Difference between matplotlib.pyplot and Open3D point clouds visualization in Z-axis

[hrimov]

Checklist

• I have searched for similar issues.
• For Python issues, I have tested with the latest development wheel.
• I have checked the release documentation and the latest documentation (for main branch).

My Question

I have a question why the two libraries produce the different image of the same point cloud. The difference is in the Z-axis visualization — points (in the example below lines) have different distance, but the dataset is the same.

I can understand it, because X and Y coordinates are much lower, than for Z (file attached). So, my question is how to achieve the same picture in the Open3D — maybe you already have some generic solution for it? I just figured out how to make it manually, reducing the Z-coordinate multiplying it (commented line of code in the MRE).

import matplotlib.pyplot as plt
import numpy as np
import open3d as o3d


pc_matrix = np.genfromtxt("matrix8-10.csv", delimiter=",")

# Matplotlib
x, y, z = pc_matrix[:, 0], pc_matrix[:, 1], pc_matrix[:, 2]
fig = plt.figure(figsize=(8, 8))
ax = fig.add_subplot(111, projection="3d")
ax.scatter(x, y, z)
plt.show()


# Open3D
pcd = o3d.geometry.PointCloud()

# this reduces all the values of Z-axis (uncomment this line for see the desired picture)
# pc_matrix = [[point[0], point[1], point[2] * 0.3] for point in pc_matrix]

pcd.points = o3d.utility.Vector3dVector(pc_matrix)
pcd.colors = o3d.utility.Vector3dVector([[0, 0, 255] for point in pc_matrix])

visualizer = o3d.visualization.Visualizer()
visualizer.create_window()
visualizer.add_geometry(pcd)
render_option = visualizer.get_render_option()
render_option.background_color = [0, 0, 0]
visualizer.run()

So, this code produce following visualizations:

But, the desired image in Open3D is:

The dataset I used for the visualization:
matrix8-10.csv