feat: support nonuniform stamp matching

match_stamp.py

@@ -34,6 +34,7 @@ TOP_N = 5
 SCALE_MIN = 0.10
 SCALE_MAX = 2.00
 SCALE_STEP = 0.05
+ASPECT_Y_FACTORS = (0.60, 0.70, 0.80, 0.90, 1.00, 1.10, 1.20)
 
 ALPHA_THRESHOLD = 20
 LOW_SCORE_WARNING_THRESHOLD = 0.55
@@ -96,6 +97,27 @@ def build_scales():
     return scales
 
 
+def build_scale_variants():
+    variants = []
+    seen = set()
+    for scale in build_scales():
+        for aspect_y in ASPECT_Y_FACTORS:
+            scale_x = scale
+            scale_y = round(scale * aspect_y, 4)
+            key = (scale_x, scale_y, aspect_y)
+            if key in seen:
+                continue
+            seen.add(key)
+            variants.append(
+                {
+                    "scale_x": scale_x,
+                    "scale_y": scale_y,
+                    "aspect_y": aspect_y,
+                }
+            )
+    return variants
+
+
 def safe_match_template(source, template, mask=None):
     if template.shape[0] > source.shape[0] or template.shape[1] > source.shape[1]:
         return None
@@ -119,25 +141,28 @@ def safe_match_template(source, template, mask=None):
     return np.clip(result, 0.0, 1.0)
 
 
-def resize_for_scale(image, scale, interpolation):
+def resize_for_scale(image, scale_x, scale_y, interpolation):
     height, width = image.shape[:2]
-    new_width = max(1, int(round(width * scale)))
+    new_width = max(1, int(round(width * scale_x)))
-    new_height = max(1, int(round(height * scale)))
+    new_height = max(1, int(round(height * scale_y)))
     return cv2.resize(image, (new_width, new_height), interpolation=interpolation)
 
 
-def score_stamp(merged_rgb, merged_edges, stamp_path, scales):
+def score_stamp(merged_rgb, merged_edges, stamp_path, scale_variants):
     stamp_rgba = load_rgba(stamp_path)
     stamp_rgb, stamp_mask = crop_transparent_border(stamp_rgba)
     stamp_gray = cv2.cvtColor(stamp_rgb, cv2.COLOR_RGB2GRAY)
     stamp_edges = cv2.Canny(stamp_gray, 80, 160)
 
     best = None
-    for scale in scales:
+    for variant in scale_variants:
-        scaled_rgb = resize_for_scale(stamp_rgb, scale, cv2.INTER_AREA)
+        scale_x = variant["scale_x"]
-        scaled_gray = resize_for_scale(stamp_gray, scale, cv2.INTER_AREA)
+        scale_y = variant["scale_y"]
-        scaled_edges = resize_for_scale(stamp_edges, scale, cv2.INTER_NEAREST)
+        aspect_y = variant["aspect_y"]
-        scaled_mask = resize_for_scale(stamp_mask, scale, cv2.INTER_NEAREST)
+        scaled_rgb = resize_for_scale(stamp_rgb, scale_x, scale_y, cv2.INTER_AREA)
+        scaled_gray = resize_for_scale(stamp_gray, scale_x, scale_y, cv2.INTER_AREA)
+        scaled_edges = resize_for_scale(stamp_edges, scale_x, scale_y, cv2.INTER_NEAREST)
+        scaled_mask = resize_for_scale(stamp_mask, scale_x, scale_y, cv2.INTER_NEAREST)
 
         template_result = safe_match_template(merged_rgb, scaled_rgb, scaled_mask)
         if template_result is None:
@@ -165,7 +190,9 @@ def score_stamp(merged_rgb, merged_edges, stamp_path, scales):
                 "stamp_path": stamp_path,
                 "x": int(x),
                 "y": int(y),
-                "scale": float(scale),
+                "scale_x": float(scale_x),
+                "scale_y": float(scale_y),
+                "aspect_y": float(aspect_y),
                 "width": int(scaled_gray.shape[1]),
                 "height": int(scaled_gray.shape[0]),
             }
@@ -178,12 +205,12 @@ def find_best_matches(merged_image, stamp_dir, top_n):
     merged_rgb = rgba_to_rgb(merged_rgba)
     merged_gray = rgba_to_gray(merged_rgba)
     merged_edges = cv2.Canny(merged_gray, 80, 160)
-    scales = build_scales()
+    scale_variants = build_scale_variants()
 
     results = []
     for stamp_path in iter_images(stamp_dir):
         try:
-            result = score_stamp(merged_rgb, merged_edges, stamp_path, scales)
+            result = score_stamp(merged_rgb, merged_edges, stamp_path, scale_variants)
         except Exception as exc:
             print("Skipped: {} ({})".format(stamp_path, exc))
             continue
@@ -211,7 +238,9 @@ def print_result(results, matched_count, merged_image, stamp_dir):
     print("edge_score: {:.4f}".format(best["edge_score"]))
     print("stamp: {}".format(Path(best["stamp_path"]).resolve()))
     print("location: x={}, y={}".format(best["x"], best["y"]))
-    print("scale: {:.4f}".format(best["scale"]))
+    print("scale_x: {:.4f}".format(best["scale_x"]))
+    print("scale_y: {:.4f}".format(best["scale_y"]))
+    print("aspect_y: {:.4f}".format(best["aspect_y"]))
     print("size: {}x{}".format(best["width"], best["height"]))
     if best["score"] < LOW_SCORE_WARNING_THRESHOLD:
         print("warning: best score is low; please review manually.")
@@ -219,14 +248,19 @@ def print_result(results, matched_count, merged_image, stamp_dir):
     print("")
     print("Top {}:".format(len(results)))
     for index, item in enumerate(results, 1):
+        line = (
+            "{}. {:.4f}  template={:.4f}  edge={:.4f}  "
+            "scale_x={:.4f}  scale_y={:.4f}  aspect_y={:.4f}  {}"
+        )
         print(
-            "{}. {:.4f}  template={:.4f}  edge={:.4f}  scale={:.4f}  {}"
+            line.format(
-            .format(
                 index,
                 item["score"],
                 item["template_score"],
                 item["edge_score"],
-                item["scale"],
+                item["scale_x"],
+                item["scale_y"],
+                item["aspect_y"],
                 Path(item["stamp_path"]).name,
             )
         )

tasks.md

@@ -1606,3 +1606,23 @@
 - [x] 明确 `1000x1000 -> 1000x800` 可由 `scale_x=1.00`、`scale_y=0.80`、`aspect_y=0.80` 覆盖
 - [x] 更新输出字段建议：从单一 `scale` 改为 `scale_x`、`scale_y`、`aspect_y`
 - [x] 验证：文档路径、标题、示例和验收点检查通过
+
+### 19.34 独立脚本：支持宽高不等比例印花匹配 — `match_stamp.py`
+
+前置阅读：
+
+- `docs/12-stamp-template-matching.md`
+- `match_stamp.py`
+
+背景：
+
+§19.33 已明确实际合成时印花可能被非等比例缩放，例如原始 `1000x1000` 合成后变成 `1000x800`。`match_stamp.py` 需要按文档把单一 `scale` 搜索扩展为基础 `scale` 加有限 `aspect_y` 候选，提升这类场景的匹配稳定性。
+
+任务：
+
+- [x] 新增 `ASPECT_Y_FACTORS = 0.60 / 0.70 / 0.80 / 0.90 / 1.00 / 1.10 / 1.20`
+- [x] 将缩放搜索从单一 `scale` 改为 `scale_x=scale`、`scale_y=scale*aspect_y`
+- [x] RGB 模板、边缘模板和 alpha mask 使用同一组 `scale_x / scale_y` 缩放
+- [x] 最佳结果保存并打印 `scale_x`、`scale_y`、`aspect_y`，不再只打印单一 `scale`
+- [x] 保持独立脚本约束：不引用项目代码、不写 CSV、不修改图片
+- [x] 验证：`python -m py_compile match_stamp.py` 通过；临时构造 `100x100 -> 100x80` 非等比例样本，Top 1 命中正确印花且输出 `aspect_y=0.8000`