fix(core): 修复模板匹配中的 threshold 值被错误地传入到了 hist_match 函数

kotonebot/backend/context.py

@@ -383,7 +383,7 @@ class Context:
     def __init__(self):
         # HACK: 暂时写死
         from adbutils import adb
-        adb.connect('127.0.0.1:16384')
+        adb.connect('127.0.0.1:5555')
         self.__device = AdbDevice(adb.device_list()[0])
         # self.__device = None
         self.__ocr = ContextOcr(self)

kotonebot/backend/image.py

@@ -190,7 +190,7 @@ def template_match(
                 img1 = cv2.bitwise_and(img1, img1, mask=mask)
                 img2 = cv2.bitwise_and(img2, img2, mask=mask)
 
-            if not hist_match(img1, img2, (0, 0, w, h), threshold):
+            if not hist_match(img1, img2, (0, 0, w, h)):
                 continue
         
         matches.append(TemplateMatchResult(
@@ -208,8 +208,8 @@ def template_match(
 def hist_match(
     image: MatLike | str,
     template: MatLike | str,
-    rect: Rect,
-    threshold: float = 0.8,
+    rect: Rect | None = None,
+    threshold: float = 0.9,
 ) -> bool:
     """
     对输入图像的矩形部分与模板进行颜色直方图匹配。
@@ -219,7 +219,7 @@ def hist_match(
 
     :param image: 输入图像
     :param template: 模板图像
-    :param rect: 待匹配的矩形区域
+    :param rect: 输入图像中待匹配的矩形区域
     :param threshold: 相似度阈值，默认为 0.8
     :return: 是否匹配成功
     """
@@ -228,12 +228,16 @@ def hist_match(
     template = _unify_image(template)
 
     # 从图像中裁剪出矩形区域
-    x, y, w, h = rect
-    roi = image[y:y+h, x:x+w]
+    if rect is None:
+        roi = image
+    else:
+        x, y, w, h = rect
+        roi = image[y:y+h, x:x+w]
 
     # 确保尺寸一致
     if roi.shape != template.shape:
-        roi = cv2.resize(roi, (template.shape[1], template.shape[0]))
+        # roi = cv2.resize(roi, (template.shape[1], template.shape[0]))
+        raise ValueError('Expected two images with the same size.')
 
     # 将图像分为上中下三个区域
     h = roi.shape[0]

tests/core/test_image.py

@@ -0,0 +1,15 @@
+import cv2
+
+from util import BaseTestCase
+from kotonebot.backend.image import *
+
+class TestImage(BaseTestCase):
+    def test_hist_match(self):
+        add_black = cv2.imread('tests/images/template_match/add.png')
+        add_gray = cv2.imread('tests/images/template_match/add_disabled.png')
+        self.assertFalse(hist_match(add_black, add_gray))
+        self.assertTrue(hist_match(add_black, add_black))
+        self.assertTrue(hist_match(add_gray, add_gray))
+
+        with self.assertRaises(ValueError):
+            hist_match(add_black, add_gray, rect=(0, 0, 1, 1))