Wavefront-for-selection

Allows you to transform wavefront files into a format that allows texture selection.

What is?

This code allows you to read a wavefront (.obj). For each mesh of stitches in different groups (separated by name or color), the group will receive a numerical identifier. The original mesh color or the vertex will be reconstructed to match this new identifier.

Usage

Command-line interface - CLI

Open the terminal and type:

python wavefrontForSelection.py <file>

For more advanced options see the commands with details below :

python wavefrontForSelection.py -i <file> -o <output_file> -ii <number> [-ij] -m <mode> -t <type> [-en]

Flag	Description	Required
-i, --input	Path to original file.	✅ Yes
-o, --output	Path to resulting file.	No, default ''
-ii, --initial_index	Initial Index for ID generation.	No, default 1
-ij, --ignore-json	Skip creating a JSON with the Ids and their original names.	No
-m, --mode	ID generation strategy, informs whether the identifier should be placed on the texture, vertex, texture coordinate or normal. Accepted arguments: 'Texture', 'Vertex', 'TextureCoordinates' and 'Normal'. (default: 'Texture')	No, default Texture
-t, --type	Type of Indexing that must be created. Accepted arguments: 'Uint8', 'Binary16' and 'Float32'.	No, default Uint8
-en, --ensure-normalization	Ensures output is normalized. Applies to identifier generation in 'Normal'. The x-axis is used to ensure its use and should be discarded.	No
-h, --help	Display help for command.	No

Python Import

You can import the library as a Python class:

from wavefrontForSelection import WavefrontForSelection

Remember to remove hyphens from the folder if necessary.

The method "perform" offers the same functionality displayed in the CLI:

WavefrontForSelection.perform(file, result_path="",initial_index=1,save_dictionary_json=True, mode="Texture", type="Uint8", ensureNormalization = False)

The method will return two outputs: A path to the OBJ file and another to the JSON with the identifiers

result_file, result_json = WavefrontForSelection.perform(file)

If the method receives "save_dictionary_json" as false, the method will return two different outputs: A path to the OBJ file and a dictionary of identifiers and names

result_file, dictionary_ids = WavefrontForSelection.perform(file)

Issues

Feel free to submit issues and enhancement requests.

Contribution

1. Fork the project
2. Create a branch for your modification (git checkout -b my-new-resource)
3. Do the commit (git commit -am 'Adding a new resource...')
4. Push (git push origin my-new-resource)
5. Create a new Pull Request