wynalazkowo - eksperymenty małe i duże

Baltic Robbo Battles 2021 – object detection and classification

Baltic Robbo Battles 2021 – object detection and classification

After reading this article, it was obvious for me to use YOLO CCN to detect objects on pic and use MobileNet model to classify them. https://medium.com/nanonets/how-to-easily-detect-objects-with-deep-learning-on-raspberrypi-225f29635c74 I used follwoing Github repo. I have built docker image and tried to run it. https://github.com/NanoNets/RaspberryPi-ObjectDetection-TensorFlow After taking pictures of several types of food in my home I usedWięcej oBaltic Robbo Battles 2021 – object detection and classification[…]

Baltic Robbo Battles 2021 – how to install docker in Windows

Baltic Robbo Battles 2021 – how to install docker in Windows

I always thought that installing Docker is difficult. Maybe it is – for Linux, but for Windows it is super easy. Here are the steps: install desktop docker from this site https://docs.docker.com/docker-for-windows/install/ install debian or another your favourite Linux distro from Microsoft Store additionaly install linux kernel-update-package from this site https://docs.microsoft.com/pl-pl/windows/wsl/install-win10#step-4—download-the-linux-kernel-update-package And voila! You haveWięcej oBaltic Robbo Battles 2021 – how to install docker in Windows[…]

Rundeck

Rundeck

Recently I had opportunity to configure this automation tool. In general, when it is well configured it works as a charm – it can be used to automate almost everything – starting from normal admin scripts, monitoring scripts, ending with home automation. You can write scripts in any programming language you want: Powershell, bash, WinWięcej oRundeck[…]

Machine Learning – introduction

Machine Learning – introduction

How to achieve this in pytohn: import pandas as pd import numpy as np from sklearn.tree import DecisionTreeClassifier from sklearn.model_selection import cross_val_score import xgboost as xgb import eli5 from collections import Counter import gc Firstly we import libraries: pandas, numpy-for data analysis and preparation. From library sklearn we import AI model and needed operations onWięcej oMachine Learning – introduction[…]

DataScience and MachineLearning

DataScience and MachineLearning

Here are another two interesting www sites for learning AI and DataScience: This site consists of free DataScience courses and datasets: https://www.kaggle.com/ 2. This is free course of AI in German: https://bootcamp.codecentric.ai/

AI – cats and dogs classifier

AI – cats and dogs classifier

Recently I participated in very interesting workshop on Technical University in GDN. Workshop was lead by Tomasz Kocejko from faculty: Medical Telematics. This workshop presented possibilites of using Machine Learning models on mobile devices. More info: https://aibay.ai/wp-content/uploads/2020/11/kursy_Inferencja_Android_DIH.pdf This is only an example what could be achieved with Transfer Learning. The goal is: creation of mobileWięcej oAI – cats and dogs classifier[…]

Xiaomi MI recenzja

Xiaomi MI recenzja

To hulajnogę testuję już prawie 3 lata, więc myślę, że przyszedł czas na recenzję. Po dokonaniu żywota poprzedniej hulajnogi szukałam hulajnogi, która: będzie równie lekka jak poprzednia – bym mogła bez problemu ją wnosić na 4 piętro będzie wytrzymała (szczególnie podczas podjeżdżania na krawężniki) i mająca trochę większe koła niż poprzednia po złożeniu nie zajmującaWięcej oXiaomi MI recenzja[…]

PhantomJS – headless webbrowser

PhantomJS – headless webbrowser

For rendering Javascript pages in cmd line in Linux/Windows without GUI: https://github.com/ariya/phantomjs It works similar to headless Chrome, but it doesn’t require installation as root. This software can be used for testing sites or as aim for IBM Watson Explorer/ ElasticSearch engine to crawl sites entirely written in Javascript. It renders Javascript page and returnsWięcej oPhantomJS – headless webbrowser[…]