def decode_netout(self, netout, anchors, obj_thresh, net_h, net_w):
        grid_h, grid_w = netout.shape[:2]
        nb_box = 3
        # (1): From this line, netout is a numpy array of 4 dimentions
        netout = netout.reshape((grid_h, grid_w, nb_box, -1))  
        nb_class = netout.shape[-1] - 5
        boxes = []
        netout[..., :2] = self._sigmoid(netout[..., :2])
        netout[..., 4:] = self._sigmoid(netout[..., 4:])
        netout[..., 5:] = netout[..., 4][..., np.newaxis] * netout[..., 5:]
        netout[..., 5:] *= netout[..., 5:] > obj_thresh

        for i in range(grid_h * grid_w):
            row = i / grid_w  # small comment: using '//' instead of '/' makes it unnecesary to cast results to int every time in the future (just replace float operation by its int version) 
            col = i % grid_w
            for b in range(nb_box):
                # 4th element is objectness score
                # (2): because of (1), the nextline will let objectness as a single np.float value
                objectness = netout[int(row)][int(col)][b][4]
                # (3): the following line contains the error
                if (objectness.all() <= obj_thresh): continue

             # Do more things
             pass
        return boxes