camera_visualisation.py

# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.

import matplotlib.pyplot as plt
import torch
from mpl_toolkits.mplot3d import Axes3D  # noqa: F401 unused import


def get_camera_wireframe(scale: float = 0.3):
    """
    Returns a wireframe of a 3D line-plot of a camera symbol.
    """
    a = 0.5 * torch.tensor([-2, 1.5, 4])
    b = 0.5 * torch.tensor([2, 1.5, 4])
    c = 0.5 * torch.tensor([-2, -1.5, 4])
    d = 0.5 * torch.tensor([2, -1.5, 4])
    C = torch.zeros(3)
    F = torch.tensor([0, 0, 3])
    camera_points = [a, b, d, c, a, C, b, d, C, c, C, F]
    lines = torch.stack([x.float() for x in camera_points]) * scale
    return lines


def plot_cameras(ax, cameras, color: str = "blue"):
    """
    Plots a set of `cameras` objects into the maplotlib axis `ax` with
    color `color`.
    """
    cam_wires_canonical = get_camera_wireframe().cuda()[None]
    cam_trans = cameras.get_world_to_view_transform().inverse()
    cam_wires_trans = cam_trans.transform_points(cam_wires_canonical)
    plot_handles = []
    for wire in cam_wires_trans:
        # the Z and Y axes are flipped intentionally here!
        x_, z_, y_ = wire.detach().cpu().numpy().T.astype(float)
        (h,) = ax.plot(x_, y_, z_, color=color, linewidth=0.3)
        plot_handles.append(h)
    return plot_handles


def plot_camera_scene(cameras, cameras_gt, status: str):
    """
    Plots a set of predicted cameras `cameras` and their corresponding
    ground truth locations `cameras_gt`. The plot is named with
    a string passed inside the `status` argument.
    """
    fig = plt.figure()
    ax = fig.gca(projection="3d")
    ax.clear()
    ax.set_title(status)
    handle_cam = plot_cameras(ax, cameras, color="#FF7D1E")
    handle_cam_gt = plot_cameras(ax, cameras_gt, color="#812CE5")
    plot_radius = 3
    ax.set_xlim3d([-plot_radius, plot_radius])
    ax.set_ylim3d([3 - plot_radius, 3 + plot_radius])
    ax.set_zlim3d([-plot_radius, plot_radius])
    ax.set_xlabel("x")
    ax.set_ylabel("z")
    ax.set_zlabel("y")
    labels_handles = {
        "Estimated cameras": handle_cam[0],
        "GT cameras": handle_cam_gt[0],
    }
    ax.legend(
        labels_handles.values(),
        labels_handles.keys(),
        loc="upper center",
        bbox_to_anchor=(0.5, 0),
    )
    plt.show()
    return fig