Search Results for "python accounting source code" - Page 63

Showing 3110 open source projects for "python accounting source code"

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  • 1
    m2cgen

    m2cgen

    Transform ML models into a native code

    m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase...
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  • 2
    Real-ESRGAN ncnn Vulkan

    Real-ESRGAN ncnn Vulkan

    NCNN implementation of Real-ESRGAN

    Real-ESRGAN ncnn Vulkan is an optimized, cross-platform implementation of Real-ESRGAN using the ncnn neural network inference engine and Vulkan for hardware acceleration. Unlike the standard PyTorch-based Real-ESRGAN code, this variant is written in C/C++ and designed to run efficiently on many platforms (including Windows, Linux, and possibly Android) without requiring heavy frameworks like CUDA or Python. It provides command-line tools for upscaling images with selected models, allowing...
    Downloads: 52 This Week
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  • 3
    Mask2Former

    Mask2Former

    Code release for "Masked-attention Mask Transformer

    Mask2Former is a unified segmentation architecture that handles semantic, instance, and panoptic segmentation with one model and one training recipe. Its core idea is to cast segmentation as mask classification: a transformer decoder predicts a set of mask queries, each with an associated class score, eliminating the need for task-specific heads. A pixel decoder fuses multi-scale features and feeds masked attention in the transformer so each query focuses computation on its current spatial...
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  • 4
    Catalyst

    Catalyst

    Accelerated deep learning R&D

    Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make...
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  • 5
    DeeProtGO

    DeeProtGO

    DeeProtGO is a deep learning model for predicting GO terms of proteins

    This project contains the source code of DeeProtGO as well as an example of its use when predicting GO terms of the biological process sub-ontology for eukaryotic proteins.
    Downloads: 0 This Week
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  • 6
    Google Cloud Vision API examples

    Google Cloud Vision API examples

    Sample code for Google Cloud Vision

    The cloud-vision repository is a sample code collection for the Google Cloud Vision API that shows developers how to implement image analysis tasks across a wide range of languages and platforms. It contains examples organized by language and environment, including Go, Java, Node.js, PHP, Python, Ruby, .NET, Android, iOS, and even a Chrome extension, which makes it especially valuable as a cross-platform learning resource. The repository demonstrates concrete image understanding use cases,...
    Downloads: 0 This Week
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  • 7
    TensorFlowOnSpark

    TensorFlowOnSpark

    TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters

    By combining salient features from the TensorFlow deep learning framework with Apache Spark and Apache Hadoop, TensorFlowOnSpark enables distributed deep learning on a cluster of GPU and CPU servers. It enables both distributed TensorFlow training and inferencing on Spark clusters, with a goal to minimize the amount of code changes required to run existing TensorFlow programs on a shared grid.
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  • 8
    The Pythonizer

    The Pythonizer

    Converts a Java program to the equivalent Python program

    An automatic source-code converter (transcompiler) that converts a valid Java program to the equivalent Python program. Uses Python naming conventions and indentation convention.
    Downloads: 0 This Week
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  • 9
    Unet

    Unet

    Source code for unet-pytorch, which can train its own model

    Unet-pytorch is a PyTorch implementation of U-Net for semantic segmentation workflows. The repository is built around training, prediction, and mIoU evaluation for VOC-style segmentation data and medical-style datasets. It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes...
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  • 10
    Jupyter Dash

    Jupyter Dash

    Dash v2.11+ has Jupyter support built in

    Dash 2.11 and later supports running Dash apps in classic Jupyter Notebooks and in JupyterLab without the need to update the code or use the additional JupyterDash library. If you are using an earlier version of Dash, you can run Dash apps in a notebook using JupyterDash. This page documents additional options available when running Dash apps in notebooks as well as troubleshooting information.
    Downloads: 0 This Week
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  • 11
    EasyNLP

    EasyNLP

    EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit

    EasyNLP is an easy-to-use NLP development and application toolkit in PyTorch, first released inside Alibaba in 2021. It is built with scalable distributed training strategies and supports a comprehensive suite of NLP algorithms for various NLP applications. EasyNLP integrates knowledge distillation and few-shot learning for landing large pre-trained models, together with various popular multi-modality pre-trained models. It provides a unified framework of model training, inference, and...
    Downloads: 0 This Week
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  • 12
    RQ-Transformer

    RQ-Transformer

    Implementation of RQ Transformer, autoregressive image generation

    Implementation of RQ Transformer, which proposes a more efficient way of training multi-dimensional sequences autoregressively. This repository will only contain the transformer for now. You can use this vector quantization library for the residual VQ. This type of axial autoregressive transformer should be compatible with memcodes, proposed in NWT. It would likely also work well with multi-headed VQ. I also think there is something deeper going on, and have generalized this to any number of...
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  • 13
    LayoutParser

    LayoutParser

    A Unified Toolkit for Deep Learning Based Document Image Analysis

    With the help of state-of-the-art deep learning models, Layout Parser enables extracting complicated document structures using only several lines of code. This method is also more robust and generalizable as no sophisticated rules are involved in this process. A complete instruction for installing the main Layout Parser library and auxiliary components. Learn how to load DL Layout models and use them for layout detection. The full list of layout models currently available in Layout Parser....
    Downloads: 0 This Week
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  • 14
    bert4keras

    bert4keras

    Keras implement of transformers for humans

    Our light reimplementation of bert for keras. 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...
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  • 15
    billing-equipment-repair

    billing-equipment-repair

    A billing APP for Equipment Sales/Repair Shops written in MS-Access.

    If you are selling and/or repairing equipment you want to track (like computers, tractors, boats, snowmobiles, TV's, dishwashers or other things like that), this might be a good app for you. It should give you practice in learning/use of Invoicing, and installing on the desktop, and programming in vba and MS-Access. Note that the free MS-Access Runtime is with the download . You need MS-Access if you want to work with the program code (part of Office 365). The program processes Invoicing,...
    Downloads: 1 This Week
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  • 16
    OhMyForm

    OhMyForm

    Free open source alternative to TypeForm, TellForm, or Google Forms

    Create stunning embeddable forms for recruiting, market research, surveys and more. With OhMyForm you'll get all the features you need to run, administer, analyze and distribute forms for free. With our opensource community, OhMyForm is always improving and is vetted by top programming experts around the world, ensuring that our code is top-notch, eliminating potential bugs and errors.
    Downloads: 0 This Week
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  • 17
    Awesome Conformal Prediction

    Awesome Conformal Prediction

    A professionally curated list of awesome Conformal Prediction videos

    awesome-conformal-prediction is a curated “awesome list” repository on GitHub collecting high-quality resources related to conformal prediction: tutorials, books, papers, theses, open-source libraries, videos, and other educational material. It is not a software library itself but a directory of resources for those wanting to learn or work with conformal prediction and uncertainty quantification. This exceptional resource is the culmination of my PhD journey in Machine Learning, specializing...
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  • 18
    Cica
    Japanese monospaced font Cica for programming. A monospaced Japanese font for programming, adjusted after synthesizing the following fonts. Hack + DejaVu Sans Mono for alphanumeric characters and symbols. Rounded Mgen+ for other characters. Nerd Fonts (= Powerline patch, others applied. Pomicons excluded*) Noto Emoji. Icons for Devs. Various adjustments forked from the Ricty generator. mShorten the middle bar as a unique adjustment (easy rnto mdistinguish & a little cute). Supports tmux...
    Downloads: 1 This Week
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  • 19
    GLIDE (Text2Im)

    GLIDE (Text2Im)

    GLIDE: a diffusion-based text-conditional image synthesis model

    glide-text2im is an open source implementation of OpenAI’s GLIDE model, which generates photorealistic images from natural language text prompts. It demonstrates how diffusion-based generative models can be conditioned on text to produce highly detailed and coherent visual outputs. The repository provides both model code and pretrained checkpoints, making it possible for researchers and developers to experiment with text-to-image synthesis. GLIDE includes advanced techniques such as...
    Downloads: 3 This Week
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  • 20
    CIPS-3D

    CIPS-3D

    3D-aware GANs based on NeRF (arXiv)

    3D-aware GANs based on NeRF (arXiv). This repository contains the code of the paper, CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis. The problem of mirror symmetry refers to the sudden change of the direction of the bangs near the yaw angle of pi/2. We propose to use an auxiliary discriminator to solve this problem. Note that in the initial stage of training, the auxiliary discriminator must dominate the generator more than the main discriminator...
    Downloads: 0 This Week
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  • 21
    authoscope

    authoscope

    Scriptable network authentication cracker (formerly `badtouch`)

    authoscope is a scriptable network authentication cracker. While the space for common service bruteforce is already very well saturated, you may still end up writing your own python scripts when testing credentials for web applications. The scope of authoscope is specifically cracking custom services. This is done by writing scripts that are loaded into a lua runtime. Those scripts represent a single service and provide a verify(user, password) function that returns either true or false....
    Downloads: 0 This Week
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  • 22
    YOLOv3

    YOLOv3

    Object detection architectures and models pretrained on the COCO data

    Fast, precise and easy to train, YOLOv5 has a long and successful history of real time object detection. Treat YOLOv5 as a university where you'll feed your model information for it to learn from and grow into one integrated tool. You can get started with less than 6 lines of code. with YOLOv5 and its Pytorch implementation. Have a go using our API by uploading your own image and watch as YOLOv5 identifies objects using our pretrained models. Start training your model without being an...
    Downloads: 16 This Week
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  • 23
    CodeSearchNet

    CodeSearchNet

    Datasets, tools, and benchmarks for representation learning of code

    CodeSearchNet is a large-scale dataset and research benchmark designed to advance the development of systems that retrieve source code using natural language queries. The project was created through collaboration between GitHub and Microsoft Research and aims to support research on semantic code search and program understanding. The dataset contains millions of pairs of source code functions and corresponding documentation comments extracted from open-source repositories. ...
    Downloads: 0 This Week
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  • 24
    Kalliope

    Kalliope

    Kalliope is a framework to create your own personal assistant

    Kalliope is a modular always-on voice-controlled personal assistant designed for home automation. Kalliope is a framework that will help you to create your own personal assistant. The concept is to create the brain of your assistant by attaching an input signal (vocal order, scheduled event, MQTT message, GPIO event, etc..) to one or multiple actions called neurons. You can create your own Kalliope bot, by simply choosing and composing the existing neurons without writing any code. But, if...
    Downloads: 1 This Week
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  • 25
    Machine Learning PyTorch Scikit-Learn

    Machine Learning PyTorch Scikit-Learn

    Code Repository for Machine Learning with PyTorch and Scikit-Learn

    Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing...
    Downloads: 3 This Week
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