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
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
# import cv2
# import os
# import pandas as pd
#
#
# def detect_features(patent_img, product_img):
# # 初始化ORB检测器
# orb = cv2.ORB_create()
#
# # 寻找关键点和描述符
# kp1, des1 = orb.detectAndCompute(patent_img, None)
# kp2, des2 = orb.detectAndCompute(product_img, None)
#
# # 创建 BFMatcher 对象
# bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
#
# # 匹配描述符
# if des1 is not None and des2 is not None:
# matches = bf.match(des1, des2)
# # 按照距离排序
# matches = sorted(matches, key=lambda x: x.distance)
#
# # 计算匹配的平均距离
# avg_distance = sum(match.distance for match in matches) / len(matches)
# num_matches = len(matches)
# else:
# matches = []
# avg_distance = float('inf') # 如果没有匹配，设置为无穷大
# num_matches = 0
#
# return matches, avg_distance, num_matches
#
#
# def batch_detect(patent_image_path, product_images_folder, output_csv):
# # 读取专利图片并转换为灰度图
# if not os.path.exists(patent_image_path):
# print(f"Patent image path does not exist: {patent_image_path}")
# return
#
# patent_img = cv2.imread(patent_image_path, cv2.IMREAD_GRAYSCALE)
# if patent_img is None:
# print(f"Failed to load patent image: {patent_image_path}")
# return
#
# # 准备结果列表
# results = []
#
# # 遍历产品图片文件夹
# for filename in os.listdir(product_images_folder):
# if filename.endswith(".png") or filename.endswith(".jpg") or filename.endswith(".jpeg"):
# product_image_path = os.path.join(product_images_folder, filename)
# if not os.path.exists(product_image_path):
# print(f"Product image path does not exist: {product_image_path}")
# continue
#
# product_img = cv2.imread(product_image_path)
# if product_img is None:
# print(f"Failed to load product image: {product_image_path}")
# continue
#
# # 将产品图片转换为灰度图
# product_img_gray = cv2.cvtColor(product_img, cv2.COLOR_BGR2GRAY)
#
# # 检测特征
# matches, avg_distance, num_matches = detect_features(patent_img, product_img_gray)
#
# # 保存结果
# results.append({
# 'product_image': filename,
# 'avg_distance': avg_distance,
# 'num_matches': num_matches
# })
#
# # 保存结果到CSV
# df = pd.DataFrame(results)
# df.to_csv(output_csv, index=False)
#
# print(f"Results saved to {output_csv}")
#
#
# # 使用示例
# # patent_image_path = rf'E:/方星钧/工作/temp/pattern/企业微信截图_17169558138503.png'
# # patent_image_path = rf'E:\方星钧\工作\temp\pattern/企业微信截图_17169558377464.png'
# # patent_image_path = 'E:\\方星钧\\工作\\temp\\pattern\\企业微信截图_17169558138503.png'
# patent_image_path = r"C:\test\resaved_image.png"
#
# product_images_folder = rf'E:\方星钧\工作\temp\product'
# output_csv = rf'./comparison_results.csv'
#
# batch_detect(patent_image_path, product_images_folder, output_csv)
#
#
# import cv2
# import os
#
# # 检查文件路径
# patent_image_path = 'E:/方星钧/工作/temp/pattern/企业微信截图_17169558138503.png'
# if not os.path.exists(patent_image_path):
# print(f"Patent image path does not exist: {patent_image_path}")
# else:
# print(f"Patent image path exists: {patent_image_path}")
#
# # 尝试读取图像
# patent_img = cv2.imread(patent_image_path, cv2.IMREAD_GRAYSCALE)
# if patent_img is None:
# print(f"Failed to load patent image: {patent_image_path}")
# else:
# print(f"Successfully loaded patent image: {patent_image_path}")
#
# # 显示图像以确认读取正确
# cv2.imshow('Patent Image', patent_img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
#
#
#
# from PIL import Image
# import cv2
# import os
#
# # 原始专利图像路径
# patent_image_path = r'E:\方星钧\工作\temp\pattern\企业微信截图_17169558138503.png'
# # 重新保存的图像路径
# new_image_path = r'E:\方星钧\工作\temp\pattern\resaved_image.png'
#
# # 使用 PIL 重新保存图像
# try:
# patent_img = Image.open(patent_image_path)
# patent_img.save(new_image_path)
# print(f"Successfully resaved patent image: {new_image_path}")
# except Exception as e:
# print(f"Failed to resave patent image: {patent_image_path}, error: {e}")
#
# # 尝试使用 OpenCV 读取重新保存的图像
# new_img = cv2.imread(new_image_path, cv2.IMREAD_GRAYSCALE)
# if new_img is None:
# print(f"Failed to load resaved image: {new_image_path}")
# else:
# print(f"Successfully loaded resaved image: {new_image_path}")
#
# # 显示图像以确认读取正确
# cv2.imshow('Resaved Image', new_img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
#
# from PIL import Image
# import cv2
# import os
#
# # 尝试使用不同的路径和格式
# original_path = r'E:\方星钧\工作\temp\pattern\企业微信截图_17169558138503.png'
# new_png_path = r'E:\方星钧\工作\temp\pattern\resaved_image.png'
# new_jpg_path = r'./resaved_image.jpg'
#
# # 使用 PIL 重新保存图像为不同格式和路径
# try:
# patent_img = Image.open(original_path)
# patent_img.save(new_png_path)
# patent_img.save(new_jpg_path)
# print(f"Successfully resaved patent image to PNG and JPG formats.")
# except Exception as e:
# print(f"Failed to resave patent image: {original_path}, error: {e}")
#
# # 尝试使用 OpenCV 读取重新保存的图像（PNG 格式）
# new_img_png = cv2.imread(new_png_path, cv2.IMREAD_GRAYSCALE)
# if new_img_png is None:
# print(f"Failed to load resaved PNG image: {new_png_path}")
# else:
# print(f"Successfully loaded resaved PNG image: {new_png_path}")
#
# # 显示图像以确认读取正确
# cv2.imshow('Resaved PNG Image', new_img_png)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
#
# # 尝试使用 OpenCV 读取重新保存的图像（JPG 格式）
# new_img_jpg = cv2.imread(new_jpg_path, cv2.IMREAD_GRAYSCALE)
# if new_img_jpg is None:
# print(f"Failed to load resaved JPG image: {new_jpg_path}")
# else:
# print(f"Successfully loaded resaved JPG image: {new_jpg_path}")
#
# # 显示图像以确认读取正确
# cv2.imshow('Resaved JPG Image', new_img_jpg)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
from PIL import Image
import cv2
import os
import shutil
import matplotlib.pyplot as plt
# 原始专利图像路径
original_patent_image_path = r'E:\方星钧\工作\temp\pattern\11.png'
# 新的简单路径
test_directory = r'C:\test'
new_png_path = os.path.join(test_directory, 'p11.png')
new_jpg_path = os.path.join(test_directory, 'p11.jpg')
# 创建测试文件夹
os.makedirs(test_directory, exist_ok=True)
# 确保原始路径存在，并复制图像到新路径
try:
shutil.copy(original_patent_image_path, test_directory)
copied_image_path = os.path.join(test_directory, os.path.basename(original_patent_image_path))
print(f"Successfully copied patent image to: {copied_image_path}")
except Exception as e:
print(f"Failed to copy patent image: {original_patent_image_path}, error: {e}")
# 使用 PIL 重新保存图像为不同格式和路径
try:
patent_img = Image.open(copied_image_path)
patent_img.save(new_png_path)
# 保存为JPEG格式时，如果图像有alpha通道，需要先去掉alpha通道
patent_img.convert('RGB').save(new_jpg_path)
print(f"Successfully resaved patent image to PNG and JPG formats.")
except Exception as e:
print(f"Failed to resave patent image: {copied_image_path}, error: {e}")
# 尝试使用 PIL 读取并显示重新保存的图像（PNG 格式）
try:
resaved_img_png = Image.open(new_png_path)
resaved_img_png.show()
print(f"Successfully loaded and displayed resaved PNG image using PIL.")
except Exception as e:
print(f"Failed to load resaved PNG image using PIL: {new_png_path}, error: {e}")
# 尝试使用 OpenCV 读取重新保存的图像（PNG 格式）
new_img_png = cv2.imread(new_png_path, cv2.IMREAD_GRAYSCALE)
if new_img_png is None:
print(f"Failed to load resaved PNG image using OpenCV: {new_png_path}")
else:
print(f"Successfully loaded resaved PNG image using OpenCV: {new_png_path}")
# 使用 Matplotlib 显示图像
plt.imshow(new_img_png, cmap='gray')
plt.title('Resaved PNG Image')
plt.show()
# 尝试使用 OpenCV 读取重新保存的图像（JPG 格式）
new_img_jpg = cv2.imread(new_jpg_path, cv2.IMREAD_GRAYSCALE)
if new_img_jpg is None:
print(f"Failed to load resaved JPG image using OpenCV: {new_jpg_path}")
else:
print(f"Successfully loaded resaved JPG image using OpenCV: {new_jpg_path}")
# 使用 Matplotlib 显示图像
plt.imshow(new_img_jpg, cmap='gray')
plt.title('Resaved JPG Image')
plt.show()