April 7, 2021 Python

The worst so-called “best practice” for Docker

Somebody is always wrong on the Internet, and bad Docker packaging advice is quite common. But one particular piece of advice keeps coming up, and it’s dangerous enough to merit its own article. In a whole bunch of places you will be told not to install security updates when building your Docker image. I’ve been submitting PRs to fix this, so it’s up in fewer places now. But previously this advice was given by the official Docker docs’ best practices […]

April 7, 2021 Python

Loading SQL data into Pandas without running out of memory

You have some data in a relational database, and you want to process it with Pandas. So you use Pandas’ handy read_sql() API to get a DataFrame—and promptly run out of memory. The problem: you’re loading all the data into memory at once. If you have enough rows in the SQL query’s results, it simply won’t fit in RAM. Pandas does have a batching option for read_sql(), which can reduce memory usage, but it’s still not perfect: it also loads […]

April 7, 2021 Machine Learning, NLP

Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers

BCNet Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [BCNet, CVPR 2021] This is the official pytorch implementation of BCNet built on the open-source detectron2. Lei Ke, Yu-Wing Tai, Chi-Keung TangCVPR 2021 Two-stage instance segmentation with state-of-the-art performance. Image formation as composition of two overlapping layers. Bilayer decoupling for the occluder and occludee. Efficacy on both the FCOS and Faster R-CNN detectors. Under construction. Our code and pretrained model will be fully released in two months. Visualization of Occluded Objects Qualitative […]

April 7, 2021 Machine Learning, NLP

A Distributed Classification Training Framework with PyTorch

Distribuuuu The pure and clear PyTorch Distributed Training Framework. Distribuuuu is a Distributed Classification Training Framework powered by native PyTorch. Please check tutorial for detailed Distributed Training tutorials: Single Node Single GPU Card Training [snsc.py] Single Node Multi-GPU Crads Training (with DataParallel) [snmc_dp.py] Multiple Nodes Multi-GPU Cards Training (with DistributedDataParallel) ImageNet training example [imagenet.py] For the complete training framework, please see distribuuuu. Requirements and Usage Dependency Install PyTorch>= 1.5 (has been tested on 1.5, 1.7.1 and 1.8) Install other dependencies: […]

April 7, 2021 Machine Learning, NLP

Auto-Magical Suite of tools to streamline your ML workflow

ClearML ClearML – Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, ML-Ops and Data-Management ClearML is a ML/DL development and production suite, it contains three main modules: Experiment Manager – Automagical experiment tracking, environments and results ML-Ops – Automation, Pipelines & Orchestration solution for ML/DL jobs (K8s / Cloud / bare-metal) Data-Management – Fully differentiable data management & version control solution on top of object-storage(S3/GS/Azure/NAS) ClearML Experiment Manager Adding only 2 lines to your code gets you […]

April 7, 2021 NLP, Robot

Cryptocurrency trading bot with a graphical user interface

algobot Cryptocurrency trading bot that allows users to create strategies and then backtest, simulate, or run live bots using them. Telegram integration has been added to support easier and remote trading. Installation Please make sure you have an installation of at least Python 3.6. For Linux/MacOS: python -m venv .venv source .venv/bin/activate pip install -r requirements.txt For Windows: python -m venv venv call venv/Scripts/activate pip install -r requirements.txt If your install fails, please make sure to have Visual Studio Build […]

April 7, 2021 NLP, Tool

Pyright extension for coc.nvim

pyright.enable Enable coc-pyright extension true python.analysis.autoImportCompletions Determines whether pyright offers auto-import completions true python.analysis.autoSearchPaths Automatically add common search paths like ‘src’ true python.analysis.diagnosticMode Analyzes and reports errors for open only or all files in workspace openFilesOnly python.analysis.stubPath Path to directory containing custom type stub files typings python.analysis.typeshedPaths Paths to look for typeshed modules [] python.analysis.diagnosticSeverityOverrides Override the severity levels for individual diagnostics {} python.analysis.typeCheckingMode Defines the default rule set for type checking basic python.analysis.useLibraryCodeForTypes Use library implementations to extract type […]

April 7, 2021 Network, NLP

Neural networks applied in recognizing guitar chords using python

Chords.py Neural networks applied in recognizing guitar chords using python, AutoML.NET with C# and .NET Core The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows 10 64 bits. Versions for Linux are expected to come as a console application. Installing the application. The demo app uses AutoML .NET as the default prediction engine and ONNX runtime as the legacy prediction engine to run the exported model created on […]

April 6, 2021 Python

Python vs Java: Object Oriented Programming

Java programmers making a move to Python often struggle with Python’s approach to object-oriented programming (OOP). The approach to working with objects, variable types, and other language capabilities taken by Python vs Java are quite different. It can make switching between both languages very confusing. This course compares and contrasts object-oriented programming support in Python vs Java. By the end, you’ll be able to apply your knowledge of object-oriented programming to Python, understand how to reinterpret your understanding of Java […]

April 6, 2021 Machine Learning, NLP

Enhancing Unsupervised Video Representation Learning

DSM The source code for paper Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion 1. Introduction (scene-dominated to motion-dominated) Video datasets are usually scene-dominated, We propose to decouple the scene and the motion (DSM) with two simple operations, so that the model attention towards the motion information is better paid. The generated triplet is as below: What DSM learned? With DSM pretrain, the model learn to focus on motion region (Not necessarily actor) powerful without one […]

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