Search Results for "model-builder" - Page 9
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Showing 411 open source projects for "model-builder"
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1
YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
YOLOV4 Pytorch is a PyTorch implementation of the YOLOv4 object detection model for training and running custom detection systems. The repository is structured around practical workflows, including training, prediction, evaluation, anchor generation, model configuration, and dataset annotation utilities. It supports VOC-style datasets and includes scripts for prediction, mAP evaluation, FPS testing, video prediction, batch prediction, and heatmap generation. -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
...Tasks store dictionaries and provide helpers for loading/iterating over Datasets, initializing the Model/Criterion and calculating the loss. -
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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
YOLOV3 Pytorch is a PyTorch implementation of the YOLOv3 object detection model built for training, prediction, and evaluation. The repository provides a complete workflow for users who want to train their own object detector with VOC-style data or use pretrained weights. It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. -
4
Flowy
The minimal javascript library to create flowcharts
...The library focuses on simplicity and aesthetics, offering a clean look out of the box that can be customized with your own CSS, making it suitable for dashboards, SaaS products, or internal tools. Events emitted by flowy enable integration with your own data model, so you can sync block positions, connections, and metadata back to a database or application state. It is framework-agnostic, so it can be dropped into vanilla JavaScript projects or wrapped inside React, Vue, or other frameworks. -
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5
CoolplaySpark
Spark Cool Play: Spark source code analysis, Spark class library, etc.
...It serves as a companion resource for the book 深入理解Spark核心思想与源码分析 (In-Depth Understanding of Spark’s Core Concepts and Source Code Analysis). The project contains annotated examples, explanations, and exercises that guide learners through Spark’s architecture, execution model, and source code internals. It is particularly valuable for developers who want to strengthen their understanding of Spark by not only using it as a data processing engine but also exploring how its internals function. Through code analysis and commentary, CoolplaySpark helps readers connect theoretical concepts with practical implementation details. ... -
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apl-library
Useful stuff for APL programmers
This collection of APL libraries have been contributed to GNU APL and should be downloaded here: https://gnu.org/software/apl. -
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Provider
InheritedWidgets, but simple
...Because it relies on Flutter’s core mechanisms, it integrates seamlessly with common architectural styles and existing widgets. Many apps use provider as a baseline pattern, and later evolve toward more advanced solutions as complexity grows—without discarding the conceptual model provider introduces. -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature extractors. ... -
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graphql-client
A Ruby library for declaring, composing and executing GraphQL queries
...If you haven't already, familiarize yourself with the GraphQL query syntax. Queries are declared with the same syntax inside of a <<-'GRAPHQL' heredoc. There isn't any special query builder Ruby DSL. This client library encourages all GraphQL queries to be declared statically and assigned to a Ruby constant. If you're using Ruby on Rails ERB templates, theres a ERB extension that allows static queries to be defined in the template itself. In standard Ruby you can simply assign queries and fragments to constants and they'll be available throughout the app. ... -
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10
Unet
Source code for unet-pytorch, which can train its own model
...The repository is built around training, prediction, and mIoU evaluation for VOC-style segmentation data and medical-style datasets. It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes that U-Net is better suited to datasets with fewer features and shallow visual structures, such as medical image segmentation, rather than complex VOC-style scenes. ... -
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DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
...It implements the encoder-decoder architecture with atrous separable convolution and provides a practical workflow for training, prediction, and mIoU evaluation. The repository supports VOC-style segmentation datasets and includes utilities for annotation generation, JSON dataset conversion, model summary inspection, prediction, and metric calculation. It provides pretrained weight workflows for MobileNetV2 and Xception backbones and notes that the correct backbone should be selected during training and prediction. The project also supports multi-GPU training, multiple backbones, learning rate schedules with step and cosine options, optimizer selection, and adaptive learning rate behavior based on batch size. ... -
12
AugLy
A data augmentations library for audio, image, text, and video
...These sub-libraries include both function-based and class-based transforms, composition operators, and have the option to provide metadata about the transform applied, including its intensity. AugLy is a great library to utilize for augmenting your data in model training, or to evaluate the robustness gaps of your model! We designed AugLy to include many specific data augmentations that users perform in real life on internet platforms like Facebook's -- for example making an image into a meme, overlaying text/emojis on images/videos, reposting a screenshot from social media. While AugLy contains more generic data augmentations as well, it will be particularly useful to you if you're working on a problem like copy detection, hate speech detection, etc. -
13
Statistical Rethinking 2022
Statistical Rethinking course winter 2022
...The code emphasizes Bayesian data analysis using R, the rethinking package, and Stan models. It includes lecture code files, example datasets, and structured exercises that parallel the topics covered in the lectures (probability, regression, model comparison, Bayesian updating). The repo functions as a direct hands-on reference for students following the 2022 recorded lecture series. There are 10 weeks of instruction. Links to lecture recordings will appear in this table. Weekly problem sets are assigned on Fridays and due the next Friday, when we discuss the solutions in the weekly online meeting. -
14
NetworkResponse Retrofit adapter
Retrofit call adapter to model success/failed responses as sealed type
This library provides a Kotlin Coroutines-based Retrofit call adapter for wrapping your API responses in a NetworkResponse sealed type. -
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go-fundamental-programming
Set of video and voice tutorials for the Go language
go-fundamental-programming is the code and notes repository for the Chinese video course, a foundational Go programming tutorial aimed at beginners. The author positions it explicitly as a way to share the knowledge and pitfalls accumulated while learning Go, so that new learners can avoid common mistakes and weird corner cases. The course is delivered as a series of lectures, and each lecture has a dedicated lectureX.md file that serves as classroom notes, listing the knowledge points... -
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TransferJsonConverter
A custom JSON converter library with some useful features for ASP.NET
...It serializes objects to a JSON string, using the provided interfaces as templates, and including attributed fields not included in the interfaces. This allows you to pass objects from the storage layer through the model to the client, hiding specific data, while still storing it for postback from the client. It deserializes a JSON string into objects, reusing existing objects as targets if possible. This avoids creating an intermediate list of objects when populating an ObservableCollection on the WPF client, and reduces the overhead of creating multiple objects in memory and the garbage collector. -
17
Differ
Swift library to generate differences and patches between collections
...There’s a lot more to calculating diffs than performing table view animations easily. Wherever you have code that propagates added/removed/moved callbacks from your model to your user interface, you should consider using a library that can calculate differences. Animating small batches of changes is usually going to be faster and provide a more responsive experience than reloading all of your data. Calculating and acting on differences should also aid you in making a clear separation between data and user interface, and hopefully provide a more declarative approach: your model performs state transition, then your UI code performs appropriate actions based on the calculated differences to that state. -
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Kotpref
Android SharedPreferences delegation library for Kotlin
Android SharedPreferences delegation library for Kotlin. -
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Spyne
A transport agnostic sync/async RPC library
...Spyne aims to save the protocol implementers the hassle of implementing their own remote procedure call api and the application programmers the hassle of jumping through hoops just to expose their services using multiple protocols and transports. In other words, Spyne is a framework for building distributed solutions that strictly follow the MVC pattern, where Model = spyne.model, View = spyne.protocol and Controller = user code. Spyne comes with the implementations of popular transport, protocol and interface document standards along with a well-defined API that lets you build on existing functionality. -
20
Graph4NLP
Graph4nlp is the library for the easy use of Graph Neural Networks
...The architecture of Graph4NLP is shown in the following figure, where boxes with dashed lines represent the features under development. Graph4NLP consists of four different layers: 1) Data Layer, 2) Module Layer, 3) Model Layer, and 4) Application Layer. Graph4nlp aims to make it incredibly easy to use GNNs in NLP tasks (check out Graph4NLP Documentation). -
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go-study-index
Go language learning materials index
go-study-index is a comprehensive, community-maintained index of Go learning resources and communities, primarily oriented toward Chinese-speaking developers. It was created because a previous index of resources had gone out of date for over three years, and the author wanted a fresher, living catalog that others could update via fork and pull request. The README is structured into sections for communities, navigation sites, learning materials, tools, cloud platforms, newsletters, videos,... -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
...This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple computational steps, while maintaining speaker consistency across output channels. Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. ... -
23
Delphi Drag&Drop Suite by Adrix.NT
Delphi Drag & Drop Comp Suite v.5.2 rev. by Vincent Radio {Adrix.NT}
...MelanderBlog: melander.dk - The Drag and Drop Component Suite v5.2 released for any question about installation e-mail me at: adrixnt@hotmail.it PS: it seems not working in C++Builder !! Adrix.NT -
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react-pxq
Implement modern front-end architecture with idiomatic React patterns
react-pxq is a React-based single-page application that demonstrates how to implement modern front-end architecture with idiomatic React patterns. It shows how to break a product into cohesive components, manage global and local state, and coordinate data-fetching with UI updates. Routing is used to separate feature areas, while shared UI primitives keep styling and behavior consistent across screens. The code emphasizes ES6+ conventions, async flows, and clean separation of concerns to keep... -
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YOLOR
implementation of paper - You Only Learn One Representation
...It builds on the YOLO family and related PyTorch detection work, combining practical detector training with a research idea about unified representations. YOLOR includes model configurations, training code, evaluation scripts, inference tools, and pretrained weights. Its central contribution is the use of implicit knowledge to improve network performance without treating every task as fully separate. It is useful for computer vision researchers and developers studying YOLO-style detectors, representation learning, and high-performance detection systems.
