| import numpy as np |
| import matplotlib as mpl |
| import matplotlib.pyplot as plt |
| from matplotlib.patches import Patch |
| from mpl_toolkits.mplot3d.art3d import Poly3DCollection |
|
|
| class CameraPoseVisualizer: |
| def __init__(self, xlim=[-1, 1], ylim=[-1, 1], zlim=[-10, 0], view_mode='none'): |
| self.xlim = xlim |
| self.ylim = ylim |
| self.zlim = zlim |
| self.view_mode = view_mode |
| self.fig = plt.figure(figsize=(5.12, 5.12)) |
| self.ax = self.fig.add_subplot(projection = '3d') |
|
|
| |
| |
| if view_mode == 'xz': |
| self.ax.view_init(elev=0, azim=-90, roll=0) |
| elif view_mode == 'xy': |
| self.ax.view_init(elev=90, azim=-90, roll=0) |
|
|
| self.ax.set_aspect("auto") |
| self.ax.set_xlim(xlim) |
| self.ax.set_ylim(ylim) |
| self.ax.set_zlim(zlim) |
| self.ax.set_xlabel('x') |
| self.ax.set_ylabel('y') |
| self.ax.set_zlabel('z') |
|
|
| def extrinsic2pyramid(self, extrinsic, color='r', focal_len_scaled=0.5, aspect_ratio=0.15): |
| |
| |
| self.reset(self.xlim, self.ylim, self.zlim, self.view_mode) |
| vertex_std = np.array([[0, 0, 0, 1], |
| [focal_len_scaled * aspect_ratio, -focal_len_scaled * aspect_ratio, focal_len_scaled, 1], |
| [focal_len_scaled * aspect_ratio, focal_len_scaled * aspect_ratio, focal_len_scaled, 1], |
| [-focal_len_scaled * aspect_ratio, focal_len_scaled * aspect_ratio, focal_len_scaled, 1], |
| [-focal_len_scaled * aspect_ratio, -focal_len_scaled * aspect_ratio, focal_len_scaled, 1]]) |
| vertex_transformed = vertex_std @ extrinsic.T |
| meshes = [ |
| [vertex_transformed[0, :-1], vertex_transformed[1][:-1], vertex_transformed[2, :-1]], |
| [vertex_transformed[0, :-1], vertex_transformed[2, :-1], vertex_transformed[3, :-1]], |
| [vertex_transformed[0, :-1], vertex_transformed[3, :-1], vertex_transformed[4, :-1]], |
| [vertex_transformed[0, :-1], vertex_transformed[4, :-1], vertex_transformed[1, :-1]], |
| [vertex_transformed[1, :-1], vertex_transformed[2, :-1], vertex_transformed[3, :-1], vertex_transformed[4, :-1]] |
| ] |
| self.ax.add_collection3d( |
| |
| Poly3DCollection(meshes, facecolors=color, linewidths=0.3, edgecolors=color, alpha=0.35)) |
| |
| canvas = self.fig.canvas |
| canvas.draw() |
| width, height = canvas.get_width_height() |
| image_array = np.frombuffer(canvas.tostring_rgb(), dtype='uint8') |
| image_array = image_array.reshape(height, width, 3) |
| return image_array |
| |
| def customize_legend(self, list_label): |
| list_handle = [] |
| for idx, label in enumerate(list_label): |
| color = plt.cm.rainbow(idx / len(list_label)) |
| patch = Patch(color=color, label=label) |
| list_handle.append(patch) |
| plt.legend(loc='right', bbox_to_anchor=(1.8, 0.5), handles=list_handle) |
|
|
| def colorbar(self, max_frame_length): |
| cmap = mpl.cm.rainbow |
| norm = mpl.colors.Normalize(vmin=0, vmax=max_frame_length) |
| self.fig.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=cmap), orientation='vertical', label='Frame Number') |
|
|
| def show(self): |
| plt.title('Extrinsic Parameters') |
| plt.show() |
| |
| def reset(self, xlim=[-50, 50], ylim=[-50, 50], zlim=[0, 50], view_mode='none'): |
| self.__init__(xlim, ylim, zlim, view_mode) |