🚀 Instantly visualize 3D point clouds from your Python debugger in VS Code!
This extension enhances your debugging workflow by allowing you to preview point cloud variables as .ply files directly from the editor. It supports native Open3D point clouds, NumPy arrays, and PyTorch tensors.
See it on the VS Marketplace: Python PLY Preview
- Set a breakpoint in your Python code.
- Start your program in Debug Mode (F5).
- When execution pauses, hover your cursor over a point cloud variable.
- In the hover menu, select View PLY.
- The point cloud will be rendered in a new editor tab.
To test all features, you can use the following Python script. Place a breakpoint on the final print statement and inspect each of the defined variables.
import open3d as o3d
import numpy as np
import torch
# 1. Create a basic NumPy array with XYZ points
points_np = np.random.rand(1000, 3)
# 2. Create a NumPy array with XYZ points and RGB colors
# Points are a spiral, colors transition from red to blue
z = np.linspace(0, 10, 1000)
x = np.sin(z) * 5
y = np.cos(z) * 5
points_spiral = np.vstack((x, y, z)).T
colors_gradient = np.zeros_like(points_spiral)
colors_gradient[:, 0] = np.linspace(0, 1, 1000) # Red channel
colors_gradient[:, 2] = np.linspace(1, 0, 1000) # Blue channel
points_and_colors_np = np.hstack((points_spiral, colors_gradient))
# 3. Create PyTorch Tensors from the NumPy arrays
points_torch = torch.from_numpy(points_np)
points_and_colors_torch = torch.from_numpy(points_and_colors_np)
# 4. Create a native Open3D PointCloud object
pcd_o3d = o3d.geometry.PointCloud()
pcd_o3d.points = o3d.utility.Vector3dVector(points_np)
pcd_o3d.paint_uniform_color([0.5, 0.5, 0.5]) # Gray color
# Set a breakpoint on the line below and hover over the variables to test
print("Breakpoint here: Hover over variables to preview them as PLY.")The extension leverages Open3D to save the point cloud data. It handles imports automatically, so you don't need to import open3d in your script.
However, the libraries must be installed in your Python environment:
- open3d: Mandatory for all operations.
- numpy: Required for NumPy visualization.
- torch: Required for PyTorch visualization.
You can install these packages using pip:
pip install open3d numpy torch
- Open3D: Native
o3d.geometry.PointCloudobjects. - NumPy:
np.ndarraywith shape(n, 3)for XYZ points or(n, 6)for XYZ + RGB points. - PyTorch:
torch.Tensorwith shape(n, 3)for XYZ points or(n, 6)for XYZ + RGB points.
This extension handles the saving of the point cloud. You need another extension to view the resulting .ply file. We recommend:
- Performance may degrade with a very large number of points (tested up to ~500,000 points).
- Replaced heavy Open3D dependency with pure NumPy and Python file I/O for array saving.
- Fixed a critical bug causing timeouts (
Cannot evaluate expression) on macOS due to slow library loading. - Improved robustness across different Python versions.
- Modified README.md to include Visual Studio Marketplace badges.
- Removed the requirement to import
open3din the user script beforehand. - Added automatic library check (Open3D, NumPy, PyTorch) and user notification if missing.
- Modified README.md to include Visual Studio Marketplace badges.
- Added support for PyTorch Tensors and NumPy arrays with color
(n, 6). - Changed temporary file location to
.vscode/ply_preview. - Implemented automatic cleanup of temporary files after a debug session.
- Improved logic to avoid activating on variables in comments or strings.
- The
__pycache__folder is now created if it doesn't exist.
- Fixed extension description and name.
- Added marketplace badges to the README.
- Initial release.
This project was inspired by the fantastic work of other developer tool extensions: