Search Results for "python sample" - Page 5
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Showing 174 open source projects for "python sample"
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The full-stack observability platform that protects your dataLayer, tags and conversion dataCode-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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Premier Construction SoftwareRated #1 Construction Accounting Software by Forbes Advisor in 2022 & 2023. Our modern SAAS solution is designed to meet the needs of General Contractors, Developers/Owners, Homebuilders & Specialty Contractors.
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XISMuS
X-Ray Imaging Software for Multiple Samples
ATTENTION: Cumulative update 2.5.0 has been released!! The update works for any previous 2.x.x version. If upgrading from version v1.x.x, please download and install v2.0.0 first. IMPORTANT FIXES in respect to base v2.0.0 version: v.2.5.0 introduces the Differential Attenuation and Cube Viewer utilities, and migrates user database to *.json files v2.4.3 fixes a with K element in the fit-approx method v2.4.3 fixes and issue where saving plots with fit-approx or a auto-wizard could... -
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Code Cookbook
Reusable code patterns which you can use as reference or copy
Reusable code patterns which you can use as reference or copy to your project. Achieve small or large tasks using recipes that contain steps, scripts, and config files. -
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Mocking Bird
Clone a voice in 5 seconds to generate arbitrary speech in real-time
...The codebase is implemented in Python (with PyTorch) and includes modules for encoder, synthesizer, vocoder, preprocessing, and inference, as well as demo scripts and a web-server interface for easier experimentation or deployment. MockingBird supports both using pretrained models and training your own synthesizer (with custom datasets), giving flexibility for voice-cloning or custom-voice synthesis depending on your needs. -
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Machine-Learning
kNN, decision tree, Bayesian, logistic regression, SVM
...This makes the repo suitable for students, hobbyists, or developers who want to deeply understand how ML algorithms work under the hood and experiment with parameter tuning or custom data. Because it's part of the author’s learning-path repositories, it likely is integrated with tutorials, sample datasets, and contextual guidance, which helps users bridge theory. -
Failed Payment Recovery for Subscription BusinessesFlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
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Pydub
Manipulate audio with a simple and easy high level interface
...Note that no validation takes place on these parameters, and you may be limited by what your particular build of ffmpeg/avlib supports. You can open and save WAV files with pure python. For opening and saving non-wav files, like mp3, you'll need ffmpeg or libav. Any operations that combine multiple AudioSegment objects in any way will first ensure that they have the same number of channels, frame rate, sample rate, bit depth, etc. -
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Keras TCN
Keras Temporal Convolutional Network
TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the... -
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...This client enables to extract and download data through a python command line Indesol project sample: http://www.indeso.web.id/indeso_wp/index.php/faq/30-6-how-to-write-and-run-the-script-to-download-indeso-met-ocean-data
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joy2key
Steer in GTBikeV with any unsupported joystick
Map joystick buttons to keyboard keys, to steer in GTBikeV with any (unsupported) joystick. Uses Python Windows joystick API and sample code from How to generate keyboard events in Python? If your joystick has an analog stick you may prefer using x360ce for steering. You can still use joy2key to enable/disable auto drive and change radio station, just leave buttons 3 and 4 unmapped in x360ce. -
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Image GPT
Large-scale autoregressive pixel model for image generation by OpenAI
Image-GPT is the official research code and models from OpenAI’s paper Generative Pretraining from Pixels. The project adapts GPT-2 to the image domain, showing that the same transformer architecture can model sequences of pixels without altering its fundamental structure. It provides scripts to download pretrained checkpoints of different model sizes (small, medium, large) trained on large-scale datasets and includes utilities for handling color quantization with a 9-bit palette.... -
Skillfully - The future of skills based hiringSkillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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HiFi-GAN
Generative Adversarial Networks for Efficient and High Fidelity Speech
HiFi-GAN is a GAN-based neural vocoder designed to generate high-fidelity speech waveforms from mel spectrograms with exceptional efficiency. It introduces a generator architecture tailored to model the periodic structure of speech and a set of discriminators that focus on different scales and periods of the waveform to better capture naturalness. The model targets a sweet spot between sample quality and generation speed, outperforming many previous GAN vocoders while being far faster than... -
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
...A sample is specified using 4 columns separated by space (or tabs). -
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LiVES
LiVES is a Video Editing System. It is designed to be simple to use, y
LiVES mixes realtime video performance and non-linear editing in one professional quality application. It is designed to be simple to use, yet powerful. It is small in size, yet it has many advanced features. Using LiVES, you can start editing and making video right away, without having to worry about formats, frame sizes, or framerates. It is a very flexible tool which is used by both professional VJ's and video editors - mix and switch clips from the keyboard, use dozens of realtime... -
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Tofu
Tofu is a Python tool for generating synthetic UK Biobank data
Tofu is a Python library for generating synthetic UK Biobank data. The UK Biobank is a large open-access prospective research cohort study of 500,000 middle-aged participants recruited in England, Scotland and Wales. The study has collected and continues to collect extensive phenotypic and genotypic detail about its participants, including data from questionnaires, physical measures, sample assays, accelerometry, multimodal imaging, genome-wide genotyping and longitudinal follow-up for a wide range of health-related outcomes. ... -
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TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the... -
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PixieDust
Python Helper library for Jupyter Notebooks
PixieDust is an open source Python helper library that works as an add-on to Jupyter notebooks to improve the user experience of working with data. It also fills a gap for users who have no access to configuration files when a notebook is hosted on the cloud. -
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TensorFlow Course
Simple and ready-to-use tutorials for TensorFlow
This repository houses a highly popular (~16k stars) set of TensorFlow tutorials and example code aimed at beginners and intermediate users. It includes Jupyter notebooks and scripts that cover neural network fundamentals, model training, deployment, and more, with support for Google Colab. -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with... -
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DCVGAN
DCVGAN: Depth Conditional Video Generation, ICIP 2019.
This paper proposes a new GAN architecture for video generation with depth videos and color videos. The proposed model explicitly uses the information of depth in a video sequence as additional information for a GAN-based video generation scheme to make the model understands scene dynamics more accurately. The model uses pairs of color video and depth video for training and generates a video using the two steps. Generate the depth video to model the scene dynamics based on the geometrical... -
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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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TGAN
Generative adversarial training for generating synthetic tabular data
...In order to be able to sample new synthetic data, TGAN first needs to be fitted to existing data. -
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Scalable Distributed Deep-RL
A TensorFlow implementation of Scalable Distributed Deep-RL
Scalable Agent is the open implementation of IMPALA (Importance Weighted Actor-Learner Architectures), a highly scalable distributed reinforcement learning framework developed by Google DeepMind. IMPALA introduced a new paradigm for efficiently training agents across large-scale environments by decoupling acting and learning processes. In this architecture, multiple actor processes interact with their environments in parallel to collect trajectories, which are then asynchronously sent to a... -
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Omniglot
Omniglot data set for one-shot learning
This repository hosts the Omniglot dataset for one-shot learning, containing handwritten characters across multiple alphabets along with stroke data. It includes both MATLAB and Python starter scripts (e.g. demo.m, demo.py) to illustrate how to load the images and stroke sequences and run baseline experiments (such as classification by modified Hausdorff distance). The dataset provides both an image representation of each character and the time-ordered stroke coordinates ([x, y, t]) for each instance. Includes stroke data (time-sequenced coordinates) per sample. ... -
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CMD Plot Tool
Calculates and plots Colour Magnitude Diagrams from Astronomical data
Sample data is also bundled, to demonstrate its complete functionality to users. Other functionality within this application is the ability to convert DAOPHOT magnitude files to CSV format. -
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A SoundFont editor and other software for editing, managing and sharing sample based MIDI instrument files for computer music composition. Support for other formats is planned.
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Compare GAN
Compare GAN code
compare_gan is a research codebase that standardizes how Generative Adversarial Networks are trained and evaluated so results are comparable across papers and datasets. It offers reference implementations for popular GAN architectures and losses, plus a consistent training harness to remove confounding differences in optimization or preprocessing. The library’s evaluation suite includes widely used metrics and diagnostics that quantify sample quality, diversity, and mode coverage. With...
