Search Results for "ai made in python" - Page 69
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Showing 2075 open source projects for "ai made in python"
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TGAN
Generative adversarial training for generating synthetic tabular data
We are happy to announce that our new model for synthetic data called CTGAN is open-sourced. The new model is simpler and gives better performance on many datasets. TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid... -
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Mouse Mover
Mouse movement simulator made in Python
Mouse Mover is a Python application that can be used to simulate cursor movement. This project is heavily inspired by the infamous Mouse Jiggler application. One of the main purposes of using this application is to prevent screen saver or auto-lock in the case where you can't disable them. -
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Offensive Web Testing Framework
Offensive Web Testing Framework (OWTF), is a framework
OWASP OWTF is a project focused on penetration testing efficiency and alignment of security tests to security standards like the OWASP Testing Guide (v3 and v4), the OWASP Top 10, PTES and NIST so that pentesters will have more time to see the big picture and think out of the box. More efficiently find, verify and combine vulnerabilities. Have time to investigate complex vulnerabilities like business logic/architectural flaws or virtual hosting sessions. Perform more tactical/targeted... -
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PyTorch pretrained BigGAN
PyTorch implementation of BigGAN with pretrained weights
An op-for-op PyTorch reimplementation of DeepMind's BigGAN model with the pre-trained weights from DeepMind. This repository contains an op-for-op PyTorch reimplementation of DeepMind's BigGAN that was released with the paper Large Scale GAN Training for High Fidelity Natural Image Synthesis. This PyTorch implementation of BigGAN is provided with the pretrained 128x128, 256x256 and 512x512 models by DeepMind. We also provide the scripts used to download and convert these models from the... -
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NeuroNER
Named-entity recognition using neural networks
Named-entity recognition (NER) aims at identifying entities of interest in the text, such as location, organization and temporal expression. Identified entities can be used in various downstream applications such as patient note de-identification and information extraction systems. They can also be used as features for machine learning systems for other natural language processing tasks. Leverages the state-of-the-art prediction capabilities of neural networks (a.k.a. "deep learning") Is... -
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BCAW Tool
Bio Codon Analysis Workflow Tool
BCAWT was developed using python 3.7 with build in and third-party modules. The usage of BCAWT is made to be very easy where users have only to input a fasta format file containing genes to be analyzed, and a bunch of analysis will be performed with 23 different output files -
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Game Programmer
A Study Path for Game Programmer
Game Programmer is Milo Yip’s study path for people who want to become stronger game programmers. Rather than being a software library, it is a structured learning roadmap built around books and knowledge areas. The path covers computer science, programming languages, software development, mathematics, game programming, game engine development, computer graphics, audio, physics, animation, AI, and multiplayer networking. It helps learners understand the breadth of skills involved in serious... -
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Parcassonne
Carcassonne clone written in python 3
Carcassonne is classic board game. Parcassonne is Carcassonne clone written in python 3. This app(parcassonne) base on pycassonne 0.9.1. Parcassonne try to enhance AI, but it still very weak. So I suggest to 1 human vs 4 computer players. Pycassonne URL below: https://sourceforge.net/projects/pycassonne/ -
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Market Reporter
Automatic Generation of Brief Summaries of Time-Series Data
Market Reporter automatically generates short comments that describe time series data of stock prices, FX rates, etc. This is an implementation of Murakami et al. This tool stores data to Amazon S3. Ask the manager to give you AmazonS3FullAccess and issue a credential file. For details, please read AWS Identity and Access Management. Install Docker and Docker Compose. Edit envs/docker-compose.yaml according to your environment. Then, launch containers by docker-compose. We recommend to use... -
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Improved GAN
Code for the paper "Improved Techniques for Training GANs"
Improved-GAN is the official code release from OpenAI accompanying the research paper Improved Techniques for Training GANs. It provides implementations of experiments conducted on datasets such as MNIST, SVHN, CIFAR-10, and ImageNet. The project focuses on demonstrating enhanced training methods for Generative Adversarial Networks, addressing stability and performance issues that were common in earlier GAN models. The repository includes training scripts, evaluation methods, and pretrained... -
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InfoGAN
Code for reproducing key results in the paper
The InfoGAN repository contains the original implementation used to reproduce the results in the paper “InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets”. InfoGAN is a variant of the GAN (Generative Adversarial Network) architecture that aims to learn disentangled and interpretable latent representations by maximizing the mutual information between a subset of the latent codes and the generated outputs. That extra incentive encourages the... -
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Finetune Transformer LM
Code for "Improving Language Understanding by Generative Pre-Training"
finetune-transformer-lm is a research codebase that accompanies the paper “Improving Language Understanding by Generative Pre-Training,” providing a minimal implementation focused on fine-tuning a transformer language model for evaluation tasks. The repository centers on reproducing the ROCStories Cloze Test result and includes a single-command training workflow to run the experiment end to end. It documents that runs are non-deterministic due to certain GPU operations and reports a median... -
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SG2Im
Code for "Image Generation from Scene Graphs", Johnson et al, CVPR 201
sg2im is a research codebase that learns to synthesize images from scene graphs—structured descriptions of objects and their relationships. Instead of conditioning on free-form text alone, it leverages graph structure to control layout and interactions, generating scenes that respect constraints like “person left of dog” or “cup on table.” The pipeline typically predicts object layouts (bounding boxes and masks) from the graph, then renders a realistic image conditioned on those layouts.... -
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OpenSeq2Seq
Toolkit for efficient experimentation with Speech Recognition
OpenSeq2Seq is a TensorFlow-based toolkit for efficient experimentation with sequence-to-sequence models across speech and NLP tasks. Its core goal is to give researchers a flexible, modular framework for building and training encoder–decoder architectures while fully leveraging distributed and mixed-precision training. The toolkit includes ready-made models for neural machine translation, automatic speech recognition, speech synthesis, language modeling, and additional NLP tasks such as... -
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Commercial version of this app can be found at: https://www.controlboard.linkpc.net/ Buget friendly video control surface and PTZ solution integrated with Telestream Wirecast. This application transforms your keyboard into a video control surface for wirecast and your mouse into a PTZ joystick. For use with Wirecast (https://www.telestream.net/wirecast/overview.htm) and USB Pan Tilt Controller with Sony LANC (S-Link) interface (http://www.expelec.co.uk/pantilt/pantiltlanc.htm). This...
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Colonization Mod Collection
Several mods for Civilization IV: Colonization
A collection of mods for Civilization IV: Colonization. The purpose of joining multiple mods into a collection is to make them share the source code. This allows joined work without the time consuming and bug prone process of moving modpacks between source codes. This mean the source code is made up of multiple features, which can be tweaked by XML and as a result it is possible to make total conversion mods without knowing how to program. What this is NOT is a bunch of nearly... -
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glparchis
Parchis Game in OpenGL. GPL.
Parchis Game in OpenGL. It has GPL license. There are Linux and Windows versions. -
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Exposure
Learning infinite-resolution image processing with GAN and RL
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model. ACM Transactions on Graphics (presented at SIGGRAPH 2018) Exposure is originally designed for RAW photos, which assumes 12+ bit color depth and linear "RGB" color space (or whatever we get after demosaicing). jpg and png images typically have only 8-bit color depth (except 16-bit pngs) and the lack of information (dynamic range/activation resolution) may... -
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WebSrapper
Webscraping with UI
Hello , i have made this simple web scrapping tool so that one can have fun web scrapping with with ease . -
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ARK AR Sticker Generator
ARK is an AR Sticker Generator
In Augmented Reality Development we often need high quality markers for image targets compatible with accurate detection. ARK is an AR sticker generator made using various image processing libraries & scientific tools. It creates a colorful sticker similar to a QR code with each sticker being completely unique from other. It also allows to add an image overlay for branding or other stuff. Generated stickers can be found in Output folder. Extension is .png *GitHub Listing is in process* -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. Because it aggregates... -
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Universe Starter Agent
A starter agent that can solve a number of universe environments
The universe-starter-agent repository is an archived OpenAI codebase designed as a starter reinforcement-learning agent that can interact with and solve tasks in OpenAI’s Universe environment platform. Its purpose is to serve as a baseline or reference implementation so researchers or developers can see how to build agents that operate in real-time, visual environments (e.g., games, browser apps) via pixel observations and keyboard/mouse actions. Under the hood, this starter agent implements... -
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EvalAI
Evaluating state of the art in AI
EvalAI is an open-source platform for evaluating and comparing machine learning (ML) and artificial intelligence (AI) algorithms at scale. We allow the creation of an arbitrary number of evaluation phases and dataset splits, compatibility using any programming language, and organizing results in both public and private leaderboards. Certain large-scale challenges need special computing capabilities for evaluation. If the challenge needs extra computational power, challenge organizers can... -
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DC-TTS
TensorFlow Implementation of DC-TTS: yet another text-to-speech model
DC-TTS is a TensorFlow implementation of the DC-TTS architecture, a fully convolutional text-to-speech system designed to be efficiently trainable while producing natural speech. It follows the “Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention” paper, but the author adapts and extends the design to make it practical for real experiments. The model is split into two networks: Text2Mel, which maps text to mel-spectrograms, and SSRN... -
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TEACUP
TCP Experiment Automation Controlled Using Python
TEACUP automates many aspects of running TCP performance experiments in a specially-constructed physical testbed. TEACUP enables repeatable testing of different TCP algorithms over a range of emulated network path conditions, bottleneck rate limits and bottleneck queuing disciplines. TEACUP utilises a text-based configuration file to define experiments as combinations of parameters specifying desired network path and end host conditions. When multiple values are provided (e.g. for TCP...