h, color=(0, 0, 0)) -> np.ndarray:
"""实心填充"""
cv2.rectangle(image, (x, y), (x+w, y+h), color, -1)
return image
def _silhouette_region(self, image, x, y, w, h, color=(128, 128, 128)) -> np.ndarray:
"""剪影填充"""
cv2.ellipse(image, (x+w//2, y+h//2), (w//2, h//2), 0, 0, 360, color, -1)
return image
def _load_face_detector(self):
"""加载人脸检测器"""
return cv2.CascadeClassifier(
cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
)
class BatchAnonymizer:
"""批量匿名化工具"""
def __init__(self, input_dir: str, output_dir: str):
self.input_dir = input_dir
self.output_dir = output_dir
self.anonymizer = ImageAnonymizer()
def process_all(self, method: str = 'blur'):
"""处理所有图像"""
import os
from pathlib import Path
input_path = Path(self.input_dir)
output_path = Path(self.output_dir)
output_path.mkdir(parents=True, exist_ok=True)
for ext in ['*.jpg', '*.png', '*.jpeg']:
for img_file in input_path.glob(ext):
image = cv2.imread(str(img_file))
anonymized = self.anonymizer.anonymize(image, method)
output_file = output_path / img_file.name
cv2.imwrite(str(output_file), anonymized)
print(f"Anonymized: {img_file.name}")
|