Showing 8 open source projects for "code analysis"

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  • 1
    Yandex Music API

    Yandex Music API

    Non-official Python library for works with API service Index

    This library provides Python interface for anyone undocumented and self-made API Yandex Music. It is compatible with Python 3.7 + and supports working with both synchronous and asyncio code. In addition to implementing a clean API, this library has a number of — high-level wrapping classes in order to make the development of customers and scripts simple and understandable. All documentation was written from scratch based on logical analysis during reverse development (reverse engineering) API.
    Downloads: 2 This Week
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  • 2
    fvcore

    fvcore

    Collection of common code shared among different research projects

    fvcore is a lightweight utility library that factors out common performance-minded components used across Facebook/Meta computer-vision codebases. It provides numerics and loss layers (e.g., focal loss, smooth-L1, IoU/GIoU) implemented for speed and clarity, along with initialization helpers and normalization layers for building PyTorch models. Its common modules include timers, logging, checkpoints, registry patterns, and configuration helpers that reduce boilerplate in research code. A...
    Downloads: 0 This Week
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  • 3
    quantitative

    quantitative

    Quantized transactions python3

    The “quantitative” repository by Jack-Cherish is a tutorial-style codebase for quantitative trading written in Python — essentially a learning resource that guides users through building algorithmic trading strategies step by step. It’s organized as a sequence of lessons (lesson1, lesson2, etc.), making it approachable for learners who want to understand both theory and practice in quantitative finance. The repo is evidently tied to a popular video series (on Bilibili) that reportedly drew...
    Downloads: 0 This Week
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  • 4
    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.
    Downloads: 0 This Week
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  • 5
    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...
    Downloads: 0 This Week
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  • 6
    BMC

    BMC

    Notes on Scientific Computing for Biomechanics

    This repository is a collection of lecture notes and code on scientific computing and data analysis for Biomechanics and Motor Control.
    Downloads: 0 This Week
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  • 7
    earthengine-py-notebooks

    earthengine-py-notebooks

    A collection of 360+ Jupyter Python notebook examples

    ...Users can quickly adapt the examples for their own remote sensing, environmental monitoring, or spatial data science projects, and can run the code in environments like Google Colab.
    Downloads: 0 This Week
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  • 8
    fastNLP

    fastNLP

    fastNLP: A Modularized and Extensible NLP Framework

    fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models (covering tasks such as Chinese word segmentation, named entity recognition, syntactic analysis, text classification, text matching, metaphor resolution, summarization, etc.). ...
    Downloads: 0 This Week
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