Search Results for "space invaders python" - Page 7
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Showing 415 open source projects for "space invaders python"
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Train Invaders
Jupyter Notebook + Space Invaders
Training a model can be a long long process. In the meantime, have a bit of fun with a competitive space invaders game. See if you can get your name to the top of the leaderboard. -
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BINPython
Lightweight and small portable Python, build with pyinstaller
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videohash
The Python package for near duplicate video detection
Videohash is a Python library for detecting near-duplicate videos (Perceptual Video Hashing). Any video input can be used to generate a 64-bit equivalent hash value with this package. The video-hash-values for identical or near-duplicate videos are the same or similar, implying that if the video is resized (upscaled/downscaled), transcoded, watermark added/removed, stabilized, color changed, frame rate changed, changed aspect ratio, slightly cropped, black-bars added or removed, the... -
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Voice Cloning App
A Python/Pytorch app for easily synthesising human voices
A Python/Pytorch app for easily synthesizing human voices. If you are using a language other than English you can add it to the app. Firstly, you'll need to find a deep speech model for your language by going to coqui. You'll then need to download the model.pbmm and alphabet.txt files for your language. Requires Windows 10 or Ubuntu 20.04+ operating system, 5GB+ Disk space, and NVIDIA GPU with at least 4GB of memory & driver version 456.38+ (optional). -
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raspberry-gpio-python
A Python module to control the GPIO on a Raspberry Pi
...This is planned for the near future - watch this space! -
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Model Search
Framework that implements AutoML algorithms
Model Search is an AutoML research system for discovering neural network architectures with minimal human intervention. Instead of hand-crafting models, you define a search space and objectives, then the system explores candidate architectures using controllers and population-based strategies. It supports multiple tasks (such as vision or text) by letting you express reusable building blocks—layers, cells, and topologies—that the search can recombine. Training, evaluation, and promotion of... -
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Smart Contract Sanctuary
A home for ethereum smart contracts
A home for Ethereum smart contracts verified on Etherscan. This is the index repository for the smart contract sanctuary. Bookmark this repo. Chain-specific sub-repos and the index are updated twice a day. Expect a full, recursive check-out to take 2GB+ disk space. Existing repository but submodules never initialized - checkout submodules and update all chain-specific sub repositories. Contains smart contract sources for various networks, grouped by the first two chars of the contract... -
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IdleX - IDLE Extensions for Python
IDLE Extensions
A collection of extensions for Python's IDLE, the Python IDE built with the tkinter GUI toolkit. -
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Available Subnet Finder
A Python Script to find unused subnets
...This script is designed to provide a way to find available subnets within a given supernet. For example, if you want to find all the available /19 networks available within your 10.0.0.0/8 space, you could feed this subnet all your known networks, and it will give you subnets which are not used. This can be used as a module to another Python script, or independently. Help available on within the interactive shell via help() or via cli via -h. -
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Paperless-ng
A supercharged version of paperless, scan, index and archive docs
Paperless is a simple Django application running in two parts, a Consumer (the thing that does the indexing) and a Web server (the part that lets you search & download already-indexed documents). Paper is a nightmare. Environmental issues aside, there’s no excuse for it in the 21st century. It takes up space, collects dust, doesn’t support any form of a search feature, indexing is tedious, it’s heavy and prone to damage & loss. I wrote this to make “going paperless” easier. I do not have to... -
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Old Photo Restoration
Bringing Old Photo Back to Life (CVPR 2020 oral)
We propose to restore old photos that suffer from severe degradation through a deep learning approach. 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... -
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MurExpo
Software to create an exhibition wall and hang artworks on it.
This application provides exhibition walls on which you can hang artworks (works by visual artists, student work, ...) in order to put them in a situation as in an exhibition hall. It's not software that uses 3D technology, but rather a layer-based device that you load and move around as you please. Once arranged, the works can be framed live on the wall and the exhibition space can be decorated with objects and characters. This tool is aimed at people who need to do artwork simulations /... -
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Texthero
Text preprocessing, representation and visualization from zero to hero
Texthero is a python package to work with text data efficiently. It empowers NLP developers with a tool to quickly understand any text-based dataset and it provides a solid pipeline to clean and represent text data, from zero to hero. -
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Nerfies
This is the code for Deformable Neural Radiance Fields
Nerfies demonstrates deformation-aware neural radiance fields that reconstruct and render dynamic, real-world scenes from casual video. Instead of assuming a static world, the method learns a canonical space plus a deformation field that maps changing poses or expressions back to that space during training. This lets the system generate photorealistic novel views of nonrigid subjects—faces, bodies, cloth—while preserving fine detail and consistent lighting. The training pipeline handles... -
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vae
Simple vae and cvae from keras
vae is a collection of Keras experiments implementing variational autoencoders and related generative models. It includes simple VAE and conditional VAE examples along with several alternative architectures. Separate scripts explore CelebA image generation, convolutional VAEs, clustering-oriented variants, hyperspherical latent spaces, and vector-quantized autoencoders. The repository includes sample output from a CelebA training run as a visual reference. Its documented environment uses... -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network to... -
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gym-pybullet-drones
PyBullet Gymnasium environments for multi-agent reinforcement
Gym-PyBullet-Drones is an open-source Gym-compatible environment for training and evaluating reinforcement learning agents on drone control and swarm robotics tasks. It leverages the PyBullet physics engine to simulate quadrotors and provides a platform for studying control, navigation, and coordination of single and multiple drones in 3D space. -
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Brain AutoML
Google Brain AutoML
This repository contains a list of AutoML related models and libraries. Google Brain researchers have introduced a new way of programming automated machine learning (AutoML) based on symbolic programming. The researchers also proposed PyGlove, a general symbolic programming library for Python, to implement the symbolic formulation of AutoML. AutoML, designed to fill the machine learning industry’s talent gap, is gaining traction among various organizations. -
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Space Grotesk
Space Grotesk: a proportional variant of the original fixed-width
...Tools are all python based. Space Grotesk is licensed under the SIL Open Font License v1.1, see OFL.txt for details. -
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Pipeline for training Language Models
Pipeline for training Language Models using PyTorch.
Pipeline for training Language Models using PyTorch. Inspired by Yandex Data School NLP Course (week 03: Language Modeling) Prepared text file with space-separated words on each line. -
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3d Linear Transformation Visualization
Visualize 3d linear transformations.
A linear transformation is a function from one vector space to another that respects the linear structure of each vector space. For visualizing this we can transform a vector, but it has an obvious problem, because the linear transformation transform the whole space, not just the vector, in other words it transforms the basis vectors thus every vector in the space gets transformed too. That's why i created this app so everyone can see how a transformation matrix change the whole space. -
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ALAE
Adversarial Latent Autoencoders
ALAE (Adversarial Latent Autoencoders) is a deep learning research implementation that combines autoencoders with generative adversarial networks to produce high-quality image synthesis models. The project implements the architecture introduced in the CVPR research paper on Adversarial Latent Autoencoders, which focuses on improving generative modeling by learning latent representations aligned with adversarial training objectives. Unlike traditional GANs that directly generate images from... -
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NuclearThroneStreamer
Live stats for Nuclear Throne
NuclearThroneStreamer is a tiny multi-platform tool that is used to show current game stats while you play the Steam version of Nuclear Throne. This is useful for streamers who need to fill in the border space in the game. Click on Files above to download it and see the Readme. -
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Lenia
Lenia - Mathematical Life Forms
Lenia is a 2D cellular automaton with continuous space, time, and states. It produces a huge variety of interesting life forms. There are various versions available. Python, Matlab, and web (JavaScript) versions are real-time, interactive, and equipped with statistics tools. Jupyter and R versions are non-interactive and just for demonstration purposes. -
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OpenAI Glow
Copy code in "Glow: Generative Flow with Invertible 1x1 Convolutions"
Glow is an open source generative model released by OpenAI that demonstrates flow-based generative modeling techniques. Unlike models that rely on approximate inference, Glow uses invertible transformations to directly learn the data distribution, allowing for exact likelihood computation and efficient sampling. The model is capable of producing high-quality synthetic images while maintaining interpretable latent spaces that enable meaningful manipulation of generated outputs. Glow’s...
