5 Python Libraries for 3D Human Poses Visualization
At this moment, there are quite many various programming languages that developers use when working on different projects. Python is one of those languages that are used most often.
Universality of applications, as well as quick learning of how to work with Python make it really popular. That is why it is used for the 3D Human Poses Visualization process as well.
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3D Human Poses Visualization and where it is applied
3D Human Pose Visualization is, in fact, determining the outlines of the human body and its key nodes in order to create a realistic digital version of it. That is, a special technology based on artificial intelligence and machine learning processes information about a person's body and with the help of certain algorithms make its visualization. Many people may assume that all this is done for fun, but in fact, such projects can bring a lot of benefits to humanity. Here are the most common examples of 3D human visualization applications.
Read also: 3D Medical Metaverse
The most popular examples in this category are the technological tools that doctors use to determine if a patient's posture is correct. This way they can clearly see where the problem is, show it to patients and prescribe the necessary methods for treatment.
If we take into account ordinary users, they can often use applications with 3D visualization of their body, which are designed for workouts. That is, the system scans a person's movement positions and gives a result about correct technique during certain exercises.
Related project: SaaS for Radiologists — Radiolance™
Gaming and cinematography
Of course, for the entertainment industry, 3D visualization has been a breakthrough. More realistic augmented reality games are thrilling millions of gamers. Meanwhile, the cinematography industry has been given the opportunity to make high-quality fantasy movies and TV series.
Sports is one of the areas of the modern world that really has a lot of passionate followers. That's why it's a multi-million dollar industry that requires a serious approach. Visualization of human poses can help athletes to improve their technique, research the opponent and build a game strategy to win. All of this makes the sport even more exciting and interesting.
3D visualization of human postures can be applied in the field of robotics. With the help of machine learning, robots will be able to repeat all movements as naturally and smoothly as a human does.
Why using libraries can make development more efficient
Libraries are certain sets of codes and templates that can be used by different developers while working on a project. The advantage of using such libraries is that they can make the development process much faster and minimize errors. In fact, a developer can simply insert an already existing part of code from a library and add a little bit of his own data to it. As a result, you will get a customized project for your needs.
TOP 5 Python libraries for 3D Human Visualization
1. SMPL-Anthropometry (from DavidBoja)
Using material from this library will allow you to work with visualizing a 3D model of a person and its measurements. Among the available options are measuring body lengths and circumferences. Also, a 3D model presented on the screen in T-pose should show the most accurate calculations.
2. 3d-body-measurements (from vcarlosrb)
With the help of this library it is also possible to get data on human body measurements. Unlike the previous library, the developer declares that the most correct measurements will be for A-pose of a person.
3. SPIN (from nkolot)
Using information from the nkolot repository you will be able to model 3D human poses. To do this you will have available three options, each of which is described in detail by the author.
4. Shapy (from muelea)
In this library you will find templates and parts of codes that can model a human figure from a photo. Then with the help of special metrics and formulas you can evaluate it.
5. EasyMocap (from ZengJiayi549)
Here you can find methods for 3d visualization of one or more people at a time. In addition, the visualization can be presented from different angles as well as in motion.
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