mxochicale/code

:computer: :school_satchel: code

Websites: Personal Website

Miguel is currently a Senior Research Engineer at University College London, UK, where he leads pioneering advancements in data-centric AI tools for Medical Imaging, MedTech, SurgTech, Biomechanics, and Clinical Translation. His work focuses on driving innovation and delivering impact in several critical areas: Real-time AI for surgery, eye movement disorders, and echocardiography, Sensor fusion data integrating wearable trackers with medical imaging, Generative models for fetal imaging, and Child-robot interaction in low-resource countries. By harnessing these cutting-edge technologies, he is dedicated to transforming healthcare through AI and making a lasting impact on patient care and medical research.

code's Issues

What is a std::atomic?

What is an atomic operation? An atomic operation is an operation guaranteed to execute as a single unified transaction. When an atomic operation is executed on an object by a specific thread, no other threads can read or modify the object while the atomic operation is in progress. This means that other threads will only see the object before or after the operation — no intermediary state.
https://ryonaldteofilo.medium.com/atomics-in-c-what-is-a-std-atomic-and-what-can-be-made-atomic-part-1-a8923de1384d

let's try yolov5-opencv-cpp-python (*.onnx)

C++:

• https://github.com/doleron/yolov5-opencv-cpp-python

Python:

• https://github.com/ibaiGorordo/ONNX-YOLOv7-Object-Detection
• https://forums.developer.nvidia.com/t/tensorrt-with-onnx-model-and-rgb-opencv-data/175401/5

Raising the quality of scientific Jupyter notebooks

• https://www.kitware.com/how-to-raise-the-quality-of-scientific-jupyter-notebooks/
• https://github.com/mxochicale/itkwidgets

PyCharm update version

Just raising this one to track updates of version for https://github.com/mxochicale/code/tree/main/IDEs/pycharm

Codespaces with ML workflows

• https://www.sckaiser.com/blog/2023/01/30/conda-codespaces.html
• https://github.com/crazy4pi314/conda-devcontainer-demo
• https://blog.shibayan.jp/entry/20220309/1646754054
• https://www.youtube.com/watch?v=RIchFX_gYb0
• https://github.com/microsoft/AI-For-Beginners/blob/main/.devcontainer/Dockerfile

R

[playground/gradient-boosted-trees] (GradientBoostingRegressor,RandomForestRegressor,VotingRegressor,etc)

• https://scikit-learn.org/stable/auto_examples/ensemble/plot_voting_regressor.html#sphx-glr-auto-examples-ensemble-plot-voting-regressor-py
• https://scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html

Let's try `Object Detection TensorRT Example`

https://github.com/NVIDIA/object-detection-tensorrt-example

replicate cLaki/UseTheForce

https://github.com/cLaki/UseTheForce

Installing CUDA drivers in new Ubuntu OS

I am raising this one to improve documentation on the installation of CUDA drivers in new Ubuntu OS

try pytorch-transfer-learning-and-image-classification/

https://www.pyimagesearch.com/2021/10/11/pytorch-transfer-learning-and-image-classification/

trying cv2PySide6 > araviq6

trying

• https://github.com/JSS95/cv2PySide6
• https://github.com/JSS95/araviq6

ohthers
civiq6: https://github.com/JSS95/civiq6

but require to install https://github.com/alliedvision/VimbaPython which is not in pypi

adds vtk with few examples

• Replicate Step 1 to 6: https://kitware.github.io/vtk-examples/site/Python/#tutorial > https://github.com/Kitware/vtk-examples/tree/master/src/Python/Tutorial
• try pyside6 with vtk of https://gist.github.com/dgobbi/7353d889886e190169e607302c618451#file-qtimageexample-py

C++ concurrency

• http://www.robert-puskas.info/2019/03/overview-cpp-concurrency.html
• https://stackoverflow.com/questions/3652056/how-efficient-is-locking-and-unlocked-mutex-what-is-the-cost-of-a-mutex
  • https://github.com/CarloWood/ai-statefultask-testsuite/blob/b69b112e2e91d35b56a39f41809d3e3de2f9e4b8/src/mutex_test.cxx

speed up conda by using mamba

https://www.biostars.org/p/9461665/

Testing Latest Stable version of OpenCV

• 4.9.0 https://github.com/opencv/opencv/releases/tag/4.9.0
• Seems 4.10-dev is avaialble but let's see
• 5.x? https://github.com/opencv/opencv/tree/5.x https://docs.opencv.org/5.x/d7/d9f/tutorial_linux_install.html

notes

• libv4l2cpp C++ wrapper for V4L2 https://github.com/mpromonet/libv4l2cpp
• https://github.com/lagadic/visp/blob/master/tutorial/grabber/tutorial-grabber-v4l2-threaded.cpp
  • https://www.youtube.com/user/VispTeam/videos
• https://arcoresearchgroup.wordpress.com/2020/06/02/virtual-camera-for-opencv-using-v4l2loopback/
  • https://bitbucket.org/OscarAcena/ocv-virtual-cam/src/master/
• https://www.e-consystems.com/articles/camera/accessing_cameras_in_opencv_with_high_performance.asp#
• ...

try Poetry

Poetry is a tool for dependency management and packaging in Python: https://python-poetry.org/docs/ https://github.com/python-poetry/poetry

Tidy up demos for kalman filters

• Create a common conda virtual environment
• Add gif for animations in the demos
• Try to investigate the latency of kalman algorithms

displaying a video feed with OpenCV and Tkinter?

Replicate this one https://pyimagesearch.com/2016/05/30/displaying-a-video-feed-with-opencv-and-tkinter/ (May 30, 2016)

Using `pytest`

• https://docs.pytest.org/en/7.1.x/contents.html#
• https://docs.pytest.org/en/7.1.x/example/nonpython.html#working-with-non-python-tests
• Python pytest.File() Examples: https://www.programcreek.com/python/example/81429/pytest.File

c++

Adding examples for few principles of c++

try DeepLabCut

See https://github.com/DeepLabCut/DeepLabCut

try few of these PyTorch-GAN examples

https://github.com/eriklindernoren/PyTorch-GAN

debugging in Python

Would like to try some of the debugging tools posted by Andrej Karpathy:

https://twitter.com/karpathy/status/1610822271157022720

then Suhail came with this "vscode debugger seems unbeatable to me rm"

https://twitter.com/Suhail/status/1610823726416953346/photo/1

So, let's try code https://www.digitalocean.com/community/tutorials/how-to-debug-python-with-an-interactive-console

GStreamer

GStreamer is a library for constructing graphs of media-handling components. The applications it supports range from simple Ogg/Vorbis playback, audio/video streaming to complex audio (mixing) and video (non-linear editing) processing.
https://gstreamer.freedesktop.org/

• Playing video

gst-launch-1.0 v4l2src device=/dev/video2 ! videoconvert ! videoscale ! video/x-raw, width=640, height=480, framerate=30/1 ! autovideosink
gst-launch-1.0 videotestsrc ! autovideosink
gst-launch-1.0 videotestsrc ! ximagesink

gst-launch-1.0 -vvv videotestsrc ! 'video/x-raw,width=1280,height=720,format=RGB,framerate=60/1' ! autovideosink
gst-launch-1.0 -vvv videotestsrc ! 'video/x-raw,width=1280,height=720,format=YV12,framerate=30/1' ! autovideosink

• Options

v4l2src: Reads frames from a linux video device.
videotestsrc: Creates a test video stream.
videoconvert: Converts video format.
videoscale: Resizes video.
autovideosink: Automatically detects video sink.

• features of devices

v4l2-ctl --list-formats-ext --device /dev/video2

References

• https://en.wikipedia.org/wiki/GStreamer
• https://gist.github.com/hum4n0id/cda96fb07a34300cdb2c0e314c14df0a
• https://gstreamer.freedesktop.org/
• https://nnstreamer.github.io/tutorial1_playing_video.html

Text to speech open-source libraries

• piper: A fast, local neural text to speech system https://github.com/rhasspy/piper
• Tortoise is a text-to-speech program built with the following priorities: Strong multi-voice capabilities. Highly realistic prosody and intonation. https://github.com/neonbjb/tortoise-tts https://replicate.com/afiaka87/tortoise-tts/examples

try Yolov5-inference-on-ONNXRuntime-and-opencv-DNN

https://github.com/poojatambe/Yolov5-inference-on-ONNXRuntime-and-opencv-DNN

Create virtual environments with miniconda

• Add few instructions to install miniconda on Ubuntu
• test the creation of a miniconda virtual environment

Using latest version of Visual Studio Code

Raising this one to track updates for latest versions of Visual Studio Code

try Build a Super Simple GAN in PyTorch

https://towardsdatascience.com/build-a-super-simple-gan-in-pytorch-54ba349920e4
https://github.com/nbertagnolli/pytorch-simple-gan

Playing around with materials/mandelbrot-set-python/

Draw the Mandelbrot Set in Python

https://github.com/realpython/materials/tree/mandelbrot/mandelbrot-set-python

Adding few examples of MultiThreading in Python

Opening this one to add few examples of MultiThreading in Python

References (might be better ones)

• https://www.youtube.com/watch?v=wOFnKB33Lls
• https://towardsdatascience.com/multithreading-multiprocessing-python-180d0975ab29
• https://www.youtube.com/watch?v=PcJZeCEEhws added: Thu 21 Jul 15:52:46 BST 2022
• https://www.youtube.com/watch?v=AZnGRKFUU0c added: Thu 21 Jul 15:55:59 BST 2022

try `nvFuser` with torch 1.13; functorch

This tutorial will demonstrate how you can accelerate your networks with nvFuser. nvFuser is a Deep Learning Compiler that just-in-time compiles fast and flexible GPU specific code to reliably accelerate users’ networks automatically, providing speedups for deep learning networks running on Volta and later CUDA accelerators by generating fast custom “fusion” kernels at runtime. nvFuser is specifically designed to meet the unique requirements of the PyTorch community, and it supports diverse network architectures and programs with dynamic inputs of varying shapes and strides.
https://pytorch.org/tutorials/intermediate/nvfuser_intro_tutorial.html

Trying Live pyqtgraph plot

https://github.com/domarm-comat/pglive

Testing few features of sklearn

Raising this one to test few features of sklearn

• from sklearn.ensemble import RandomForestRegressor
• from sklearn.neighbors import KNeighborsRegressor
• etc
  Reference: https://github.com/malleshd/Machine-Learning-Regression-Models

try onnx, `onnx.checker` and others bits

• onnx.checker
  • See examples https://snyk.io/advisor/python/onnx/functions/onnx.checker.check_model
  • Docs: https://onnx.ai/onnx/api/checker.html

pyside6: Qt for Python

https://doc.qt.io/qtforpython/examples/index.html

Using `#include <opencv2/opencv.hpp>`

I am opening this ticket to check opencv version in Ubuntu22.04.
Notes: there is already some examples for opencv in c++ https://github.com/mxochicale/code/tree/main/opencv/examples/cpp but not sure which is the opencv version and if they work in the latest ubuntu verision.

• OS

hostnamectl
 Static hostname: --
       Icon name: computer-laptop
         Chassis: laptop
      Machine ID: --
         Boot ID: --
Operating System: Ubuntu 22.04.1 LTS              
          Kernel: Linux 5.15.0-56-generic
    Architecture: x86-64
 Hardware Vendor: --

Why Synchronize your Jupyter Notebook with a python (.py) file?

https://towardsdatascience.com/why-synchronize-your-jupyter-notebook-with-a-python-py-file-bbf35baf02ee

Just a quickly trying YOLOv9

• https://github.com/culurciello/yolov9demo?tab=readme-ov-file

References

• https://github.com/WongKinYiu/yolov9
• https://github.com/kadirnar/yolov9-pip
• https://stackoverflow.com/questions/64902852/the-difference-between-opencv-python-and-opencv-contrib-python

Some issues

cv2.error: OpenCV(4.9.0) /io/opencv/modules/highgui/src/window.cpp:1272: error: (-2:Unspecified error) The function is not implemented. Rebuild the library with Windows, GTK+ 2.x or Cocoa support. If you are on Ubuntu or Debian, install libgtk2.0-dev and pkg-config, then re-run cmake or configure script in function 'cvShowImage'
SOLVED #- opencv-contrib-python-headless USING - opencv-python

Using docker

Creating this one to add few details to use docker in Ubuntu

1. Installation

sudo apt update
sudo apt install docker.io

docker version
Client:
 Version:           24.0.5
 API version:       1.43
 Go version:        go1.20.3
 Git commit:        24.0.5-0ubuntu1~20.04.1
 Built:             Mon Aug 21 19:50:14 2023
 OS/Arch:           linux/amd64
 Context:           default
permission denied while trying to 
connect to the Docker daemon socket at unix:///var/run/docker.sock:

https://www.howtoforge.com/tutorial/how-to-create-docker-images-with-dockerfile/

2. Linux post-installation steps for Docker Engine

sudo groupadd docker
sudo usermod -aG docker $USER
newgrp docker
docker run hello-world
reboot
#chmod 777 /var/run/docker.sock
#sudo chmod 666 /var/run/docker.sock

https://docs.docker.com/engine/install/linux-postinstall/#manage-docker-as-a-non-root-user

References

• https://docs.docker.com/engine/install/ubuntu/#install-using-the-repository

Testing Learn-CUDA-Programming

https://github.com/PacktPublishing/Learn-CUDA-Programming

The bolts and nuts of GAN in PyTorch

https://www.youtube.com/watch?v=OljTVUVzPpM

LightBGM and XGBoost [playground/xgboost]

Quick replication of https://neptune.ai/blog/xgboost-vs-lightgbm

Trying geospacial tools (i.e.. `Rasterio`, `earthpy`,etc)

https://github.com/rasterio/rasterio
https://pypi.org/project/rasterio/

try pytorch-lightning

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
https://github.com/PyTorchLightning/pytorch-lightning