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final_project.py

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+import cv2
+import numpy as np
+from ultralytics import YOLO
+
+# ============================================================
+# Cargar YOLO
+# ============================================================
+
+WEIGHTS_PATH = "yolov8n.pt"   # el modelo que ya te funcionaba
+print(f"[INFO] Cargando modelo YOLO: {WEIGHTS_PATH}")
+
+model = YOLO(WEIGHTS_PATH)
+print("[INFO] Modelo YOLO cargado correctamente.")
+
+
+# ============================================================
+# Preprocesado básico 
+# ============================================================
+
+def preprocess_frame(frame):
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    blur = cv2.GaussianBlur(gray, (5, 5), 0)
+
+    # Detecta cambios bruscos de intensidad (útil para bordes de objetos alargados)
+    sobel = cv2.Sobel(blur, cv2.CV_64F, 1, 1, ksize=3)
+    sobel = cv2.convertScaleAbs(sobel)
+
+    # Filtro de bordes más duro
+    edges = cv2.Canny(blur, 80, 150)
+
+    # Pequeña expansión de bordes
+    kernel = np.ones((3, 3), np.uint8)
+    dilated = cv2.dilate(edges, kernel, iterations=1)
+
+    # Cierra huecos pequeños en formas
+    morph = cv2.morphologyEx(dilated, cv2.MORPH_CLOSE, kernel, iterations=1)
+
+    return gray, sobel, morph
+
+
+# ============================================================
+# Detección usando YOLO
+# ============================================================
+
+def detect_knives(frame):
+    results = model(frame, verbose=False)[0]
+
+    detections = []
+    for box in results.boxes:
+        cls = int(box.cls[0])
+        label = results.names[cls].lower()
+
+        # Verifica si YOLO considera la clase como cuchillo
+        if "knife" in label or "cuchillo" in label:
+            x1, y1, x2, y2 = box.xyxy[0].cpu().numpy()
+            detections.append((int(x1), int(y1), int(x2), int(y2)))
+
+    return detections
+
+
+# ============================================================
+# Lógica principal
+# ============================================================
+
+def main():
+    print("[INFO] Iniciando cámara...")
+    cap = cv2.VideoCapture(0)
+
+    if not cap.isOpened():
+        print("[ERROR] No se pudo abrir la cámara.")
+        return
+
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            print("[ERROR] No se pudo leer el frame.")
+            break
+
+        gray, sobel, morph = preprocess_frame(frame)
+        detections = detect_knives(frame)
+
+        # Dibuja detecciones
+        for (x1, y1, x2, y2) in detections:
+            cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 2)
+            cv2.putText(frame, "KNIFE", (x1, y1 - 10),
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+
+        # Ventana principal
+        cv2.imshow("Detección de Cuchillos (YOLO)", frame)
+
+        # ------- Ventana extra con 2 filtros juntos -------
+        filters = np.hstack((gray, sobel))
+        cv2.imshow("Filtros (Gray | Sobel)", filters)
+
+        # Salir con Q
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+    cap.release()
+    cv2.destroyAllWindows()
+    print("[INFO] Cámara finalizada.")
+
+
+if __name__ == "__main__":
+    main()

weapons_yolo.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a010e4a9a18f9b1ccaffe063334f088d5b64083e4ccd7b9ef2dbc7b183fc2d80
+size 22531960