Search Results for "mac utilities" - Page 9
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Showing 282 open source projects for "mac utilities"
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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... -
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EverydayWechat
Python tool that automates WeChat messages, replies, & group utilities
EverydayWechat is a Python-based automation tool designed to enhance and automate interactions on the WeChat messaging platform. Built using Python 3 and the Itchat library, it connects to the web version of WeChat to perform various automated messaging tasks. It allows users to send scheduled messages to friends or group chats, including daily weather updates, reminders, inspirational quotes, and other personalized content. It also supports intelligent automatic replies to incoming messages... -
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PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
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Image Quality Assessment
Convolutional Neural Networks to predict aesthetic quality of images
Image Quality Assessment is an open-source deep learning project that implements neural models for predicting the aesthetic and technical quality of digital images. The repository provides an implementation inspired by the NIMA (Neural Image Assessment) research approach, which uses convolutional neural networks trained on human-annotated datasets to estimate image quality scores. The goal of the project is to automatically evaluate images based on perceived quality factors such as... -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out... -
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DeepSDF
Learning Continuous Signed Distance Functions for Shape Representation
DeepSDF is a deep learning framework for continuous 3D shape representation using Signed Distance Functions (SDFs), as presented in the CVPR 2019 paper DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation by Park et al. The framework learns a continuous implicit function that maps 3D coordinates to their corresponding signed distances from object surfaces, allowing compact, high-fidelity shape modeling. Unlike traditional discrete voxel grids or meshes, DeepSDF... -
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PyTorch-BigGraph
Generate embeddings from large-scale graph-structured data
PyTorch-BigGraph (PBG) is a system for learning embeddings on massive graphs—think billions of nodes and edges—using partitioning and distributed training to keep memory and compute tractable. It shards entities into partitions and buckets edges so that each training pass only touches a small slice of parameters, which drastically reduces peak RAM and enables horizontal scaling across machines. PBG supports multi-relation graphs (knowledge graphs) with relation-specific scoring functions,... -
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yapyutils
Utilities for platform indepentent low-level system APIs.
The 'yapyutils' - Yet Another Python Utils - package provides miscellaneous *Python* utilities for the adaptation of platform independent APIs of the low-level part of the software stack. These are e.g. used for extensions of the *setuptools* and *distutils*, thus reduce the package dependency and avoid circular dependencies whenever possible by using standard packages and classes only. The more complex and complete data packages are provided for higher application layer... -
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Spotlight
Deep recommender models using PyTorch
Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various pointwise and pairwise ranking losses), representations (shallow factorization representations, deep sequence models), and utilities for fetching (or generating) recommendation datasets, it aims to be a tool for rapid exploration and prototyping of new recommender models. Spotlight offers a slew of popular datasets, including Movielens 100K, 1M,... -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The... -
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PyRobot
An Open Source Robotics Research Platform
PyRobot is a high-level robotics API that simplifies controlling real and simulated robots through a consistent Python interface. Instead of fighting ROS internals, you call clear methods for things like base navigation, arm manipulation, and camera capture, and PyRobot handles the plumbing. It was built to make research repeatable on accessible platforms—most notably low-cost mobile manipulators—while still scaling to richer hardware. The library exposes canonical abstractions (base, arm,... -
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UnsupervisedMT
Phrase-Based & Neural Unsupervised Machine Translation
Unsupervised Machine Translation is a research repository that implements both phrase-based SMT and neural MT approaches for translation without parallel corpora. The neural component supports multiple architectures—seq2seq, biLSTM with attention, and Transformer—and allows extensive parameter sharing across languages to improve data efficiency. Training relies on denoising auto-encoding and back-translation, with on-the-fly, multithreaded generation of synthetic parallel data to continually... -
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Finetune Transformer LM
Code for "Improving Language Understanding by Generative Pre-Training"
finetune-transformer-lm is a research codebase that accompanies the paper “Improving Language Understanding by Generative Pre-Training,” providing a minimal implementation focused on fine-tuning a transformer language model for evaluation tasks. The repository centers on reproducing the ROCStories Cloze Test result and includes a single-command training workflow to run the experiment end to end. It documents that runs are non-deterministic due to certain GPU operations and reports a median... -
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LUMINOTH
Deep Learning toolkit for Computer Vision
LUMINOTH is an open-source deep learning toolkit designed for computer vision tasks, particularly object detection. The framework is implemented in Python and built on top of TensorFlow and the Sonnet neural network library, providing a modular environment for training and deploying detection models. It was created to simplify the process of building and experimenting with deep learning models capable of identifying objects within images. Luminoth includes support for popular object... -
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Spatial Media
Specifications and tools for 360º video and spatial audio
spatial-media provides tools for working with spherical video and spatial audio metadata so players and platforms can correctly render immersive media. The utilities inject, inspect, and extract metadata in common container formats (MP4/WebM) to signal 360° projection type, stereoscopy mode, and spatial audio layout. Creators use it to prepare 360/VR180 assets for upload so services know whether a video is monoscopic, top-bottom stereo, or side-by-side, and whether ambisonic audio is... -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution... -
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Python ADB
Python ADB + Fastboot implementation
python-adb provides a pure-Python implementation of the Android Debug Bridge protocol so you can script Android devices without depending on the platform adb binary. It exposes high-level helpers for device discovery, shell commands, file push/pull, port forwarding, and log collection, making it easy to build automation around phones and emulators. Under the hood it speaks the ADB protocol directly and can connect via USB or over TCP, which is useful for lab setups and headless servers.... -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. Because it aggregates... -
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Deep Reinforcement Learning TensorFlow
TensorFlow implementation of Deep Reinforcement Learning papers
Deep Reinforcement Learning TensorFlow is a comprehensive TensorFlow codebase that implements several foundational deep reinforcement learning algorithms for educational and experimental use. The repository focuses on clarity and modularity so users can study how different RL approaches are built and compare their behavior across environments. It includes implementations of well-known algorithms such as Deep Q-Networks (DQN), policy gradients, and related variants, demonstrating how neural... -
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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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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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Assorted projects. General-purpose libraries for Python, C++, Scala, bash, and others. Meta-programming tools. System utilities. UI components. Web APIs. Configuration files. Benchmarks. Programming competition entries. And much more.
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pyfilesysobjects
Search and match of file type resource paths and addresses
The 'filesysobjects' package provides cross-platform-utilities for path addresses of file like resources. This includes the search and navigation features on file system structures with the application of regular expressions for pathnames intermixed with globs. - filesysobjects - constants - filesysobjects.apppaths - application resource path processing - filesysobjects.paths - file systems path processing - filesysobjects.pathtools - search, enumeration, and iteration operations - filesysobjects.userdata - user directories - filesysobjects.osdata - OS directories - filesysobjects.configdata - config directories Supported platforms are: - Linux, BSD, Unix, Mac-OS/OS-X, and Windows - Python2.7, Python3.5+ Online documents: https://pyfilesysobjects.sourceforge.io/ -
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BlockSparse
Efficient GPU kernels for block-sparse matrix multiplication
The blocksparse repository provides efficient GPU kernels (TensorFlow custom ops) for block-sparse matrix multiplication and convolution operations. The idea is to exploit block-level sparsity — i.e. treat matrices or weight tensors as composed of blocks, many of which may be zero or unused — to save compute and memory when sparsity patterns are structured. This is particularly useful in models like Sparse Transformers, where attention matrices or intermediate layers may adopt block-sparse... -
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Flask JSONDash
Build complex dashboards without any front-end code
Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go. Easily configurable, chart dashboards from any arbitrary API endpoint. JSON config only. Ready to go. This project is a flask blueprint that allows you to create sleek dashboards without writing any front-end (or backend) code. Everything is powered through simple JSON configurations for declaring arbitrary charts. Leveraging popular libraries like C3.js and D3.js, and much more. Also...
