Search Results for "clean" - Page 8
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Showing 280 open source projects for "clean"
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1
AnimeGAN
A simple PyTorch Implementation of Generative Adversarial Networks
...The images are generated from a DCGAN model trained on 143,000 anime character faces for 100 epochs. Manipulating latent codes enables the transition from images in the first row to the last row. The images are not clean, some outliers can be observed, which degrades the quality of the generated images. Anime-style images of 126 tags are collected from danbooru.donmai.us using the crawler tool gallery-dl. The images are then processed by an anime face detector python-anime face. The resulting dataset contains ~143,000 anime faces. Note that some of the tags may no longer be meaningful after cropping, i.e. the cropped face images under the 'uniform' tag may not contain visible parts of uniforms. -
2
ConvNeXt
Code release for ConvNeXt model
...It revisits classic ResNet-style backbones through the lens of transformer design trends—large kernel sizes, inverted bottlenecks, layer normalization, and GELU activations—to bridge the performance gap between convolutions and attention-based models. ConvNeXt’s clean, hierarchical structure makes it efficient for both pretraining and fine-tuning across a wide range of visual recognition tasks. It achieves competitive or superior results on ImageNet and downstream datasets while being easier to deploy and train than transformers. The repository provides pretrained models, training recipes, and ablation studies demonstrating how incremental design choices collectively yield state-of-the-art performance. -
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SimpleTextFormatter
STF automatically generates documentation
STF is a system of automatically generating documentation under control of a program or a script. It is frequently used to automatically generate test reports. STF is also used to clean up the output of a process and turn it into a nice looking report. -
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Texar-PyTorch
Integrating the Best of TF into PyTorch, for Machine Learning
Texar-PyTorch is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar-PyTorch was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror... -
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5
FastClicker
Autoclicker to set your dynamic cursor locations and number of clicks
An application with a predefined template to set your dynamic cursor locations or at a prespecified location. The maximum number of clicks can also be set. -
6
bert4keras
Keras implement of transformers for humans
...A cleaner, lighter version of bert for keras. This is the keras version of the transformer model library re-implemented by the author and is committed to combining transformer and keras with as clean code as possible. The original intention of this project is for the convenience of modification and customization, so it may be updated frequently. Load the pre-trained weights of bert/roberta/albert for fine-tune. Implement the attention mask required by the language model and seq2seq. Pre-training code from zero (supports TPU, multi-GPU, please see pertaining). ... -
7
JumbleGame
A word puzzle game with a set of words scrambled.
A word puzzle game with a set of words, each of which is “jumbled” or scrambled. A solver answers the scrambled word with the correct word, and can also request for a hint -
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GANformer
Generative Adversarial Transformers
This is an implementation of the GANformer model, a novel and efficient type of transformer, explored for the task of image generation. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linearly efficiency, that can readily scale to high-resolution synthesis. The model iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of... -
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Automation Orchestrator
Automation Orchestrator application to orchestrate digital processes
...The Automation Orchestrator is tested with and supports Nintex RPA version = 15.1. As described on the official Django project site, it "is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Built by experienced developers, it takes care of much of the hassle of Web development, so you can focus on writing your app without needing to reinvent the wheel. It’s free and open source." The purpose of the Automation Orchestrator is to offer a well-functioning, fully customizable web server application to trigger and schedule scripts. ... -
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10
VoiceFixer
General Speech Restoration
VoiceFixer is a machine-learning framework for “speech restoration”: given a degraded or distorted audio recording — with noise, clipping, low sampling rate, reverberation, or other artifacts — it attempts to recover high-fidelity, clean speech. The architecture works in two stages: first an analysis stage that tries to extract “clean” intermediate features from the noisy audio (e.g. removing noise, denoising, dereverberation, upsampling), and then a neural vocoder-based synthesis stage that reconstructs a high-quality waveform from those features. Unlike many single-purpose noise reduction tools, VoiceFixer targets a “general speech restoration” problem (GSR), capable of handling multiple types of distortions at once, which makes it suitable for old recordings, phone-call audio, amateur voice recordings, or archival media. ... -
11
Rescatux
Easy to use Repair distribution for both Gnu/Linux and Windows systems
Rescatux is a GNU/Linux repair cd (and eventually also Windows) but it is not like other rescue disks. Rescatux comes with Rescapp. Rescapp is a nice wizard that will guide you through your rescue and repair tasks. When the wizard is not able to solve your problem you can also enjoy of Rescatux unique support features: * Chat: Open the chat for asking help directly in Rescatux channel. * Share log: After running an option you can share its log (the action registry that it has done) so... -
12
qiji-font
Typeface from Ming Dynasty woodblock printed books
...Manually lay a grid on top of each page to generate bounding boxes for characters (potentially replaceable by an automatic corner-detection algorithm). Generate a low-poly mask for each character on the grid, and save the thumbnails (using OpenCV). First, red channel is subtracted from the grayscale, in order to clean the annotations printed in red ink. Next, the image is thresholded and fed into the contour-tracing algorithm. A metric is then used to discard shapes that are unlikely to be part of the character in interest. -
13
Tez
Tez is a super-simple and lightweight Trainer for PyTorch
Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch. tez (तेज़ / تیز) means sharp, fast & active. This is a simple, to-the-point, library to make your PyTorch training easy. This library is in early-stage currently! So, there might be breaking changes. Currently, tez supports cpu, single gpu and multi-gpu & tpu training. More coming soon! Using tez is super-easy. We don't want you to... -
14
Forge Auto Clicker
Fully Customisable and Super Fast Free Auto Clicker. Free Updates.
Fully Customisable and Super Fast Free auto clicker. Fully-fledged with many modes of automatic clicking. Change click speed, cursor position, hotkeys and more with all settings saved. Forge Auto Clicker brings new, never seen before features to auto clicking. The AutoClicker is fully customizable with many useful functions as well as being easy to use, fast and free! As well as this, Forge Auto Clicker comes with no ads or malware making an amazing user experience! Use this... -
15
TRFL
TensorFlow Reinforcement Learning
...The library is designed to integrate seamlessly with TensorFlow, allowing users to define differentiable RL objectives and train models using standard optimization routines. TRFL supports both CPU and GPU TensorFlow environments, though TensorFlow itself must be installed separately. It exposes clean, modular APIs for various RL methods including Q-learning, policy gradient, and actor-critic algorithms, among others. Each function returns not only the computed loss tensor but also a detailed structure containing auxiliary information like TD errors and targets. -
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ReinventCommunity
Jupyter Notebook tutorials for REINVENT 3.2
This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2. -
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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... -
18
Old Photo Restoration
Bringing Old Photo Back to Life (CVPR 2020 oral)
...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. -
19
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. -
20
PyCls
Codebase for Image Classification Research, written in PyTorch
pycls is a focused PyTorch codebase for image classification research that emphasizes reproducibility and strong, transparent baselines. It popularized families like RegNet and supports classic architectures (ResNet, ResNeXt) with clean implementations and consistent training recipes. The repository includes highly tuned schedules, augmentations, and regularization settings that make it straightforward to match reported accuracy without guesswork. Distributed training and mixed precision are first-class, enabling fast experiments on multi-GPU setups with simple, declarative configs. ... -
21
Denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)
Denoiser is a real-time speech enhancement model operating directly on raw waveforms, designed to clean noisy audio while running efficiently on CPU. It uses a causal encoder-decoder architecture with skip connections, optimized with losses defined both in the time domain and frequency domain to better suppress noise while preserving speech. Unlike models that operate on spectrograms alone, this design enables lower latency and coherent waveform output. -
22
googler
Google from the terminal
...For example, fetch any number of results or start anywhere, limit the search by any duration, define aliases to google search any number of websites, and switch domains easily, all of this in a very clean interface without ads or stray URLs. The shell completion scripts make sure you don't need to remember any options. -
23
molten
A minimal, extensible, fast and productive framework
...Schemas are PEP484-compatible, which means mypy and molten go hand-in-hand, making your code more easy to maintain. Schema instances are automatically serializable and you can pick and choose which fields to exclude from responses and requests. Write clean, decoupled code by leveraging DI. Define components for everything from settings to DB access and business logic, test them in isolation and swap them out as needed. Here we’ve declared a Todo manager whose job it is to store and load Todos in the DB. In order for handlers to be able to request manager instances from the DI system, we also define a component that knows how and when to instantiate a TodoManager. -
24
googler
Google Search, Google Site Search, Google News from the terminal
...For example, fetch any number of results or start anywhere, limit search by any duration, define aliases to google search any number of websites, switch domains easily... all of this in a very clean interface without ads or stray URLs. The shell completion scripts make sure you don't need to remember any options. googler isn't affiliated to Google in any way. Demo: https://asciinema.org/a/85019 -
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CC-Net
Tools to download and cleanup Common Crawl data
cc_net provides tools to download, segment, clean, and filter Common Crawl to build large-scale text corpora, including monolingual datasets and the multilingual CC-100 collection introduced in the associated paper. It includes pipelines to fetch snapshots, extract text, de-duplicate, identify language, and apply quality filtering based on heuristics and language models. The outputs are intended for pretraining language models and for creating standardized corpora that can be reproduced or updated with new crawls. ...