PyMesh

Python library for mesh conversion and utilities for applying colors to meshes. The library features a convertor capable of handling various mesh formats and converting them as needed. It also includes visualizer classes that allow you to write simple scripts using custom objects without requiring knowledge of underlying libraries. The visualizer application then renders the script using the provided mesh model.

Prerequisites

Make sure you have Python3 installed. You can check by running the following command in your terminal:

Unix

python3 --version

Windows

python --version

Build and launch

Clone the repo.

git clone -b dev https://github.com/kerrambit/PyMesh.git
cd PyMesh

It is recommended to run the application in a virtual environment. Virtual environments provide a isolated environment for each project, preventing dependency conflicts and other problems.

python3 -m venv pymeshve

Activate it by running the activate script inside.

Windows

pymeshve\Scripts\activate

Unix

source pymeshve/bin/activate

You can now install needed dependencies using pip.

pip install -e .

After you are finished the virtual environment, you can deactivate it (you can remove the whole directory also).

deactivate

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Use convert.py CLI application to easily convert different mesh formats.

Windows

python3 .\src\cli-clients\convert.py --input_file_path .\example_data\pumpkin_tall_10k.obj --output_folder_path ./example_data --output_file_format stl --debugging_info true

Unix

python3 ./src/cli-clients/convert.py --input_file_path ./example_data/pumpkin_tall_10k.obj --output_folder_path ./example_data --output_file_format stl --debugging_info true

Use visualize.py CLI application to easily display the mesh. You can write your own script using PyMesh library to e.g. color the mesh.

Windows

python3 .\src\cli-clients\visualize.py --input_mesh_filepath .\example_data\export.stl --input_script_filepath .\example_scripts\script.py --window_title "Pumpkin visualizer"

Unix

python3 ./src/cli-clients/visualize.py --input_mesh_filepath ./example_data/export.stl --input_script_filepath ./example_scripts/script.py --window_title "Pumpkin visualizer"

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Run the tests suites.

python3 -m pytest

Comments

Find the appropriate Python library for conversion of “.obj” file with mesh data to “.stl” file.

• I have chosen Trimesh as the default Python library for this task. However, I tried to make code modular in the sense that any other library can be used. For example, the repository also contains PyMeshLabConvertor class to convert files using PyMeshLab library.
• The code has abtract classes InputMeshFile and OutputMeshFile from which individual format classes can inherit (note: in the current state, the library supports only two types, OBJ and STL files, but there is no issue in adding more - the system enables this with just writing another specified format class). The reason for this hierarchy is that e.g. PyMeshLab enables to specify users more detailed imports/exports arguments other than just filepath, see.

Visualize the obtained “.stl” file with another Python library. Color the mesh such that the object it represents looks as much similar as possible to its real-world counterpart.

• For this part I have chosen PyVista library. It is a Python high-level API to the Visualization Toolkit (VTK). I have created simple wrapper objects around PyVista objects so the user may use only a few classes for a simple visualiztion, which is the aim of Pymesh.

Develop a python CLI application based on your solution, that allows the user to have more control over the process of conversion and visualization.

• This library contains two CLI applications using argparse library. First application convert.py helps with the different file format conversions. The application visualize.py takes a special Python script file and the mesh file. Then it runs the script with the mesh object. Users can write their own simple script using Pymesh library without any need of knowledge of PyVista or other libraries.

Create a publicly available google colab notebook (or alternative) with your solution so that anyone can run the code and obtain the visualization right in the web browser.

• Solution is accesible via GitHub Gist service. Open this link and you can open and run the code inside Google Colab.

Find errors and mistakes related to the task content itself (if any) and suggest possible improvements.

• The only thing is that I am not sure if the attached .obj file could be publicly shared inside the GitHub repository (so the user can run the example script without any problem).

Troubleshooting

• If you have problems on Linux (WSL) with running visualizer.py script with error ImportError: libGL.so.1: cannot open shared object file: No such file or directory, try this command sudo apt-get install libxrender1.