Assistant

Dahua Camera and Doorbell Home Assistant Integration

Home Assistant Dahua Integration The Dahua Home Assistant integration allows you to integrate your Dahua cameras and doorbells in Home Assistant. It’s also confirmed to work with some Lorex cameras. Supports motion events, alarm events (and others), enabling/disabling motion detection, switches for infrared, illuminator (white light), security lights (red/blue flashers), sirens, doorbell button press events, and more. Also exposes several services to enable/disable motion detection or set the text overlay on the video. NOTE: Using the switch to turn on/off […]

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HTTP

An awesome library that records and replays HTTP interactions for unit tests

Cornell: record & replay mock server When your application integrates with multiple web based services, end-to-end testing is crucial before deploying to production. Mocking is often a tedious task, it becomes even more tiresome when working with multiple APIs from multiple vendors. vcrpy is an awesome library that records and replays HTTP interactions for unit tests. Its output is saved to reusable “cassette” files. By wrapping vcrpy with Flask, Cornell provides a lightweight record and replay server that can be […]

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Data Analysis

Manage your exceptions in Python like a PRO

tryceratops Manage your exceptions in Python like a PRO. Installation and usage Installation pip install tryceratops Usage tryceratops [filename or dir…] You can enable experimental analyzers by running: tryceratops –experimental [filename or dir…] You can ignore specific violations by using: –ignore TCXXX repeatedly: tryceratops –ignore TC201 –ignore TC202 [filename or dir…] You can exclude dirs by using: –exclude dir/path repeatedly: tryceratops –exclude tests –exclude .venv [filename or dir…] Violations All violations and its descriptions can be found in docs. Ignoring […]

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Images

A suite of image generation models that produce images from simple random processes

Learning to See by Looking at Noise In this work, we investigate a suite of image generation models that produce images from simple random processes. These are then used as training data for a visual representation learner with a contrastive loss. We study two types of noise processes, statistical image models and deep generative models under different random initializations. Requirements This version of code has been tested with Python 3.7.7 and pytorch 1.6.0. Other versions of pytorch are likely to […]

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GUI

Make NixOS usable for non-technical users through a settings / package management GUI

Nix-Gui Make NixOS usable for non-technical users through a settings / package management GUI. Motives The declarative nature of NixOS provides it the capability of being the most user friendly linux distro. No more editing dotfiles, /etc files, manually writing timers, services, running commands to manage and create users and groups, etc. NixOS integrates all of that into a declarative system, and this project integrates NixOS’ declarative system into a GUI. Serve Users Unfamiliar with or Learning Nix Nix-Gui is […]

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Machine Learning

Push your spaCy pipelines to the Hugging Face Hub

spacy-huggingface-hub This package provides a CLI command for uploading any trained spaCy pipeline packaged with spacy package to the Hugging Face Hub. It auto-generates all meta information for you, uploads a pretty README (requires spaCy v3.1+) and handles version control under the hood. About the Hugging Face Hub The Hugging Face Hub hosts Git-based repositories which are storage spaces that can contain all your files. These repositories have multiple advantages: versioning (commit history and diffs), branches, useful metadata about their […]

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Search

A fast and feature-rich CTC beam search decoder for speech recognition with python

pyctcdecode A fast and feature-rich CTC beam search decoder for speech recognition written in Python, providing n-gram (kenlm) language model support similar to PaddlePaddle’s decoder, but incorporating many new features such as byte pair encoding and real-time decoding to support models like Nvidia’s Conformer-CTC or Facebook’s Wav2Vec2. pip install pyctcdecode Main Features: 🔥 hotword boosting 🤖 handling of BPE vocabulary 👥 multi-LM support for 2+ models 🕒 stateful LM for real-time decoding ✨ native frame index annotation of words 💨 fast runtime, comparable to C++ implementation […]

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Network

Unofficial implementation of Alias-Free Generative Adversarial Networks

alias-free-gan-pytorch Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) This implementation contains a lot of my guesses, so I think there are many differences to the official implementations Usage First create lmdb datasets: python prepare_data.py –out LMDB_PATH –n_worker N_WORKER –size SIZE1,SIZE2,SIZE3,… DATASET_PATH This will convert images to jpeg and pre-resizes it. This implementation does not use progressive growing, but you can create multiple resolution datasets using size arguments with comma separated lists, for the cases that you want to try […]

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Screenshots

A CTF web challenge about making screenshots

screenshotter (web) A CTF web challenge about making screenshots. It is inspired by a bug found in real life. Run the challenge To run the challenge you have to install docker-compose: docker-compose up Once the servicses are running, you should be able to access http://127.0.0.1:5000. Solution The DO_NOT_ACCESS folder contains the solution when you checkout the solution branch with git checkout solution.    

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Advanced, Classification, NLP, Skilltest, Structured Data, Supervised, Text

Custom Text Classification on Android using TensorFlow Lite

This article was published as a part of the Data Science Blogathon Introduction A lot of social media platforms have been using AI these days to classify vulgar and offensive posts and automatically take them down. I thought why not try doing something similar; and so, I’ve come up with this end-to-end tutorial that will help you build your own corpus for training a text classification model, and later export and deploy it on an Android app for you to use. […]

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