Search Results for "2-plan" - Page 23
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Showing 3102 open source projects for "2-plan"
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Practice Python
Part of my daily plan for studying Python
practice-python provides a structured set of small, focused exercises aimed at building fluency with Python fundamentals. The tasks emphasize real coding over passive reading, nudging you to write, run, and iterate on solutions. Exercises commonly target strings, lists, dictionaries, control flow, functions, classes, and common algorithms, reinforcing idiomatic Python patterns. Many problems are intentionally minimal in boilerplate so you can concentrate on logic and clarity. The collection... -
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CleverHans
An adversarial example library for constructing attacks
This repository contains the source code for CleverHans, a Python library to benchmark machine learning systems' vulnerability to adversarial examples. You can learn more about such vulnerabilities on the accompanying blog. The CleverHans library is under continual development, always welcoming contributions of the latest attacks and defenses. In particular, we always welcome help with resolving the issues currently open. Since v4.0.0, CleverHans supports 3 frameworks: JAX, PyTorch, and TF2.... -
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Old Photo Restoration
Bringing Old Photo Back to Life (CVPR 2020 oral)
...Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the domain gap between synthetic images and real old photos makes the network fail to generalize. Therefore, we propose a novel triplet domain translation network by leveraging real photos along with massive synthetic image pairs. Specifically, we train two variational autoencoders (VAEs) to respectively transform old photos and clean photos into two latent spaces. And the translation between these two latent spaces is learned with synthetic paired data. This translation generalizes well to real photos because the domain gap is closed in the compact latent space. Besides, to address multiple degradations mixed in one old photo, we design a global branch with a partial nonlocal block targeting to the structured defects, such as scratches and dust spots. -
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U-Net Fusion RFI
U-Net for RFI Detection based on @jakeret's implementation
See original code here: https://github.com/jakeret/tf_unet Currently this project is based on Tensorflow 1.13 code base and there are no plans to transfer to TF version 2. The primary improvements to this code base include a training and evaluation framework, along with a fusion based approach to detection, combining a number of models (currently hard coded to two trained models) along with Sum Threshold as an additional "expert." Additional work is being done to add custom layers to this model for further experimentation, including Squeeze/Excitation layers (unimplemented.) ... -
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Pytago
A source-to-source transpiler for Python to Go translation
pytago is a source-to-source transpiler that converts some Python into human-readable Go. It enables developers to translate Python codebases into Go, facilitating migration or interoperability between the two languages. -
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bob-buildsystem
Software build system
bob is a Python3 based software build system roughly comparable with autotools + gmake or CMake + gmake. It is meant to overcome known shortcomings of the two. -
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VITS
Conditional Variational Autoencoder with Adversarial Learning
VITS is a foundational research implementation of “VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech,” a well-known neural TTS architecture. Unlike traditional two-stage systems that separately train an acoustic model and a vocoder, VITS trains an end-to-end model that maps text directly to waveform using a conditional variational autoencoder combined with normalizing flows and adversarial training. This architecture enables parallel generation (fast inference) while achieving speech quality that rivals or surpasses many two-stage systems. ... -
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SimSiam
PyTorch implementation of SimSiam
...The project introduces a minimalist approach to self-supervised learning that avoids negative pairs, momentum encoders, or large memory banks—key complexities of prior contrastive methods. SimSiam learns image representations by maximizing similarity between two augmented views of the same image through a Siamese neural network with a stop-gradient operation, preventing feature collapse. This elegant yet effective design achieves strong results in unsupervised learning benchmarks such as ImageNet without requiring contrastive losses. The repository provides scripts for both unsupervised pre-training and linear evaluation, using a ResNet-50 backbone by default. ... -
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Transformer TTS
Implementation of a Transformer based neural network
TransformerTTS is an implementation of a non-autoregressive Transformer-based neural network for text-to-speech, built with TensorFlow 2. It takes inspiration from architectures like FastSpeech, FastSpeech 2, FastPitch, and Transformer TTS, and extends them with its own aligner and forward models. The system separates alignment learning and acoustic modeling: an autoregressive Transformer is used as an aligner to extract phoneme-to-frame durations, while a non-autoregressive “ForwardTransformer” generates mel-spectrograms conditioned on text and durations. ... -
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AliceMind
ALIbaba's Collection of Encoder-decoders from MinD
...Pre-trained models for natural language understanding (NLU). We extend BERT to a new model, StructBERT, by incorporating language structures into pre-training. Specifically, we pre-train StructBERT with two auxiliary tasks to make the most of the sequential order of words and sentences, which leverage language structures at the word and sentence levels, respectively. Pre-trained models for natural language generation (NLG). We propose a novel scheme that jointly pre-trains an autoencoding and autoregressive language model on a large unlabeled corpus, specifically designed for generating new text conditioned on context. ... -
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Linux-reminders
A simple reminder Gui for Linux using wxpython
...The following types of reminder can be created: One off, at a specified date and time; every 15 minutes; every 30 minutes; every 45 minutes; every hour; daily; monthly; weekly; annually; last day of the month; penultimate day of the month; the 1st,2nd,3rd,4th or last Monday of the month; the 1st,2nd,3rd,4th or last Tuesday of the month; the 1st,2nd,3rd,4th or last Wednesday of the month; the 1st,2nd,3rd,4th or last Thursday of the month; the 1st,2nd,3rd,4th or last Friday of the month; the 1st,2nd,3rd,4th or last Saturday of the month; the 1st,2nd,3rd,4th or last Sunday of the month. All reminders are issued 2 minutes before the allotted time. All reminders can be “snoozed” even if they are One off. Reminders can be “snoozed” for 5 mins, 15 mins, 30 mins, 1 hour, 1 day or 1 week. Snoozed reminders can be re-snoozed. -
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DrQA
Reading Wikipedia to Answer Open-Domain Questions
DrQA is an open-domain question answering system that reads large text corpora—famously Wikipedia—to answer natural language questions with extractive spans. It follows a two-stage pipeline: a fast document retriever first narrows down candidate articles, and a neural machine reader then predicts the exact answer span from those passages. The retriever relies on classic IR features (like TF-IDF and n-gram statistics) to remain lightweight and scalable to millions of documents. The reader is a neural model trained on supervised QA data to estimate start and end positions within a paragraph, and it can be adapted to new domains through fine-tuning or distant supervision. ... -
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Hands-on Unsupervised Learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
...Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data. -
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Upscale
This program is upscaling any image by a factor 2 using an algorithm
This program is upscaling any image by a factor 2 using an algorithm of cubic interpolation. You may need to install the following libraries to run the program, tqdm, itertools, and OpenCV. -
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LoL Absent
Program to block League of Legends contacts.
...When you use it, you will appear offline and you will not be able to write in the picks and bans phase, but yes during the game. REQUIREMENTS: 1 - Windows 10 x64 or higher operative system. 2 - NET Framework 4.7.2 or higher. -
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kamiFaka
kamiFaka
...Has integrated Alipay face-to-face payment, WeChat official, Payjs, Hupijiao, YunGouOS, Yipay, Mugglepay, V visa-free and other more than a dozen payment interfaces. Ordinary users support email and SMS to receive messages. Administrators support email, SMS, TG, WeChat, QQ notifications. Support 2~4 layer wholesale mode. Long card password can be exported as txt text. A variety of theme modes [list, card, grid]. Support custom background, logo, contact information, etc. Support hot backup, one-click cloud backup, one-click export backup file to local. Detachable database, compatible with Mysql, PostgreSQL and Sqlite. -
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CRSLab
CRSLab is an open-source toolkit
...Comprehensive benchmark models and datasets: We have integrated commonly-used 6 datasets and 18 models, including graph neural network and pre-training models such as R-GCN, BERT and GPT-2. We have preprocessed these datasets to support these models, and release for downloading. Extensive and standard evaluation protocols: We support a series of widely-adopted evaluation protocols for testing and comparing different CRS. General and extensible structure: We design a general and extensible structure to unify various conversational recommendation datasets and models, in which we integrate various built-in interfaces and functions for quickly development. ... -
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TypeLines
Improved replacement for Fond of Writing (FOW)
Allows a dominant to set a task for a submissive, keeping him/ner busy and under control -
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Etchimaths (ALL categories)
This is a maths solving app and study guide for various levels..
Etchimaths is a Mathematics software, a helping tool for Mathematics simulation(solving) and study.It is a solving as well as a teaching software. It involves Mathematics programs at various levels of studies;they include: 1.Etchimaths(O'LEVEL) 2.Etchimaths(A'LEVEL) 3.Etchimaths(UNIVERSITY) 4.Etchimaths(BEPC/BEPC+1) 5.Etchimaths(BAC) 6.Etchimaths(UNIVERSITE) 7.Etchimaths(ULTIMATE) and more to come in future.. -
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Reminder
A simple reminder application
A simple reminder application to remind the users in a specified time interval given by the user. The reminding functionality will happen in two ways. 1. Remind Once: When user inputs the time in minutes and then click on "Remind Once", user will be reminded with a short sound after the specified time interval once. 2. Remind Continuously: When user inputs the time in minutes and then click on "Remind Continuously", user will be reminded with a short sound after every time interval specified continuously until the application is closed. ... -
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Tahafacex
It works as electronic book for keeping attendance records...
It works as electronic book for keeping attendance records using face identification\recognition technology it can mark attendance upto 100 person it can be used anywhere. MINOR CHANGE: Functionality improved MAJOR CHANGE: 1. Backup and Restore (For 1.1.0 and future versions only) 2. Export your attendance sheets in excel format of each class -
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WiFiSafe
Small utility software conceived to share WiFi connections between com
...Warning: the software will create two folders, "profiles" and "temp", do not remove those folders during use. The encrypted data will be stored within the profiles folder -
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pycassonne
Carcassonne clone written in python using pygame
...Computer player examines own her step only, so the analysation depth is only 1, trying to gain the maximum available extra points. Turning trace mode on it is possible to play against computer with ultra skill level, where the analysation depth is increased to 2. With this setting the AI is stronger but the gameplay is unbearable slow. It is just for test purpose. -
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dumb-init
A minimal init system for Linux containers
...However, omitting an init system often leads to incorrect handling of processes and signals, and can result in problems such as containers that can’t be gracefully stopped, or leaking containers that should have been destroyed. dumb-init is simple to use and solves many of these problems: you can just add it to the front of any container’s command, and it will take on the role of PID 1 for itself. It immediately spawns your process as PID ~2, and then proxies on any signals it receives. This helps to avoid special kernel behavior applied to PID 1, while also handling regular responsibilities of the init system (like reaping orphaned zombie processes). dumb-init is a simple process supervisor and init system designed to run as PID 1 inside minimal container environments (such as Docker). ...