feat: 초기 프로젝트 구조 추가

ai/detector.py

@@ -0,0 +1,59 @@
+# AI 추론 — YOLOv8 기반 불량(스크래치/이물/흑점/변형) 검출
+import os
+import numpy as np
+
+from utils.path_helper import BASE_PATH
+
+
+class Detector:
+    class_names = ["스크래치", "이물", "흑점", "변형"]
+
+    def __init__(self):
+        self._model     = None
+        self.model_path = None
+
+    def load_model(self, model_path: str) -> bool:
+        if model_path and not os.path.isabs(model_path):
+            model_path = os.path.join(BASE_PATH, model_path)
+        try:
+            from ultralytics import YOLO  # 지연 로딩 — 앱 시작 시 torch DLL 오류 방지
+            self._model     = YOLO(model_path)
+            self.model_path = model_path
+            print(f"[AI] 모델 로드 성공: {model_path}")
+            return True
+        except Exception as e:
+            print(f"[AI] 모델 로드 실패: {e}")
+            self._model = None
+            return False
+
+    def is_loaded(self) -> bool:
+        return self._model is not None
+
+    def detect(self, image: np.ndarray) -> list:
+        """
+        image: numpy array (BGR)
+        반환: [{"class_id": int, "class_name": str,
+                "confidence": float, "bbox": [x1,y1,x2,y2]}, ...]
+        """
+        if self._model is None:
+            return []
+        try:
+            results = self._model(image, verbose=False)
+            detections = []
+            for result in results:
+                for box in result.boxes:
+                    class_id = int(box.cls[0])
+                    detections.append({
+                        "class_id":   class_id,
+                        "class_name": (
+                            self.class_names[class_id]
+                            if class_id < len(self.class_names)
+                            else str(class_id)
+                        ),
+                        "confidence": float(box.conf[0]),
+                        "bbox":       box.xyxy[0].tolist(),
+                    })
+            return detections
+        except Exception as e:
+            print(f"[AI] 추론 오류: {e}")
+            return []