处理优化。

预定系统/Base/app_base.py

@@ -112,85 +112,67 @@ def compare_brightness(light_down_path, light_on_path, threshold=1):
 import cv2
 import numpy as np
 
+import logging
+from PIL import Image
+import numpy as np
+
+# 配置日志
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
 def compare_images_feature_matching(image1_path, image2_path):
-    """
-    使用特征匹配对比两张图片的相似度。
-    """
     try:
-        image1 = cv2.imread(image1_path, cv2.IMREAD_GRAYSCALE)
-        image2 = cv2.imread(image2_path, cv2.IMREAD_GRAYSCALE)
+        # 打开两张图片
+        img1 = Image.open(image1_path)
+        img2 = Image.open(image2_path)
 
-        if image1 is None or image2 is None:
-            logging.error(f"无法读取图像: {image1_path} 或 {image2_path}")
-            return False
+        # 将图片转换为相同的模式和尺寸
+        img1 = img1.convert("RGB")
+        img2 = img2.convert("RGB")
 
-        # 初始化ORB检测器
-        orb = cv2.ORB_create()
+        # 如果尺寸不同，先调整大小
+        if img1.size != img2.size:
+            logging.info("图片尺寸不同，调整为相同尺寸进行比较")
+            img2 = img2.resize(img1.size, Image.ANTIALIAS)  # 保持纵横比
 
-        # 查找关键点和描述符
-        kp1, des1 = orb.detectAndCompute(image1, None)
-        kp2, des2 = orb.detectAndCompute(image2, None)
+        # 转换为 numpy 数组进行比较
+        img1_array = np.array(img1)
+        img2_array = np.array(img2)
 
-        logging.info(f"图像1的关键点数量: {len(kp1)}")
-        logging.info(f"图像2的关键点数量: {len(kp2)}")
+        # 比较两个数组是否相同
+        return np.array_equal(img1_array, img2_array)
 
-        if des1 is None or des2 is None:
-            logging.error("无法检测到描述符")
+    except FileNotFoundError as e:
+        logging.error(f"文件未找到: {e}")
         return False
-
-        # FLANN参数
-        FLANN_INDEX_LSH = 6
-        index_params = dict(algorithm=FLANN_INDEX_LSH, table_number=6, key_size=12, multi_probe_level=1)
-        search_params = dict(checks=50)
-
-        # FLANN匹配器
-        flann = cv2.FlannBasedMatcher(index_params, search_params)
-
-        # 匹配描述符
-        matches = flann.knnMatch(des1, des2, k=2)
-
-        # 使用比率测试过滤匹配
-        good_matches = []
-        for m, n in matches:
-            if m.distance < 0.7 * n.distance:
-                good_matches.append(m)
-
-        # 计算匹配点的数量
-        num_matches = len(good_matches)
-        logging.info(f"匹配点数量: {num_matches}")
-        INFO(f"匹配点数量：{num_matches}")
-
-        if num_matches > 10:
-            INFO("图片相同")
-            return True
-        else:
-            INFO("图片不同")
+    except OSError as e:
+        logging.error(f"图片处理错误: {e}")
         return False
-
-    except Exception as e:
-        logging.error(f"对比图片时发生错误: {e}", exc_info=True)
+    except MemoryError as e:
+        logging.error(f"内存不足: {e}")
         return False
 
 
-if __name__ == '__main__':
-    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
-    logging.info("开始对比图片")
-
-    image1_path = r'D:\GithubData\自动化\ubains-module-test\预定系统\reports\imgs\Exhibit_Inspect\No_PaperLess\同屏后-无纸化设备A界面截屏.png'
-    image2_path = r'D:\GithubData\自动化\ubains-module-test\预定系统\reports\imgs\Exhibit_Inspect\No_PaperLess\同屏后-无纸化设备B界面截屏.png'
 
-    if not os.path.exists(image1_path):
-        logging.error(f"图片 {image1_path} 不存在")
-        exit(1)
-    if not os.path.exists(image2_path):
-        logging.error(f"图片 {image2_path} 不存在")
-        exit(1)
+# if __name__ == '__main__':
+#     logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+#     logging.info("开始对比图片")
+#
+#     image1_path = r'D:\GithubData\自动化\ubains-module-test\预定系统\reports\imgs\Exhibit_Inspect\No_PaperLess\DeviceA-ShareScreen.png'
+#     image2_path = r'D:\GithubData\自动化\ubains-module-test\预定系统\reports\imgs\Exhibit_Inspect\No_PaperLess\DeviceB-ShareScreen.png'
+#
+#     if not os.path.exists(image1_path):
+#         logging.error(f"图片 {image1_path} 不存在")
+#         exit(1)
+#     if not os.path.exists(image2_path):
+#         logging.error(f"图片 {image2_path} 不存在")
+#         exit(1)
+#
+#     # 对比两张截图的相似度
+#     if compare_images_feature_matching(image1_path, image2_path):
+#         logging.info("图片相同")
+#     else:
+#         logging.error("图片不同")
 
-    # 对比两张截图的相似度
-    if compare_images_feature_matching(image1_path, image2_path):
-        logging.info("图片相同")
-    else:
-        logging.error("图片不同")
 
 import cv2
 import logging

预定系统/README.md

@@ -211,4 +211,4 @@
    - 增加get_test_result函数通过正则匹配获取通过率、失败率以及异常率，再调用钉钉消息通知输出通过率等值。优化处理。
 54. 2025-02-14
    - 补充讯飞语音转录功能流程，调试通过。
-   - 补充实现无纸化同屏巡检流程，但是还存在图片匹配失败问题。
+   - 补充实现无纸化同屏巡检流程，但是还存在图片匹配失败问题。处理优化。
\ No newline at end of file

预定系统/cases/展厅巡检/03无纸化/01无纸化同屏测试.py

@@ -84,8 +84,8 @@ class same_screen_share_001:
 
             # 调用图片对比函数判断相似度
             match_text = compare_images_feature_matching(
-                r"D:\GithubData\自动化\ubains-module-test\预定系统\reports\imgs\Exhibit_Inspect\No_PaperLess\同屏后-无纸化设备A界面截屏.png",
-                r"D:\GithubData\自动化\ubains-module-test\预定系统\reports\imgs\Exhibit_Inspect\No_PaperLess\同屏后-无纸化设备B界面截屏.png")
+                r"/预定系统/reports/imgs/Exhibit_Inspect/No_PaperLess/DeviceA-ShareScreen.png",
+                r"/预定系统/reports/imgs/Exhibit_Inspect/No_PaperLess/DeviceB-ShareScreen.png")
             INFO(f"图片相似度：{match_text}")
             CHECK_POINT("校验同屏功能是否成功", match_text == True)