Search Results for "python samples" - Page 4

Showing 117 open source projects for "python samples"

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  • 1

    pydatascope

    Software oscilloscope using Python and tkinter

    Software oscilloscope using Python and tkinter. Supports multiple sources: socket, file, audio, USB. Displays data by samples, time or frequency. Scales the input automatically or manually.
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  • 2
    earthengine-py-notebooks

    earthengine-py-notebooks

    A collection of 360+ Jupyter Python notebook examples

    earthengine-py-notebooks is a comprehensive collection of hundreds of Jupyter Python notebooks that serve as examples and tutorials for using the Google Earth Engine Python API. These notebooks are organized into thematic areas such as image processing, machine learning, visualization, filtering, and asset management, exposing users to real geospatial analysis tasks. The repository makes it easier to explore Earth Engine’s large geospatial data catalog, interactively display map layers, and...
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  • 3
    Objectron

    Objectron

    A dataset of short, object-centric video clips

    The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists...
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  • 4
    lxspider

    lxspider

    Educational Python web scraping case collection for many sites

    lxSpider is a collection of web scraping examples designed primarily for learning and experimentation with data extraction techniques. It gathers numerous crawler implementations that demonstrate how to collect data from a wide range of websites and online services. It focuses heavily on practical cases that illustrate how different platforms handle requests, authentication parameters, and anti-scraping protections. lxSpider includes examples targeting areas such as e-commerce platforms,...
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  • 5
    OpenAI Glow

    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...
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  • 6
    Multilingual Speech Synthesis

    Multilingual Speech Synthesis

    An implementation of Tacotron 2 that supports multilingual experiments

    This repository provides synthesized samples, training and evaluation data, source code, and parameters for the paper One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech. It contains an implementation of Tacotron 2 that supports multilingual experiments and that implements different approaches to encoder parameter sharing. It presents a model combining ideas from Learning to speak fluently in a foreign language: Multilingual speech synthesis and cross-language voice...
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  • 7
    Reliable Metrics for Generative Models

    Reliable Metrics for Generative Models

    Code base for the precision, recall, density, and coverage metrics

    Reliable Fidelity and Diversity Metrics for Generative Models (ICML 2020). Devising indicative evaluation metrics for the image generation task remains an open problem. The most widely used metric for measuring the similarity between real and generated images has been the Fréchet Inception Distance (FID) score. Because it does not differentiate the fidelity and diversity aspects of the generated images, recent papers have introduced variants of precision and recall metrics to diagnose those...
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  • 8
    Machine Learning with TensorFlow

    Machine Learning with TensorFlow

    Accompanying source code for Machine Learning with TensorFlow

    Machine Learning with TensorFlow is an open repository containing the source code and practical examples that accompany the book Machine Learning with TensorFlow. The project provides numerous code samples demonstrating how to build machine learning models using the TensorFlow framework. These examples illustrate core machine learning concepts such as regression, classification, clustering, and neural networks through practical implementations. The repository includes implementations of...
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  • 9
    nonechucks

    nonechucks

    Deal with bad samples in your dataset dynamically

    nonechucks is a library that provides wrappers for PyTorch's datasets, samplers and transforms to allow for dropping unwanted or invalid samples dynamically. What if you have a dataset of 1000s of images, out of which a few dozen images are unreadable because the image files are corrupted? Or what if your dataset is a folder full of scanned PDFs that you have to OCRize, and then run a language detector on the resulting text, because you want only the ones that are in English? Or maybe you...
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  • 10
    CakeChat

    CakeChat

    CakeChat: Emotional Generative Dialog System

    CakeChat is a backend for chatbots that are able to express emotions via conversations. The code is flexible and allows to condition model's responses by an arbitrary categorical variable. For example, you can train your own persona-based neural conversational model or create an emotional chatting machine. Hierarchical Recurrent Encoder-Decoder (HRED) architecture for handling deep dialog context. Multilayer RNN with GRU cells. The first layer of the utterance-level encoder is always...
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  • 11
    FID score for PyTorch

    FID score for PyTorch

    Compute FID scores with PyTorch

    This is a port of the official implementation of Fréchet Inception Distance to PyTorch. FID is a measure of similarity between two datasets of images. It was shown to correlate well with human judgement of visual quality and is most often used to evaluate the quality of samples of Generative Adversarial Networks. FID is calculated by computing the Fréchet distance between two Gaussians fitted to feature representations of the Inception network. The weights and the model are exactly the same...
    Downloads: 7 This Week
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  • 12
    Examples.Python

    Examples.Python

    Shows how to use tkinter only by programming code (Python).

    Examples Python shows how to use tkinter only by programming code (Python). * Github repository : https://github.com/gammasoft71/Examples.Python * Homepage : https://gammasoft71.wixsite.com/gammasoft/python
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  • 13
    Deepvoice3_pytorch

    Deepvoice3_pytorch

    PyTorch implementation of convolutional neural networks

    An open source implementation of Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning.
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  • 14
    reNamer

    reNamer

    Rename files depending on their .extension

    If you want to rename your dataset samples for ML and you might have a lot of them (you should btw) or maybe you need to set different enumeration for every .extension you have or you just want to rename some personal stuff I am glad you are here. This is how you can rename your files: - For every .extension in the target folder reNamer sets unique enumeration. - Randomly - With your set of parameters. Example, name=FILE, start counting from=10, step=1 Finally It is simple...
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  • 15
    EfiPy

    EfiPy

    Python Library for accessing UEFI BIOS internal function by protocol

    Samples https://sourceforge.net/u/efipy/svn/HEAD/tree/Trunk/ EfiPy Author: https://www.linkedin.com/in/max-wu-a9068b90/
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  • 16
    Siamese and triplet learning

    Siamese and triplet learning

    Siamese and triplet networks with online triplet mining in PyTorch

    Siamese and triplet learning is a PyTorch implementation of Siamese and triplet neural network architectures designed for learning embedding representations in machine learning tasks. These types of networks learn to map images into a compact feature space where the distance between vectors reflects the similarity between inputs. Such embeddings are commonly used in applications like face recognition, image similarity search, and few-shot learning. The repository demonstrates how to train...
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  • 17
    Vaex

    Vaex

    Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python

    Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive exploration of big data. ...
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  • 18
    DC-TTS

    DC-TTS

    TensorFlow Implementation of DC-TTS: yet another text-to-speech model

    DC-TTS is a TensorFlow implementation of the DC-TTS architecture, a fully convolutional text-to-speech system designed to be efficiently trainable while producing natural speech. It follows the “Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention” paper, but the author adapts and extends the design to make it practical for real experiments. The model is split into two networks: Text2Mel, which maps text to mel-spectrograms, and SSRN...
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  • 19
    GDeps

    GDeps

    Automatic process to update and build your external libraries/projects

    Welcome to GDeps! ( http://gdeps.org ) ========== [PRE-ALPHA] GDeps is a C++ dependencies/projects builder. Write in Python3. Launch a project script and GDeps will: 1) Create and Update the repository (svn, git, mercurial) 2) Make the solution (cmake, boost, bakefile) 3) Build the solution (Compilers : Mingw, VC90~140, Clang, Digital Mars, Ides : Visual Studio, Codeblocks ). Install: ========== 1) Install Python3: https://www.python.org/ 2) Install...
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  • 20
    The 2D space game (top-down view), turn based game flow with RPG elements. ***The gameplay was inherited from game Space rangers. *** The first samples was made with python 2.6 (pygame/pyopengl). *** Currently the game is moving to C++ with SFML game framework*** Game is still far for ready to use/play. The reason of posting the raw code is to get advices from more experiences programmers how to make things better. Newest code is available in mercury repository.
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  • 21
    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django

    A Complete Beginner's Guide to Django - Code Samples

    Code samples from the Django tutorial series. I’m starting a new tutorial series about Django fundamentals. It’s a complete beginner’s guide to start learning Django. The material is divided into seven parts. We’re going to explore all the basic concepts in great detail, from installation, and preparation of the development environment, models, views, templates, URLs to more advanced topics such as migrations, testing, and deployment.
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  • 22

    Training Image Operators from Samples

    Tools to train Image Operators automatically from a set of samples.

    TRIOS - Training Image Operators from Samples is a set of tools to bring Image Processing closer to scientists in general. It is capable of estimating an operator between two images using only pairs of samples that contain an input image and the desired output. The operator is saved to a file and can be applied to any image.
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  • 23
    S.E.E.R. 2 is a full featured SCADA / Historian / Aggregate Analysis System developed to work as a 'front end' for mod_openopc. Written in pure PHP (HTML 4.01 Transitional), and driven by a web-based user interface for universal deployment.
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  • 24
    FOCUS

    FOCUS

    A model to identify organisms present in metagenomes in seconds

    FOCUS, an innovative and agile composition based using non-negative least squares to profile and report abundant organisms present in me-tagenomic samples and their relative abundance without sequence length dependencies. The program was tested with simulated and real metagenomes, and the results show that our approach predicts the organisms in random communities. Availability and implementation: The code implemented in Python can be found here and a web-sever at http://edwards.sdsu.edu/FOCUS. ...
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  • 25
    Awesome AWS

    Awesome AWS

    A curated list of awesome Amazon Web Services libraries

    A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources. Featuring the Fiery Meter of AWSome. Each repo listed meets at least one of the following requirements, community-authored repo with 100+ stars, community-vouched repo with < 100 stars, official repo from aws or awslabs. 100+ stars for community repos is not a strict requirement, it only serves as a guideline for the initial compilation. If you can vouch for the awesomeness...
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