use properties

official/projects/cots_detector/crown_of_thorns_starfish_detection_pipeline.ipynb

@@ -536,15 +536,19 @@
     "    d.update(kwargs)\n",
     "    return type(self)(**d)\n",
     "\n",
+    "  @property\n",
     "  def center(self)-> Tuple[float, float]:\n",
     "    return ((self.x0+self.x1)/2, (self.y0+self.y1)/2)\n",
     "  \n",
+    "  @property\n",
     "  def width(self) -> float:\n",
     "    return self.x1 - self.x0\n",
     "\n",
+    "  @property\n",
     "  def height(self) -> float:\n",
     "    return self.y1 - self.y0\n",
     "\n",
+    "  @property\n",
     "  def area(self)-> float:\n",
     "    return (self.x1 - self.x0 + 1) * (self.y1 - self.y0 + 1)\n",
     "  \n",
@@ -562,9 +566,9 @@
     "    if intersection is None:\n",
     "      return 0\n",
     "    \n",
-    "    ia = intersection.area()\n",
+    "    ia = intersection.area\n",
     "\n",
-    "    return ia/(self.area() + other.area() - ia)\n",
+    "    return ia/(self.area + other.area - ia)\n",
     "  \n",
     "  def draw(self, image, label=None, color=(0, 140, 255)):\n",
     "    image = np.asarray(image)\n",
@@ -740,9 +744,9 @@
     "    of_params = default_of_params()\n",
     "\n",
     "  bboxes = [det.bbox for det in detections]\n",
-    "  centers = np.float32([[bbox.center() for bbox in bboxes]])\n",
-    "  widths = np.float32([[bbox.width() for bbox in bboxes]])\n",
-    "  heights = np.float32([[bbox.height() for bbox in bboxes]])\n",
+    "  centers = np.float32([[bbox.center for bbox in bboxes]])\n",
+    "  widths = np.float32([[bbox.width for bbox in bboxes]])\n",
+    "  heights = np.float32([[bbox.height for bbox in bboxes]])\n",
     "\n",
     "\n",
     "  new_centers, status, error = cv2.calcOpticalFlowPyrLK(\n",