New Logo

Hello there. I'm still here. 

Recently, I decided to make a logo for this blog. So, here it is.

Global Game Jam 2024

Wow, what a weekend. The Global Game Jam is intense. But I and 3 other members manage to build a game for the theme "Make me laugh".

Go and check out the Apocalyptic Bowling! Destroy everything!

Rigid Registration Finished

Yay! Finally! After 3.5 weeks of work, it is done. And it even has an animated GIF to undertand how it works through the GUI. 

I'll just try to install the code all over again to build a step-by-step tutorial so anyone can use it.

Check out the code here:

GitHub/LilianeRA/RigidRegistration

Visualization almost complete

Another update for the Rigid Registration project.

Now you can visualize the result of the registration, choose the method configuration from the GUI and reset to check the performance of another method.

There are still some issues to investigate, but the first release is close.

See you soon!

Lie Groups Incorporated

More news. Today was really productive. 

I've just finished the implementation of all the Lie Group approaches into the ICP Rigid Registration method, according to my paper:

Pairwise Rigid Registration Based on Riemannian Geometry and Lie Structures of Orientation Tensors

I still need to confirm if the results are the same as in the original code.

But you can still check the code here:

GitHub/LilianeRA/RigidRegistration

Basic Rigid Registration complete

Hello there.

I've finished the base code for the Original ICP, the ICP-CTSF, SWC-ICP and SWC-CTSF. I've only tested it with the Stanford Bunny, downsampled to have 894 points. After incorporating the Lie Groups, I'll start the real performance test.

Have a look!

GitHub/LilianeRA/RigidRegistration

I'm back. Again

Sorry guys, I can only come back here during my vacations. But this time, I made a new year's promise to give more attention to this blog. Right now, I'm developing a 3D Visualizer based on OpenGL and Dear ImGui for me to use in any other project. Details here:

GitHub/LilianeRA/Visualizer3D

And the second project is the code refactor for the official implementation of the Rigid Registration methods developed by my college colleagues: ICP-CTSF and SWC-ICP. The code is being published here:

GitHub/LilianeRA/RigidRegistration

For now, I've only tested it on Windows 10. Feel free to try to install it. If you have any trouble, you can let me know

Tensorflow 1.x to 2.x

I changed the only function from Tensorflow 1.x of TempoGAN that I mentioned in this post, from

tf.contrib.layers.batch_norm()

to

tf.compat.v1.layers.batch_normalization()

and, of course, the pre-trained weights are useless now that I changed the net structure. So, I need to retrain it, but there is no script to do it. I can do one myself and be very careful when choosing the parameters. Or, I use Google Colab to run the original net for me.

You may have noticed that Google Colab does not support Tensorflow 1.x anymore, right? But no worries. I've found a way to overcome this with miniconda here.

I'm back

Hello. It's been a a while. Not yet back to normal, but as normal as it can be.

I'm here to tell about an error I got while trying to run the TempoGAN on a brand new server. The error happens when "session.run" is called, and it gives:

Internal: Blas SGEMM launch failed : m=216000, n=32, k=4

If you search on the internet, everyone will tell this is due to lack of memory in the GPU. Ok, this net is quite large but... I have 48GB available to me! This net can't be that greedy.

So, what did I found? Yes, it needs more memory in the graphics card... BECAUSE IT IS NOT ALLOCATING ANY!  The code is from 2018, the GPU architecture is modern, and cuBLAS from CUDA 10 does not know how to do its job.

I'm sorry, but you and I will have to upgrade the code to Tensorflow 2.X.

Good luck for us. 

Trying to return to normal

Hello. 

I am having troubles with 3 estate inventory deeds and an eviction action, which are taking a lot of my time. But I hope this year all of them will be solved. Until then, I need to raise money for all the taxes, fine, interests and court costs related to it. So I am really focused on my work, and that's why there were no updates here.

But the first thing I'll do is to post the code of the simple Toy Model net to learn the traingle area,

See you soon.

Troubleshoot in Visual Studio 2013 Community

A few days ago I was receiving a message from Visual Studio, telling that my license needed to be updated. Nonsense, I thoutgh. How can a free program have a license to expire? Then, after 30 days, the program was blocked. I tried to sign in again, update my license, but all I got was: 

The underlying connection was closed: An unexpected error occurred on a send.

I followed every single sugestion to solve this, but this error was persistent. 

You know what was it?

I changed my internet provider last month, and I experienced some troubles to get a good connection, despite the high download rates. I returned to my previous internet provider, connected to the VPN of my job, set Firefox as my default browser (I was using Edge), delete the user data with the command "./devenv.exe /resetuserdata" (devenv.exe is in "C:\Program Files (x86)\Microsoft Visual Studio 12.0\Common7\IDE") and I activated the localization system in Windows. Finally the login window showed up, VS 2013 openned and asked me to uptade the license and it was done.

I lost 3 days of work because of this. I hope you don't need to.

Link to practice reading in Japanese

Hello again. 

This time I'm here to share a link with several short books, organized by levels, and with audio (most of them).

Free easy japanese books

This link is also saved in my Japanese page.

Have fun!

Change of plans

In the last post I said I would update the tutorial of the deep learning API. But an urgent matter came first: learn to use SHAP. The subject will be a Toy Model for predicting the area of a 2D triangle based on its points.

The tutorial is not ready yet, but you can check it every week for new content, and the code is not open source yet.

When there is more updates, I'll let you know.

See ya.

Problems with PyTorch in Conda

So... I made a tutorial for using the Deep Lagrangian Fluids, but the training gets stuck in what I suppose it is a deadlock. However, the training works fine with Tensorflow. I know I said it was impossible to install the version I needed via conda (still is), but via pip, it is possible.

I'll post the tutorial update ASAP. There are some differences in the steps. I'm thinking about how to organize them.

Starting Unity

I finally decided to start learning Unity. Before building a Game Engine, I need to know how one works, right? For now I'll follow the official tutorial, and in the end I want to make a 2D spaceship game, probably similar to Chicken Invaders. I played it a lot in my childhood.

See ya.

Japanese Keyboard in Ubuntu

Hello, there. I'll just post the step by step to add the Japanese Keyboard in Ubuntu 20.04 because I always forget how.

It's here.

Cheers.

Starting Arena Engine

Yes, yes. It's been a long time. But now I found a goal for my engine. It will only implement a feature for another engine, like Quixel that was integrated in Unreal 5. Since I'm studying fluid (liquid) simulation with Deep Learning, I'm going to implement the Smoothed Particle Hydrodynamics (SPH). This is a relative old technique, so there are many works, even using CUDA and open source. This will help me a lot. 

Nevertheless, wish me luck.

New page released

I just made a tutorial to build and install all the dependencies to run the Deep Learning network I'm studying for fluid simulation, right here. For now, I can just execute it and visualize the results. The presentation video can be remade on your computer if you follow all the steps, no skipping or changing the order (please).

Soon I'm gonna find out the next step.

If you are interested on this topic and you want to work with Disney, check out the lib this project uses: Partio. And also, the SPlisH SPlasH that uses it.

I'm Back

Hello there. Almost a year, huh? 

Last time I stopped because I needed to generate data for a paper, which is now at the last step to be accepted. It is about Rigid Registration with Lie Groups. When it is released, I'll post here.

Since then, I started to research about Deep Learning for this topic. But I found out it is very complicated when you don't know much of the theory. 

For instance, I made a Toy Model with a Multilayer Perceptron to compute the triangle area. However, I couldn't make it have a good accuracy. 

So the task was assigned to another student who knows better about neural networks, and he concluded that triangles with very small area are being interpreted as outliers by the network, and making the training harder. Also, there is an error accumulation due to numerical instability, so the training needed 64 bit float and the error measurement, a 32 bit float.

Right now, I changed my research to fluid simulation with Deep Learning, far more interesting to me. I just made this code work, and very soon I'll post the step by step to make it work for you too.

See ya.

Where was I?

Hello, future me.

In case you are wondering where did I go these days since the last post, I've been busy studying many different things, from deep learning to gamification. Both are courses from Coursera, where you can watch the videos, but in order to get the certification, you must pay. Fair enough.

Also, I upgraded my Ubuntu version to 20.04, and it is a lot prettier. Now my simple laptop is faster and my desktop cleaner. Luckily, I manage to compile Yade DEM from source to activate the Potential Particles computation, which once was a real headache. But not before installing 1GB of dependencies. I know I probably wont use Yade anymore, but I found a workshop from a Ph.D in rock mechanics that opened my eyes for certain details when dealing with DEM:

1. If the particles are getting high velocities, decrease the time step for numerical stability;
2. If the real sample exhibits plastic behavior, select the simulation material that can recreate it;
   
3. Know the shape and size distribution of the grain of the material you want to simulate.

Besides, my sensei recommended me a YouTube channel that teaches Japanese in Japanse. The name is 日本語の森, and they teach grammar of any level.

So, I need to watch some of these videos, test Yade, and get the Deep Learning networks for rigid registration, that I found here, working.

I'm feeling like a workaholic. If it wasn't for my dog getting my attention, I would be lost.

PS: Today the blog completes 1 month!