The plugin is completely integrated in Blender. The GUI is designed to be self-explanatory and intuitive and when possible the features are designed to work with one click.
Over 90% of the character is defined with only three sliders that control age (from 18 to 80 y.o.), body mass and body tone. The character is finished with other lab tools for body and face details, poses, skin and eye shaders, animation, poses, proxy, etc.
The software is designed as a laboratory7 in constant evolution and includes both consolidated algorithms as the 3D morphing and experimental technologies, as the fuzzy mathematics used to handle the relations between human parameters, the non-linear interpolation8 used to define the age, mass and tone, the auto-modelling engine based on body proportions and the expert system used to recognize the bones in motion capture skeletons.9
The software is written in Python and works on all the platforms supported by Blender: Windows, macOS and Linux.
All the characters use the same standard skeleton, so the poses and animation can be easily moved from a character to another.
Most of the data distributed in the package is stored using the standard json syntax.
ManuelbastioniLAB is completely open source, released under standard licenses 10 of the Free Software Foundation.
The characters generated with ManuelbastioniLAB are released under the GNU Affero General Public License 3 (as derivative of AGPL'd data, meshes, textures etc.)
ManuelbastionLAB provides two different base meshes for male and female models. Each model respects the fundamental requisites of a professional mesh, as defined by the author:11
The base humans are modelled after accurate studies of anatomy and anthropology. The lab 1.5.0 provides about 470 morphs for each human character, designed to parametrically describe most of the anatomical range in human bodies, faces and expressions. Genitalia are not present.
Concerning ManuelbastionLAB, the word phenotype is intended with the following meaning:
The lab provides three main classes of humans: Caucasian, Asian and Afro. For each class there is a specific set of phenotypes. Each phenotype can be loaded from the library and used as base for a custom character, or mixed with another phenotype. The available phenotypes are:
While the lab is aimed to create realistic 3d human beings based on a scientific description of their parameters, the same technology can be successfully applied to non-human characters, like fantasy creatures.
The version 1.5.0 of the lab supports three variety of anime characters: classic shojo, modern shojo and "realistic style" anime. There are also male and female elves and male dwarf. Each model has a separate set of morphs to create millions of variations.
Concerning the creation of fantasy characters, the lab supports some extra parameters for humans too, like pointed ears, special teeth, etc..
While MakeHuman has similar characteristics to MB-Lab, the former is a stand-alone application and requires export and import to Blender which is not necessary with MB-Lab.1415
The project was discontinued abruptly by Bastioni,16 after release 1.6.1a, which was not compatible with Blender 2.80. Bart Veldhhuzien indicates Bastioni attempted unsuccessfully to raise funds, and then chose to move on, quoting Bastioni as saying: "I’m sorry, I did my best, but I cannot continue the development of the lab. I will use Blender as artist, since Blender and its community are part of my life."; and "I realized that the lab community size is not enough to support a so expensive project".17
In December 2018, a new repository, based on Bastioni's last version (1.6.1a), aiming at Blender 2.80 compatibility, was opened on GitHub with the project name MB-Lab.18
New community based versions are available on GitHub supporting Blender 2.79 and 2.80.1920
"Open Source Character Creation mit MB-LAB". DigitalProduction. July 24, 2019. Archived from the original on July 29, 2019. Retrieved October 28, 2019. https://www.digitalproduction.com/2019/07/24/open-source-character-creation-mit-mb-lab/ ↩
Active in Open Source since 1999. Coauthor of "The Official Blender 2.3 guide, the open 3D creation suite" with chapter "From Blender to YafRay Using YableX". Founder of MakeHuman project, that received in 2004 the Suzanne Award for the best Python script for Blender. He left the MakeHuman project in 2016 /wiki/MakeHuman ↩
Staff (February 2, 2016). "Manuel Bastioni Lab free human models creation tool". CGPress. Archived from the original on November 13, 2016. Retrieved October 28, 2019. https://cgpress.org/archives/manuel-bastioni-lab-free-human-models-creation-tool.html ↩
"MB-Lab GitHub clone". github.com. Retrieved 2019-01-31. https://github.com/animate1978/MB-Lab ↩
Bart (December 15, 2018). "ManuelBastioniLAB fork 'MB-Lab' is looking for contributors". BlenderNation. Archived from the original on June 7, 2019. Retrieved October 28, 2019. https://www.blendernation.com/2018/12/15/manuelbastionilab-fork-mb-lab-is-looking-for-contributors/ ↩
Thacker, Jim (January 28, 2018). "Create free CG characters with Manuel Bastioni Lab 1.6.1". CG Channel. Archived from the original on April 28, 2019. Retrieved November 1, 2019. http://www.cgchannel.com/2018/01/manuel-bastioni-lab-turns-blender-into-a-character-creator/ ↩
"Meta parameters". mb-lab.readthedocs.io. Retrieved 2019-10-31. https://mb-lab.readthedocs.io/en/latest/creation_tools.html ↩
"Posing the character". mb-lab.readthedocs.io. Archived from the original on 2019-10-31. Retrieved 2019-10-31. https://mb-lab.readthedocs.io/en/latest/pose.html ↩
"License". github.com. Retrieved 2019-10-31. https://github.com/animate1978/MB-Lab/blob/master/license.txt ↩
"Base characters in Manuel Bastioni Lab". mb-lab.readthedocs.io. Archived from the original on 2019-10-31. Retrieved 2019-10-31. https://mb-lab.readthedocs.io/en/latest/base_char.html ↩
Designed to be optimally sculpted with Blender, Mudbox, Zbrush, etc. ↩
"Phenotypes". mb-lab.readthedocs.io. Retrieved 2019-10-31. https://mb-lab.readthedocs.io/en/latest/creation_tools.html#phenotypes ↩
Andersson, Pontus; Wessman, David (2018-08-10). Generation of Artificial Training Data for Deep Learning (Master). Lund university. ISSN 1650-2884. LU-CS-EX 2018-39. Archived from the original on 2019-10-31. Retrieved 2019-10-31. http://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=8972350&fileOId=8972351 ↩
Guevara, Bermeo; Bryan, Stefano; Martínez, Navarrete; Azucena, Wilma (2018-07-13). Diseño y desarrollo de un sistema inmersivo de reconocimiento y control de gestos, ostensible por medio de realidad virtual como método de ayuda en la rehabilitación de la capacidad motriz de las extremidades superiores en pacientes con accidente cerebrovascular [Design and development of an immersive gesture recognition and control system, ostensible through virtual reality as an aid method in the rehabilitation of the motor capacity of the upper extremities in patients with stroke] (Thesis) (in Spanish). Universidad de Las Fuerzas Armadas ESPE. pp. 106–110. Archived (PDF) from the original on 2019-10-31. Retrieved 2019-10-31. http://repositorio.espe.edu.ec/handle/21000/14928 ↩
"ManuelBastioniLAB Character Editor Shuts Down". BlenderNation. November 26, 2018. Archived from the original on June 7, 2019. Retrieved November 1, 2019. https://www.blendernation.com/2018/11/26/manuelbastionilab-character-editor-shuts-down/ ↩
"MB-Lab GitHub clone". mb-lab.readthedocs.io. Archived from the original on 2019-08-19. Retrieved 2019-10-31. https://mb-lab-community.github.io/MB-Lab.github.io/ ↩
Thacker, Jim (July 22, 2019). "Create free, facially rigged CG characters with MB-Lab 1.7.5". CG Channel. Retrieved October 31, 2019. http://www.cgchannel.com/2019/07/create-free-facially-rigged-cg-characters-with-mb-lab-1-7-5/ ↩