Search Results for "input-leap" - Page 15
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Showing 574 open source projects for "input-leap"
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MachineTrans
A prototype for a Russian-English machine translation program.
This program currently allows for input of vocabulary an generation of random English sentences from semi-random data. -
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iHome by ionware
iHome Smart Home System Platform
iHome is a fully tested Smart Home Automation system using the Raspberry Pi Zero WiFi SBC and Linux OS and has all the functional features of NEST or ECOBEE smart thermostats with the added benefit of full privacy and security at less than half the price! It incorporates MBLogic with algorithms and Modbus coms for HVAC home control via the ionware modbus compatible ionC1 input/output controller board. The iHome software system comes fully configured as a SD Card image file for Raspberry Pi Zero wifi Plug and Play capability complete with MBLogic, Node-RED and MQTT already fully installed and ready to go. See wiki instructions to burn the SD Card image file, insert into your RPi Zero and Plug and Play. ... -
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ebfformat
An Efficient Binary data Format
...The EBF specification is designed to be concise and easy to understand to make it easier for others to write their own code if needed. It is also designed to simplify the programming of input output routines in different programming languages. In a nutshell an EBF file is a collection of data objects. Each data object is specified by a unique name and a single file can have multiple data objects. Each data object is preceded by a meta-data or header which describes the binary data associated with it. Among other things, this header allows the files to be portable across systems with different endianess. -
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FavFreak
Favicon hash–based reconnaissance tool for security research
FavFreak is an open source reconnaissance tool designed to assist security researchers, bug bounty hunters, and penetration testers in identifying web technologies using favicon hashes. It works by taking one or more URLs as input and automatically retrieving the favicon.ico file associated with each target website. After fetching the favicon, it calculates a hash value and organizes the scanned domains, subdomains, or IP addresses according to these hashes. FavFreak then compares the generated hashes against a predefined fingerprint dictionary that maps known favicon hashes to specific technologies or services. ... -
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TFKit
Handling multiple nlp task in one pipeline
...The key to combine different task together is to make different task with same data format. All data will be in csv format - tfkit will use csv for all task, normally it will have two columns, first columns is the input of models, the second column is the output of models. Plane text with no tokenization - there is no need to tokenize text before training, or do re-calculating for tokenization, tfkit will handle it for you. No header is needed. -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and... -
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Super-résolution via CNN
Super resolution using a CNN, based on the work of the DGtal team
...This program will generate "model_epoch_ .pth" files corresponding to the model at epoch n, in a folder saved_model_u t_bs bs_tbs tbs_lr lr, where corresponds to the scale factor, bsthe size of the training batch, tbsthe size of the test batch and lrto the learning rate. Low res images should be located in a "dataset/input" folder, and high res targets in a "dataset/target" folder, where each different quality image has the same name in both folders. -
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Alfred-Workflow
Full-featured library for writing Alfred 3 & 4 workflows
Alfred-Workflow is a Python helper library for Alfred 2, 3 and 4 workflow authors, developed and hosted on GitHub. Alfred workflows typically take user input, fetch data from the Web or elsewhere, filter them and display results to the user. Alfred-Workflow takes care of a lot of the details for you, allowing you to concentrate your efforts on your workflow’s functionality. Alfred-Workflow supports macOS 10.7+ (Python 2.7). Easily launch background tasks (daemons) to keep your workflow responsive. ... -
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DNSGen
Intelligent DNS permutation tool for subdomain discovery
DNSGen is an open source DNS name permutation tool designed primarily for security researchers and penetration testers who need to discover potential subdomains during reconnaissance and attack surface mapping. It analyzes existing domain names and generates numerous intelligent variations that may represent valid subdomains within an organization’s infrastructure. These generated permutations help identify hidden or unlisted services that may not appear in standard DNS queries or public... -
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AttackSurfaceMapper
Automated tool for mapping & expanding organization’s attack surface
...It combines open source intelligence (OSINT) with selective active reconnaissance techniques to expand and analyze a target’s external attack surface. Users can supply domains, subdomains, or IP addresses as input, and applies multiple discovery methods to identify additional related assets such as new subdomains, associated IP ranges, and hosts within the same network ownership. It performs both brute-force and passive enumeration techniques to uncover infrastructure components that may not be immediately visible. After building an expanded list of targets, AttackSurfaceMapper collects intelligence such as screenshots of web applications, information about exposed services, and possible vulnerabilities identified through integrated services. ... -
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VoteNet
Deep Hough Voting for 3D Object Detection in Point Clouds
VoteNet is a 3D object detection framework for point clouds that combines deep point set networks with a Hough voting mechanism to localize and classify objects in 3D space. It tackles the challenge that object centroids in 3D scenes often don’t lie on any input surface point by having each point “vote” for potential object centers; these votes are then clustered to propose object hypotheses. Once cluster centers are formed, the network regresses bounding boxes around them and classifies them. VoteNet works end-to-end: it learns the voting, aggregation, and bounding-box regression components jointly, enabling strong detection accuracy without relying on 2D proxies or voxelization. ... -
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textgenrnn
Easily train your own text-generating neural network
...Train on and generate text at either the character-level or word-level. Configure RNN size, the number of RNN layers, and whether to use bidirectional RNNs. Train on any generic input text file, including large files. Train models on a GPU and then use them to generate text with a CPU. Utilize a powerful CuDNN implementation of RNNs when trained on the GPU, which massively speeds up training time as opposed to typical LSTM implementations. Train the model using contextual labels, allowing it to learn faster and produce better results in some cases. -
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MatchZoo
Facilitating the design, comparison and sharing of deep text models
...With the unified data processing pipeline, simplified model configuration and automatic hyper-parameters tunning features equipped, MatchZoo is flexible and easy to use. Preprocess your input data in three lines of code, keep track parameters to be passed into the model. Make use of MatchZoo customized loss functions and evaluation metrics. Initialize the model, fine-tune the hyper-parameters. Generate pair-wise training data on-the-fly, evaluate model performance using customized callbacks on validation data. MatchZoo is dependent on Keras and Tensorflow. -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
...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 both RGB and optical flow input streams. The models have achieved state-of-the-art results on benchmark datasets such as UCF101 and HMDB51, and also won first place in the CVPR 2017 Charades Challenge. The project provides TensorFlow and Sonnet-based implementations, pretrained checkpoints, and example scripts for evaluating or fine-tuning models. It also offers sample data, including preprocessed video frames and optical flow arrays, to demonstrate how to run inference and visualize outputs. -
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AET
Detects visual changes on websites and performs page health checks
AET is a system that detects visual changes on websites and performs basic page health checks (like w3c compliance, accessibility, HTTP status codes, JS Error checks and others). AET is designed as a flexible system that can be adapted and tailored to the regression requirements of a given project. The tool has been developed to aid front-end client-side layout regression testing of websites or portfolios, in essence assessing the impact or change of a website from one snapshot to the next. -
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Django Celery
Old Celery integration project for Django
...Celery has a large and diverse community of users and contributors, you should come join us on IRC or our mailing-list. Celery is Open Source and licensed under the BSD License. A task queue’s input is a unit of work called a task. Dedicated worker processes constantly monitor task queues for new work to perform. Celery communicates via messages, usually using a broker to mediate between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. Celery requires a message transport to send and receive messages. -
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GIF for CLI
Takes in a GIF, short video, or a query to the Tenor GIF API
gif-for-cli is a small, playful utility that brings animated GIFs to the command line by rendering frames directly in a terminal. It takes an input GIF (or a URL) and converts each frame into a terminal-friendly representation, timing updates to approximate the original animation. Depending on terminal capabilities, it can use ANSI color blocks or image protocols to achieve surprisingly faithful playback. The tool includes conveniences such as looping control, scaling to fit your terminal, and caching to avoid repeated downloads. ... -
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Molecular Dynamics Studio
Molecular Dynamics Cell Construction
...PACKMOL can generate a random collection of molecules using the molecule templates from NanoEngineer-1 thus providing the initial MD cell. Modifications to PACKMOL allow the atom type data to be passed through to the MSI2LMP software. MSI2LMP creates a LAMMPS input file based on class I or class II force fields. MSI2LMP was modified to use numerically coded force field data generated by NanoEngineer-1. The MMP file format was extended and integrated into all three software applications. http://www.nanoengineer-1.net http://www.ime.unicamp.br/~martinez/packmol/ http://lammps.sandia.gov/ -
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vid2vid
Pytorch implementation of our method for high-resolution
...The framework is capable of producing high-resolution outputs and is widely used in research related to video synthesis, animation, and simulation. It also supports diverse input modalities, making it flexible for different types of video generation tasks. -
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ParamIT
a Toolset for Molecular Mechanical Force Field Parameterization
...The usage of these tools decreases the labor effort, lowers manual input errors and reduces the time needed for accurate MM parameterization efforts. -
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TGAN
Generative adversarial training for generating synthetic tabular data
We are happy to announce that our new model for synthetic data called CTGAN is open-sourced. The new model is simpler and gives better performance on many datasets. TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid... -
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automl-gs
Provide an input CSV and a target field to predict, generate a model
Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learning model plus native Python code pipelines allowing you to integrate that model into any prediction workflow. No black box: you can see exactly how the data is processed, and how the model is constructed, and you can make tweaks as necessary. automl-gs is an AutoML tool which, unlike Microsoft's NNI, Uber's Ludwig, and TPOT, offers a zero code/model definition interface to getting an optimized model and data transformation pipeline in multiple popular ML/DL frameworks, with minimal Python dependencies (pandas + scikit-learn + your framework of choice). automl-gs is designed for citizen data scientists and engineers without a deep statistical background under the philosophy that you don't need to know any modern data preprocessing and machine learning engineering techniques to create a powerful prediction workflow. -
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BCAW Tool
Bio Codon Analysis Workflow Tool
BCAWT was developed using python 3.7 with build in and third-party modules. The usage of BCAWT is made to be very easy where users have only to input a fasta format file containing genes to be analyzed, and a bunch of analysis will be performed with 23 different output files -
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pyGear
Precise gear geometry generator for spur and helical gears
A python gear generator that serves as CAE/CAD-preprocessor for involute gears based on pythonOCC. It allows for the computation of dynamic properties and the creation of exact geometries from a minimal input set. PyGear can simulate the tool geometry and kinematics of standard gear hobbing tools to generate precise flank, tooth root and tip geometries. -
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PYWAL
Generate and change color-schemes on the fly
PYWAL is a highly popular tool that automatically generates a color scheme from any image (usually your wallpaper) and then applies it across your Linux or Unix desktop. It analyzes the input image, extracts a palette, and builds theme files for terminals, window managers, and various desktop applications so everything looks coordinated. The magic is that it’s not just a one-off script: it supports many terminals, shells, and launchers, and can export the colors in multiple formats (JSON, Xresources, CSS) for other programs to consume. ...
