Method remove_close_points_tensor

data/utils/visual_trace.py:122–149

Removes points from the 2D trajectory that are closer than min_distance apart. Parameters: trajectory (torch.Tensor): A tensor of shape (N, 2) representing N points in 2D space. min_distance (float): The minimum distance threshold for points to be retained.

(self, trajectory, min_distance=2)

        return sampled_ids        
    
    def remove_close_points_tensor(self, trajectory, min_distance=2):
        """
        Removes points from the 2D trajectory that are closer than min_distance apart.

        Parameters:
        trajectory (torch.Tensor): A tensor of shape (N, 2) representing N points in 2D space.
        min_distance (float): The minimum distance threshold for points to be retained.

        Returns:
        torch.Tensor: A filtered tensor of points where consecutive points are at least min_distance apart.
        """
        # Start with the first point
        filtered_trajectory = [trajectory[0]]

        # Iterate through the points
        for i in range(1, trajectory.size(0)):
            prev_point = filtered_trajectory[-1]
            curr_point = trajectory[i]

            # Calculate the Euclidean distance between the previous point and the current point
            distance = torch.norm(curr_point - prev_point)

            # Keep the point if it's at least min_distance apart from the previous one
            if distance >= min_distance:
                filtered_trajectory.append(curr_point)

        # Convert the filtered list back to a tensor
        return torch.stack(filtered_trajectory)