Search Results for "sarvesh-project" - Page 53
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Showing 3486 open source projects for "sarvesh-project"
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Steam Career
Generate webpages of your Steam player data
Python application which uses the Steam Web API to retrieve player data and present an overview in HTML form. This project is not endorsed in any way by Valve Corporation. -
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DeepSpeech
Open source embedded speech-to-text engine
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. A pre-trained English model is available for use and can be downloaded following the instructions in the usage docs. If you want to use the pre-trained English model for performing speech-to-text, you can download it (along with other important inference material) from the DeepSpeech releases page. -
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Upscale
This program is upscaling any image by a factor 2 using an algorithm
This program is upscaling any image by a factor 2 using an algorithm of cubic interpolation. You may need to install the following libraries to run the program, tqdm, itertools, and OpenCV. -
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Denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)
...The implementation includes data augmentation techniques applied to the raw waveforms (e.g. noise mixing, reverberation) to improve model robustness and generalization to diverse noise types. The project supports both offline denoising (batch inference) and live audio processing (e.g. via loopback audio interfaces), making it practical for real-time use in calls or recording. The codebase includes training and evaluation scripts, configuration management via Hydra, and pretrained models on standard noise datasets. -
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Pension-Calculator
A simple retirement benefit calculator app written in python with GUI.
A simple retirement benefit calculator app written in python with GUI specifically for West Bengal State Govt. employees (India). This app is not associated with Govt. of West Bengal. This app is for informational purpose only. This project is open source under GNU public license v3.0 -
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MetaHash
#MetaHash is a next-generation network based on the Blockchain 4.0
#MetaHash is a next-generation network based on the Blockchain 4.0 technology for sharing digital assets and a platform for creating and managing decentralized apps and services in real-time. The #MetaHash project implements a solution that simultaneously possesses all the qualities of Blockchain new generation, namely: - Decentralization, which ensures absolute trust of users to the network; - Full synchronization, thanks to which each user has instant access to the most relevant data; - А transaction speed of up to 3 seconds, which provides unconditional ease of system using and a guarantee of the full operation of decentralized applications; - High bandwidth, which allows the network to keep transaction prices low due to the fact that a similar amount of resources can confirm more transactions per unit time; - Low commissions, due to which a huge number of potential customers will be interested in using the network for transfer and storage of payment means and technical data -
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pyment
Format and convert Python docstrings and generates patches
...It is useful for code not well documented, or code without docstrings, or some not yet or partially documented code, or a mix of all of this. It can be helpful also to harmonize or change a project docstring style format. It will parse one or several python scripts and retrieve existing docstrings. Then, for all found functions/methods/classes, it will generate formatted docstrings with parameters, default values. At the end, patches can be generated for each file. Then, man can apply the patches to the initial scripts. It is also possible to update the files directly without generating patches, or to output on stdout. ... -
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Sar2html is web based frontend for performance monitoring. It converts sar binary data to graphical format and keep historical data in it's database. Project homepage is here: https://github.com/cemtan/sar2html.git Supported Operating Systems: HPUX 11.11, 11.23, 11,31 Solaris 5.9, 5.10, 5.11 Redhat 3, 4, 5, 6, 7 Suse 8, 9, 10, 11, 12 Ubuntu 18, 20 If you have customers facing performance problems on operating systems listed above you may send sar2ascii to collect performance data. ...
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Data Science Notes
Curated collection of data science learning materials
Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. Because it aggregates topics in one place, learners can move linearly or jump into specific areas as needed during projects. The notes also highlight common pitfalls and good practices, which helps beginners adopt professional habits early. ... -
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TA-Lib.git: Technical Analysis Library
Mirror of the TA-Lib project using a Git repository
This project is intended to provide Git access to the code of the original project, TA-Lib, which uses Subversion. It is intended for system integrators wishing to use TA-Lib in their Git-managed project through Git submodules or subtrees. No actual development is being done here; all development happens in the original project. -
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nbdev template
Template for nbdev projects
Write, test, document, and distribute software packages and technical articles, all in one place, your notebook. Traditional programming environments throw away the result of your exploration in REPLs or notebooks. nbdev makes exploration an integral part of your workflow, all while promoting software engineering best practices. -
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MachineLearningStocks
Using python and scikit-learn to make stock predictions
MachineLearningStocks is a Python-based template project that demonstrates how machine learning can be applied to predicting stock market performance. The project provides a structured workflow that collects financial data, processes features, trains predictive models, and evaluates trading strategies. Using libraries such as pandas and scikit-learn, the repository shows how historical financial indicators can be transformed into machine learning features. -
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BBQLinux
An Arch based Linux distribution for Android developers
BBQLinux is a user-friendly Linux distribution made for Android developers. It has everything on board to build AOSP or AOSP-based Distributions like CyanogenMod. BBQLinux is based on Arch Linux and is using a Rolling Release Development Model which means it’s getting continually updated and upgraded. It will never be necessary to re-install a later release of BBQLinux. BBQLinux is fully compatible with Arch Linux and is using the same package repos. -
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BerryNet
Deep learning gateway on Raspberry Pi and other edge devices
This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. -
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cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data.
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Minecraft
Simple Minecraft-inspired program using Python and Pyglet
Minecraft is a simple Minecraft-inspired demo written in Python using the Pyglet library for windowing, input, and OpenGL rendering. The project implements a first-person block world where you can walk around, jump, fly, and place or remove blocks using a small set of block types like brick, grass, and sand. It provides full WASD movement with mouse look and basic building controls, giving a surprisingly complete “sandbox” feel in only a small amount of Python code. The author explicitly describes a vision for the project as an educational tool: because many kids love Minecraft and Python is a friendly first programming language, the codebase is meant to be readable, hackable, and heavily commented so learners can tweak parameters like gravity or walking speed and see the effects immediately. ... -
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The purpose of the SynCE project is to provide a means of communication with a Windows CE or Pocket PC device from a computer running Linux, *BSD or other unices.
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APTOS is an open source Apt translator project. It consists of several CAM applications, based on the Apt programming language. It is used to create control programs for cnc mills, lathes, water jets, lasers, and other industrial equipment.
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... • You will be able to convert your Python programs to .exe format with the pyinstaller method in the criteria you want. • You can quickly set up a virtual environment in your project, test it in a virtual environment, load modules and assist in the development phase of your project. It will be added with updates.
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OpenVCT
The Open-Source Virtual Clinical Trial Project
The OpenVCT project is designed to provide a common platform for performing Virtual Clinical Trials of medical imaging. OpenVCT provides tools for simulation of patient accrual and reader studies of medical imaging devices, simulating by simulating cohorts of patients and readers. OpenVCT uses common data standards, such as DICOM, to ensure inter-compatibility. -
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KlayGE is an open source, cross-platform game engine with plugin-based architecture. It provides a framework to make game development, testing, porting as simple as possible.
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TensorLayer
Deep learning and reinforcement learning library for scientists
...It provides an extensive collection of customizable neural layers to build advanced AI models quickly, based on this, the community open-sourced mass tutorials and applications. TensorLayer is awarded the 2017 Best Open Source Software by the ACM Multimedia Society. This project can also be found at OpenI and Gitee. 3.0.0 has been pre-released, the current version supports TensorFlow, MindSpore and PaddlePaddle (partial) as the backends, allowing users to run the code on different hardware like Nvidia-GPU and Huawei-Ascend. In the future, it will support TensorFlow, MindSpore, PaddlePaddle, PyTorch and other backends. ... -
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video-to-ascii
It is a simple python package to play videos in the terminal
...The tool adapts video resolution to match terminal dimensions, ensuring a coherent and readable output despite limited character space. It can optionally include audio playback when additional dependencies such as FFmpeg and PortAudio are installed. The project supports multiple rendering strategies and allows exporting ASCII output to files for sharing or reuse. It also includes color approximation using ANSI palettes to enhance visual fidelity within terminal limitations. Designed as both a creative and technical project, it demonstrates how video data can be transformed into text-based representations. -
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STManager
manage assortment in your company
...Application designed to help with managing for example postal packages, where each product is very distinct for one another. For source code and more insides of this project, please visit github page: https://github.com/michalwilk123/STManager Name STManager is derived from old name: "Stocktake Manager". -
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Text2Video
Software tool that converts text to video for more engaging experience
...I created a prototype web application that takes text as an input and generates a video as an output. I plan to further work on the project targeting young college students who are aged between 18 to 23 because they tend to prefer learning through videos over books based on the survey I found. The technologies I used for the project are HTML, CSS, Javascript, Node.js, CCapture.js, ffmpegserver.js, Amazon Polly, Python, Flask, gevent, spaCy, and Pixabay API.
