Release/v0.1.1

README.ja.md

@@ -21,7 +21,12 @@ v0.1.0を公開済みです。
 
 - PySide6によるデスクトップGUI
 - JSONによるルール保存・読み込み
+- `rules/*.json` によるルールセット作成・切り替え
 - ルールの追加・編集・削除
+- ルールの複製・並び替え
+- ルール一覧での最終状態・スコア表示
+- 検知画像プレビュー
+- スクリーンショットからの検知画像切り出し
 - 画面上での探索範囲選択
 - 検知画像上でのクリック位置指定
 - マルチディスプレイ対応
@@ -145,7 +150,9 @@ GitHub Releasesでは、Windows向けzipを配布しています。
 8. ルールを保存する。
 9. `Test Detection`でクリックなしの検知確認を行う。
 10. `Start`で実行する。
-11. `Stop`で停止する。
+11. `Stop`または`Esc`で停止する。
+
+メイン画面上部の`Rule Set`からルールセットを切り替えられます。`New`で空のルールセットを`rules`フォルダ内に作成できます。
 
 ## ルール例
 

README.md

@@ -21,7 +21,12 @@ Current implementation includes:
 
 - PySide6 desktop GUI
 - JSON rule loading and saving
+- Rule set creation and switching from `rules/*.json`
 - Rule add, edit, and delete
+- Rule duplication and reordering
+- Last status and score display in the rule list
+- Detection image preview
+- Detection image capture from screenshots
 - Screen region selection
 - Click position selection on the template image
 - Multi-monitor region support
@@ -149,7 +154,9 @@ GitHub Releases can be created from tags such as `v0.1.0-alpha.1`. The release w
 8. Save the rule.
 9. Use `Test Detection` to verify matching without clicking.
 10. Click `Start` to run the macro loop.
-11. Click `Stop` to stop execution.
+11. Click `Stop` or press `Esc` to stop execution.
+
+Use the `Rule Set` dropdown in the main window to switch rule sets. Click `New` to create an empty rule set under the `rules` directory.
 
 ## Rule Example
 

app/detector.py

@@ -48,6 +48,14 @@ def __init__(self, base_dir: str | Path = ".") -> None:
 
     def detect(self, screenshot: np.ndarray, rule: Rule) -> MatchResult | None:
         """Return the best match when it meets the rule confidence."""
+        match = self.find_best_match(screenshot, rule)
+        if match is None or match.score < rule.confidence:
+            return None
+
+        return match
+
+    def find_best_match(self, screenshot: np.ndarray, rule: Rule) -> MatchResult | None:
+        """Return the best match even when it is below the rule confidence."""
         origin_x = 0
         origin_y = 0
         if isinstance(screenshot, CapturedScreenshot):
@@ -67,9 +75,6 @@ def detect(self, screenshot: np.ndarray, rule: Rule) -> MatchResult | None:
         result = self._match_template(region_image, template)
         _, max_score, _, max_location = cv2.minMaxLoc(result)
 
-        if max_score < rule.confidence:
-            return None
-
         match_x = rule.region.x + max_location[0]
         match_y = rule.region.y + max_location[1]
         return MatchResult(

app/rule_operations.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+from dataclasses import replace
 from pathlib import Path
 
 from app.models import Rule, RuleSet
@@ -36,6 +37,59 @@ def remove_rule(rule_set: RuleSet, index: int) -> RuleSet:
     return RuleSet(version=rule_set.version, rules=rules)
 
 
+def duplicate_rule(rule_set: RuleSet, index: int) -> RuleSet:
+    """Return a new RuleSet with the selected rule copied after itself."""
+    if index < 0 or index >= len(rule_set.rules):
+        raise RuleOperationError("rule index is out of range")
+
+    rules = list(rule_set.rules)
+    original = rules[index]
+    duplicated = replace(
+        original,
+        name=_copy_rule_name(original.name, {rule.name for rule in rules}),
+    )
+    rules.insert(index + 1, duplicated)
+    return RuleSet(version=rule_set.version, rules=rules)
+
+
+def move_rule(rule_set: RuleSet, index: int, target_index: int) -> RuleSet:
+    """Return a new RuleSet with one rule moved to target_index."""
+    if index < 0 or index >= len(rule_set.rules):
+        raise RuleOperationError("rule index is out of range")
+    if target_index < 0 or target_index >= len(rule_set.rules):
+        raise RuleOperationError("target rule index is out of range")
+
+    rules = list(rule_set.rules)
+    rule = rules.pop(index)
+    rules.insert(target_index, rule)
+    return RuleSet(version=rule_set.version, rules=rules)
+
+
+def reorder_rules(rule_set: RuleSet, order: list[int]) -> RuleSet:
+    """Return a new RuleSet reordered by a list of original indices."""
+    if len(order) != len(rule_set.rules):
+        raise RuleOperationError("rule order length does not match rule count")
+    if sorted(order) != list(range(len(rule_set.rules))):
+        raise RuleOperationError("rule order must contain each rule index exactly once")
+
+    return RuleSet(
+        version=rule_set.version,
+        rules=[rule_set.rules[index] for index in order],
+    )
+
+
+def _copy_rule_name(name: str, existing_names: set[str]) -> str:
+    base_name = f"{name} copy"
+    if base_name not in existing_names:
+        return base_name
+
+    suffix = 2
+    while f"{base_name} {suffix}" in existing_names:
+        suffix += 1
+
+    return f"{base_name} {suffix}"
+
+
 def make_image_path_relative(rule: Rule, base_dir: str | Path) -> Rule:
     """Return a copy of rule with image path relative to base_dir when possible."""
     image_path = Path(rule.image)

app/runner.py

@@ -33,6 +33,7 @@ class RuleRunResult:
     matched: bool = False
     triggered: bool = False
     skipped_cooldown: bool = False
+    score: float | None = None
     match: MatchResult | None = None
     click_target: ClickTarget | None = None
     error: str | None = None
@@ -108,7 +109,7 @@ def test_once(self, screenshot: Any) -> RunnerCycleResult:
                 continue
 
             try:
-                match = self.detector.detect(screenshot, rule)
+                match = self._find_best_match_for_test(screenshot, rule)
             except DetectionError as error:
                 results.append(
                     RuleRunResult(
@@ -120,11 +121,19 @@ def test_once(self, screenshot: Any) -> RunnerCycleResult:
 
             if match is None:
                 results.append(RuleRunResult(rule_name=rule.name))
+            elif match.score < rule.confidence:
+                results.append(
+                    RuleRunResult(
+                        rule_name=rule.name,
+                        score=match.score,
+                    )
+                )
             else:
                 results.append(
                     RuleRunResult(
                         rule_name=rule.name,
                         matched=True,
+                        score=match.score,
                         match=match,
                     )
                 )
@@ -162,6 +171,7 @@ def run_once(self, screenshot: Any) -> RunnerCycleResult:
                         rule_name=rule.name,
                         matched=True,
                         triggered=True,
+                        score=match.score,
                         match=match,
                         click_target=click_target,
                     )
@@ -190,3 +200,10 @@ def _capture_screenshot(self, screenshot_provider: ScreenshotProvider) -> Any:
             return capture_frame()
 
         return screenshot_provider.capture()
+
+    def _find_best_match_for_test(self, screenshot: Any, rule: Rule) -> MatchResult | None:
+        find_best_match = getattr(self.detector, "find_best_match", None)
+        if callable(find_best_match):
+            return find_best_match(screenshot, rule)
+
+        return self.detector.detect(screenshot, rule)

app/storage.py

@@ -3,6 +3,8 @@
 from __future__ import annotations
 
 import json
+import re
+from dataclasses import dataclass
 from pathlib import Path
 from typing import Any
 
@@ -13,6 +15,67 @@ class RuleStorageError(RuntimeError):
     """Raised when a rule file cannot be loaded or saved."""
 
 
+@dataclass(frozen=True)
+class RuleProfile:
+    title: str
+    path: Path
+
+
+def list_rule_profiles(base_dir: str | Path = ".") -> list[RuleProfile]:
+    """List the root rules.json and rule JSON files from the rules directory."""
+    root_dir = Path(base_dir)
+    profile_paths = []
+
+    legacy_rules_path = root_dir / "rules.json"
+    if legacy_rules_path.is_file():
+        profile_paths.append(legacy_rules_path)
+
+    profiles_dir = root_dir / "rules"
+    if profiles_dir.exists() and profiles_dir.is_dir():
+        profile_paths.extend(
+            path
+            for path in sorted(profiles_dir.glob("*.json"), key=lambda item: item.stem.lower())
+            if path.is_file()
+        )
+
+    return _title_rule_profiles(profile_paths)
+
+
+def _title_rule_profiles(paths: list[Path]) -> list[RuleProfile]:
+    title_counts: dict[str, int] = {}
+    profiles = []
+    for path in paths:
+        base_title = path.stem
+        count = title_counts.get(base_title, 0)
+        title_counts[base_title] = count + 1
+        title = base_title if count == 0 else f"{base_title} ({count})"
+        profiles.append(RuleProfile(title=title, path=path))
+
+    return profiles
+
+
+def safe_rule_profile_stem(name: str) -> str:
+    """Return a filesystem-friendly rule profile filename stem."""
+    stem = re.sub(r"[^0-9A-Za-z_-]+", "_", name.strip()).strip("_")
+    return stem or "rules"
+
+
+def new_rule_profile_path(base_dir: str | Path, name: str) -> Path:
+    """Return a non-existing path for a new rule profile under rules/."""
+    profiles_dir = Path(base_dir) / "rules"
+    stem = safe_rule_profile_stem(name)
+    path = profiles_dir / f"{stem}.json"
+    if not path.exists():
+        return path
+
+    suffix = 1
+    while True:
+        candidate = profiles_dir / f"{stem}_{suffix}.json"
+        if not candidate.exists():
+            return candidate
+        suffix += 1
+
+
 def load_rules(path: str | Path) -> RuleSet:
     """Load a rule set from JSON.