Books

 

[1] La Incognita Newton ( My First book )

 

[1] Amazon https://www.amazon.com/INCOGNITA-NEWTON-CATHERINE-SHAW/dp/B00A6FIPGK

[2] As palavras de saramago

https://kbook.com.br/wp-content/uploads/2016/07/aspalavrasdesaramago.pdf

2D and 3D Moments resources

Theory

[1] Binary Image http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OWENS/LECT2/node3.html

[2] https://towardsdatascience.com/a-visual-introduction-to-binary-image-processing-part-1-d2fba9f102a4

[3] Hu Moments code and theory https://www.learnopencv.com/shape-matching-using-hu-moments-c-python

[4] PCA Analysis and code https://towardsdatascience.com/visualizing-principal-component-analysis-with-matrix-transforms-d17dabc8230e

[3] 3D moments http://147.231.16.195/3DRotationInvariants

Codes

[1] OpenCV moments https://github.com/krutikabapat/Shape-Matching-using-Hu-Moments

[2] Hu Moments https://github.com/adailtonjn68/hu_moments_in_python

Books

[1] 2D and 3D Image Analysis by Moments https://b-ok.lat/book/4985123/51d687?regionChanged=&redirect=34651345

Applications

[1] Tracking http://raphael.candelier.fr/?blog=Image%20Moments

 

 

 

 

 

Cloud points viewers

 

[1] python pptk  https://github.com/heremaps/pptk

Compile g3dviewer in Ubuntu16

 

Source:

[1] http://automagically.de/g3dviewer/

Settings:

$cd src

$grep DATA_DIR *

$locate g3dviewer.glade #to define DATA_DIR

#To find right libraries

$pkg-config --libs gtk+-2.0     
$pkg-config --libs gtkglext-x11-1.0

 

Compile Code:

$gcc -o app main.c model.c screenshot.c texture.c trackball.c glarea.c gl.c gu
i_callbacks.c gui_glade.c gui_infowin.c gui_log.c -I /usr/include/gtk-2.0 -I /u
sr/include/glib-2.0 -I /usr/lib/x86_64-linux-gnu/glib-2.0/include -I /usr/inclu
de/cairo -I /usr/include/pango-1.0 -I /usr/lib/x86_64-linux-gnu/gtk-2.0/include
-I /usr/include/gdk-pixbuf-2.0 -I /usr/include/atk-1.0 -I /usr/include/gtkglex
t-1.0 -I /usr/lib/gtkglext-1.0/include -I /usr/include/libglade-2.0 -lgtk-x11-2
.0 -lgdk-x11-2.0 -lpangocairo-1.0 -latk-1.0 -lcairo -lgdk_pixbuf-2.0 -lgio-2.0
-lpangoft2-1.0 -lpango-1.0 -lgobject-2.0 -lglib-2.0 -lfontconfig -lfreetype -lm
-lGL -lglut -lGLU -lglade-2.0 -lgtkglext-x11-1.0 -lgdkglext-x11-1.0 -lGLU -lGL
-lXmu -lXt -lSM -lICE -lgdk-x11-2.0 -lpangox-1.0 -lX11 -Wl,--export-dynamic -l
gmodule-2.0 -pthread -lgtk-x11-2.0 -lgdk-x11-2.0 -lpangocairo-1.0 -latk-1.0 -lc
airo -lgdk_pixbuf-2.0 -lgio-2.0 -lpangoft2-1.0 -lpango-1.0 -lgobject-2.0 -lglib
-2.0 -lfontconfig -lfreetype -lg3d

 

Maxx alternatives

 

Resources:

[1] php+mysql https://sourceforge.net/projects/simple-invoice/

      demo http://obedalvarado.pw/simple-invoice/

[2] php+mysql https://sourceforge.net/projects/gatax/

 

Compile k3d in Ubuntu 16

 

Source http://www.k-3d.org/

Main errors:

INCLUDE(K3DFindFreetype2) # freetype6-dev

INCLUDE(K3DFindGtkmm) #DEBUG 

https://gtkmm.org/en/download.html #works with version 2.x

INCLUDE(K3DFindFTGL) #DEBUG

#To DEBUG Variables

message(STATUS "DEBUG: K3D_FREETYPE2_FOUND: ${K3D_FREETYPE2_FOUND}")
message(STATUS "DEBUG: Aqsis_FOUND: ${Aqsis_FOUND}")

#Support CUDA need to enable in CMakeLists.txt (main)

Day 2:

K3DFindBoost.cmake (update paths)

SET(K3D_BOOST_INCLUDE_DIR "/usr/local/include" CACHE PATH "Override the default location for Boost header files.")
SET(K3D_BOOST_LIBRARY_DIR "/usr/local/lib" CACHE PATH "Override the default location for Boost libraries.")

renderframe/CMakeLists.txt

LINK_DIRECTORIES() #add boost path

TARGET_LINK_LIBRARIES()  #add boost_regex boost_program_options boost_system boost_python27 boost_thread boost_date_time

 #disable CGAL

#K3D_CHECK(K3D_BUILD_CGAL_MODULE REQUIRES K3D_CGAL_FOUND RESOURCE "CGAL") #DEBUG

 

Houdini Resources

Models online
[1] Fluid, Physics models https://hdbp.io/browse?page=3

[2] Complete dops examples with Houdini files to download

https://www.tokeru.com/cgwiki/index.php?title=HoudiniDops

Nubank Status and Alternatives

 

 

References: 

[0] https://olhardigital.com.br/noticia/nubank-tem-prejuizo-de-r-313-milhoes-em-2019-mas-isso-nao-e-ma-noticia/97307

[1] Pt https://tecnoblog.net/237472/nubank-alternativas-cartao-de-credito/

Compile and Links snippets

 

 

[1] cmake parameters https://stackoverflow.com/questions/31387188/pass-variable-value-to-make-using-cmake

 

[2] PYTHONPATH https://www.devdungeon.com/content/python-import-syspath-and-pythonpath-tutorial

 

Deep Learning Architectures

[1] Helper using latex to Draw Net https://github.com/HarisIqbal88/PlotNeuralNet

[2] https://github.com/yosinski/deep-visualization-toolbox

[3] https://github.com/wagenaartje/neataptic

[4] .Appimage (viewer .h5 models) https://github.com/lutzroeder/netron

[5] 

!pip install visualkeras
import visualkeras
visualkeras.layered_view(modelobject)

[6] Quiver? https://github.com/ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network

References:

[1] https://datascience.stackexchange.com/questions/12851/how-do-you-visualize-neural-network-architectures/44571#44571

Boost 1.7 on Ubuntu16

 

 

https://www.boost.org/users/download/

Enable to work with Python3

cd boost1.7

 $./bootstrap.sh -with-libraries=python -with-python-version=3.6 
$./b2

$sudo ./b2 install

Lectures

 Alter ego

[1] https://amenteemaravilhosa.com.br/alter-ego/

Wavefront render

 By Code:

 [1] https://pyrender.readthedocs.io/en/latest/examples/quickstart.html

By Tools

[1] Blender (>=2.9) Add On  https://github.com/neverhood311/Stop-motion-OBJ

3D Deep Learning

 

https://github.com/mit-han-lab/pvcnn

https://paperswithcode.com/paper/octnet-learning-deep-3d-representations-at

Numeric methods to solve PDE

 

 

[1] http://www.maths.dur.ac.uk/~dma0bmp/

 

Pdf Listen tools

 

 

http://freesoftwaremagazine.com/articles/listen_your_books_epub_pdf_okular/

 https://askubuntu.com/questions/633337/pdf-reader-that-can-read-out-loud

Installed this extension on chrome called readaloud

https://www.sodapdf.com/pdf-reader/  (Just for open pdf online)

Python Animation Matrix Convolution

 

[1] Convolution animation https://stackoverflow.com/questions/52067833/how-to-plot-an-animated-matrix-in-matplotlib

Python - Read binary data int float

 

[1] struct https://docs.python.org/3.0/library/struct.html 

Toefl Resources (English Exam)

 

 

https://www.ets.org/s/cv/toefl/the-americas/

 

Listening

[1] Example https://www.ets.org/toefl_itp/content/sample_questions

[2] 65 Listen tests https://englishteststore.net/

[3] Toefl Listen https://englishteststore.net/index.php?option=com_content&view=article&id=11388&Itemid=2799

 

Edital Capes Print 

[1] https://www.gov.br/capes/pt-br/acesso-a-informacao/acoes-e-programas/bolsas/bolsas-e-auxilios-internacionais/informacoes-internacionais/programa-institucional-de-internacionalizacao-capes-print

[2] http://www.propp.ufu.br/sites/propp.ufu.br/files/conteudo/acontece_na_pro_reitoria/retificacao_do_edital-ufu-capes.print-bolsas-2019-25_03_19.pdf

Course

https://courses.edx.org/login

 

 

 

Mount Google Drive in local file system

 

[1]  https://ostechnix.com/how-to-mount-google-drive-locally-as-virtual-file-system-in-linux/

 

 

Mobile App Developer tool

Tools

[1] https://flutter.dev/docs/get-started/install/linux

Time series

https://towardsdatascience.com/the-complete-guide-to-time-series-analysis-and-forecasting-70d476bfe775

https://github.com/AileenNielsen/TimeSeriesAnalysisWithPython
https://github.com/aurea-soriano/PublicAnomalyDetection

 

Tools

[1] Smooth time series

https://machinelearningmastery.com/moving-average-smoothing-for-time-series-forecasting-python/


[2] Auto encoders https://towardsdatascience.com/autoencoders-for-the-compression-of-stock-market-data-28e8c1a2da3e

Keypoints from Pose Estimation

 

 [1]  https://google.github.io/mediapipe/solutions/pose

 

Cuda Filters

 

 

[1] Recursive Gaussian Filter

http://148.225.111.80/docs/cuda-5.5/CUDA_Samples.pdf

 

 

Video edition by ffmpeg

 

$ffmpeg -i video.avi -vf subtitles=subtitle.srt out.avi

$ffmpeg -i video.mp4 -f srt -i video.srt -map 0:0 -map 0:1 -map 1:0 -c:v copy -c:a copy -c:s mov_text out.mp4

References:

[1] https://trac.ffmpeg.org/wiki/HowToBurnSubtitlesIntoVideo

[2] https://stackoverflow.com/questions/8672809/use-ffmpeg-to-add-text-subtitles

Cultura Inventos

 

[1] Thomas A. Edison(1847-1931) Fonografo vs Gramófono

https://www.youtube.com/watch?v=6AjyrEtMrQ8 

Jetson Nano Resources

 

[1] NVIDIA https://developer.nvidia.com/open-source

Watching movies

[1] Requires installation Windows/Linux https://syncplay.pl/download/

[2] Watch2Getter for Youtube links

Tools

[1] Mergue Video and Subtitle Win/Linux https://mkvtoolnix.download/downloads.html

[2]

ffmpeg -i video.mp4 -vf subtitles=video.srt out.mp4

Volume of Fluid Related

[1] Introduction Adaptive Mesh Refinement (AMR)
https://materials.prace-ri.eu/441/5/AMRIntroHNDSCi15.pdf
https://materials.prace-ri.eu/441/

Scientific Publication Resources

[1] Where to publish a scientific publication http://methodo.ucc.edu.ar/files/vol5/num3/ART%209%20..pdf

Audiobooks

[1] http://www.loyalbooks.com/genre/Teen_Young_adult
[2] Nietzsche, Socrates and others https://librivox.org



References:
[1] https://www.mosalingua.com/pt/lista-dos-melhores-audiolivros-gratuitos-para-aprender-ingles/

Euclidean Distance Transform

Resources:
[1] https://github.com/seung-lab/euclidean-distance-transform-3d

Colab include Html

Resources:

[1] with IPython https://stackoverflow.com/questions/47723731/how-embed-html-file-exported-from-plotly-to-jupiter-notebook
[2] Embedding html in Colab https://ipywidgets.readthedocs.io/en/latest/embedding.html

Segmentation Lectures

https://medium.com/free-code-camp/mask-r-cnn-explained-7f82bec890e3
https://www.analyticsvidhya.com/blog/2019/07/computer-vision-implementing-mask-r-cnn-image-segmentation/

Anisotropic Diffusion

[1] Perona Malik Diffusion for Edge Detection
https://github.com/fubel/PeronaMalikDiffusion/blob/master/main.py

[2] https://github.com/pastapleton/Perona-Malik
[3] https://pastebin.com/sBsPX4Y7

Facial Expression related

[1] Face Drawing http://geometrylearning.com/paper/DeepFaceDrawing.pdf

Automatically Text to speech resources

[1] Text to speech https://github.com/as-ideas/TransformerTTS

Rendering

[1] Physically Based Rendering https://pbrt.org/index.html
[2] Scenes https://pbrt.org/scenes-v3.html
[3] Guide https://pbrt.org/users-guide.html

Smoke Simulation Code

Compile from Windows to Linux

C++17 implementation of "Local Bases for Model-reduced Smoke Simulations" in 2D with dynamic obstacles. See www.olivier-mercier.com/res/publications/basisFluid/ for more details.

[1] Source Visual Studio https://github.com/omercier01/basisfluid
[2] One file libraries (images, noise, fonts,etc ) https://github.com/nothings/stb
[3] GLM Library https://glm.g-truc.net/0.9.2/api/index.html
[4] Localtime https://en.cppreference.com/w/c/chrono/localtime

Image Segmentation using Deep Learning resources

[1] https://www.nature.com/articles/s41699-020-0137-z.pdf

https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC5729043&blobtype=pdf

https://borda.github.io/pyImSegm/

http://vision.cs.utexas.edu/projects/keysegments/keysegments.html

SPH Code Resource

[1] C++ SPH https://github.com/aartiukh/sph-sdk
      use

    $git clone --recursive

3D Face reconstruction resources

[1] Python code  https://github.com/YadiraF/face3d
[2] Torch+Lua? https://github.com/AaronJackson/vrn
[3] Complete body https://github.com/vchoutas/smplify-x
[4] https://medium.com/vitalify-asia/create-3d-model-from-a-single-2d-image-in-pytorch-917aca00bb07
[5] Based on ShapeNet https://github.com/nywang16/Pixel2Mesh
[6] https://github.com/microsoft/Deep3DFaceReconstruction

Tools online
[1] 3D Model from single face picture https://cvl-demos.cs.nott.ac.uk/vrn/
[2] Search in github https://github.com/topics/3d-face-reconstruction


Resources
[1] https://paperswithcode.com/task/3d-face-reconstruction

SPGrid Resources

Code http://pages.cs.wisc.edu/~sifakis/project_pages/SPGrid.html

Compatibility for Linux https://gcc.gnu.org/onlinedocs/gcc-4.9.2/gcc/X86-Built-in-Functions.html
Intel instructions https://software.intel.com/sites/landingpage/IntrinsicsGuide/#text=_pext_u64&expand=4330

Houdini Resources

Working with Volumes
[1] https://www.sidefx.com/docs/houdini/model/volumes.html
[2] OpenCL convolution https://forums.odforce.net/topic/27049-volume-convolution-vex-c-vs-opencl/

Volumes
[1] Volumetric Rendering https://tigerprints.clemson.edu/cgi/viewcontent.cgi?article=2942&context=all_theses
[2] Volumes on Houdini https://www.youtube.com/watch?v=UKED3rpvYEw&t=200s


Fluids
[1] https://www.sidefx.com/learn/fluids/
[2] Animation Fluid Project (free) https://www.youtube.com/watch?v=K7UAVUzRP4Q


[1] https://www.sidefx.com/download/daily-builds/#category-gold

Write tools

https://edubirdie.com/plagiarism-checker
https://www.scanmyessay.com/
https://smallseotools.com/plagiarism-checker/

Schlieren

https://skunkbear.tumblr.com/post/73551240655/hair-straightener-by-amber-kates-that-hair-isnt

python display 3D Objects

https://ratcave.readthedocs.io/en/latest/tutorial1.html
https://pypi.org/project/PyWavefront/

Houdini Render command line

[0] https://www.sidefx.com/docs/houdini/render/batch.html
[1] structure https://www.sidefx.com/forum/topic/52170/?page=1#post-234716

[1] https://www.sidefx.com/forum/topic/31659/?page=1#post-148027
[2] https://github.com/kiryha/Houdini/wiki/python-snippets
[3] https://houdinitricks.tumblr.com/
[4] ?? https://github.com/symek/hafarm




others
[1] https://github.com/Kitware/vtk-js

COVID-19

Trackers
[1] https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6
[2] https://who.sprinklr.com/
[3] Perú https://www.bing.com/covid/local/peru
[4] https://extranet.who.int/publicemergency
[5] Brasil https://olhardigital.com.br/coronavirus/noticia/coronavirus-brasil-registra-904-casos-confirmados-e-11-mortes/98089

Codes
[1] https://laconicml.com/predict-infected-people-coronavirus-python
[2] https://github.com/fincahuanaco/covid19peru

[3] https://www.tecmint.com/convert-files-to-utf-8-encoding-in-linux/

Datasets
[1] Timeseries https://github.com/CSSEGISandData/COVID-19
[2] images https://www.kaggle.com/bachrr/covid-chest-xray/data
[2.1] https://theaisummer.com/medical-image-deep-learning

[3] Brazil daily report https://github.com/wcota/covid19br

Other Datasets

[1] Datasus http://www2.datasus.gov.br/DATASUS/index.php