fix: error when recognize training

fix #156

auto_derby/single_mode/training.py

@@ -50,7 +50,11 @@ def _ocr_training_effect(img: Image) -> int:
     )
     sharpened_img = imagetools.mix(sharpened_img, cv_img, 0.5)
 
-    white_outline_img = imagetools.constant_color_key(sharpened_img, (255, 255, 255))
+    white_outline_img = imagetools.constant_color_key(
+        sharpened_img,
+        (255, 255, 255),
+        (234, 245, 240),
+    )
     white_outline_img = cv2.dilate(
         white_outline_img,
         cv2.getStructuringElement(
@@ -70,6 +74,7 @@ def _ocr_training_effect(img: Image) -> int:
         (30, 109, 216),
         (69, 104, 197),
         (119, 139, 224),
+        (103, 147, 223),
     )
 
     bg_mask_img = imagetools.bg_mask_by_outline(brown_outline_img)
@@ -91,7 +96,7 @@ def _ocr_training_effect(img: Image) -> int:
     assert fill_img.shape == cv_img.shape
 
     text_img = imagetools.color_key(masked_img, fill_img)
-    imagetools.fill_area(text_img, (0,), size_lt=4)
+    imagetools.fill_area(text_img, (0,), size_lt=8)
 
     text_img_extra = imagetools.constant_color_key(
         masked_img, (175, 214, 255), threshold=0.95

auto_derby/single_mode/training_test.py

@@ -310,6 +310,31 @@ def test_update_by_training_scene_issue130():
     assert partner1.has_hint == False
 
 
+def test_update_by_training_scene_issue156():
+    with _test.screenshot("training_scene_issue156.png") as img:
+        training = Training.from_training_scene(img)
+    assert training.type == training.TYPE_SPEED
+    assert training.level == 1
+    assert training.speed == 21
+    assert training.stamina == 0
+    assert training.power == 13
+    assert training.guts == 0
+    assert training.wisdom == 0
+    assert training.skill == 4
+
+    assert len(training.partners) == 3, len(training.partners)
+    partner1, partner2, partner3 = training.partners
+    assert partner1.type == Partner.TYPE_POWER
+    assert partner1.level == 2
+    assert partner1.has_hint == False
+    assert partner2.type == Partner.TYPE_SPEED
+    assert partner2.level == 4
+    assert partner2.has_hint == False
+    assert partner3.type == Partner.TYPE_STAMINA
+    assert partner3.level == 4
+    assert partner3.has_hint == False
+
+
 def benchmark_from_training_scene():
     RUN_COUNT = 10
     img = PIL.Image.open(_TEST_DATA_PATH / "training_scene_5.png").convert("RGB")