Search Results for "mapping"
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26 projects for "mapping" with 2 filters applied:
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Cloud tools for web scraping and data extractionAutomate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
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Screenshot to Code
A neural network that transforms a design mock-up into static websites
Screenshot-to-code is a tool or prototype that attempts to convert UI screenshots (e.g., of mobile or web UIs) into code representations, likely generating layouts, HTML, CSS, or markup from image inputs. It is part of a research/proof-of-concept domain in UI automation and image-to-UI code generation. Mapping visual design to code constructs. Code/UI layout (HTML, CSS, or markup). Examples/demo scripts showing “image UI code”. -
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Anthropic SDK Python
Provides convenient access to the Anthropic REST API from any Python 3
...The library includes definitions for all request and response parameters using Python typed objects, automatically handles serialization and deserialization, and wraps HTTP logic (timeouts, retries, error mapping) so that developers can call the API in a clean, high-level way. The SDK supports both synchronous and asynchronous usage (via async/await) depending on context. Importantly, it also supports streaming responses via Server-Sent Events (SSE) so that large outputs can be consumed incrementally rather than waiting for the full response. ... -
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OpenAI Python
The official Python library for the OpenAI API
The OpenAI Python library provides convenient access to the OpenAI REST API from any Python 3.7+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx. -
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Universal Tool Calling Protocol (UTCP)
Official python implementation of UTCP. UTCP is an open standard
The python-utcp repository is the official Python SDK implementation of the Universal Tool Calling Protocol (UTCP). UTCP is an open, modern standard designed to let AI agents call any tool or API directly—over HTTP, CLI, WebSocket, gRPC, and more—without the overhead of extra wrapper layers or middleware. It leverages a modular, plugin-based architecture built around Pydantic models and separates the core functionality into a lightweight client and extensible protocol plugins, enabling... -
Smart Business Texting that Generates PipelineTextUs is the leading text messaging service provider for businesses that want to engage in real-time conversations with customers, leads, employees and candidates. Text messaging is one of the most engaging ways to communicate with customers, candidates, employees and leads. 1:1, two-way messaging encourages response and engagement. Text messages help teams get 10x the response rate over phone and email. Business text messaging has become a more viable form of communication than traditional mediums. The TextUs user experience is intentionally designed to resemble the familiar SMS inbox, allowing users to easily manage contacts, conversations, and campaigns. Work right from your desktop with the TextUs web app or use the Chrome extension alongside your ATS or CRM. Leverage the mobile app for on-the-go sending and responding.
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mcpo
A simple, secure MCP-to-OpenAPI proxy server
mcpo is a minimal bridge that exposes any MCP tool as an OpenAPI-compatible HTTP server. Instead of writing glue code, you point mcpo at an MCP server command and it generates REST endpoints and an OpenAPI spec that other systems (or LLM agent frameworks) can call immediately. This design lets you reuse a growing library of MCP servers with platforms that only understand HTTP+OpenAPI, unifying tool access across ecosystems. The project emphasizes “dead-simple” setup and pairs with Open WebUI... -
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CVPR 2025
Collection of CVPR 2025 papers and open source projects
CVPR 2025 curates accepted CVPR 2025 papers and pairs them with their corresponding code implementations when available, giving researchers and practitioners a fast way to move from reading to reproducing. It organizes entries by topic areas such as detection, segmentation, generative models, 3D vision, multi-modal learning, and efficiency, so you can navigate the year’s output efficiently. Each paper entry typically includes a title, author list, and links to the paper PDF and official or... -
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GeoDMA
Geographic feature extraction and data mining
GeoDMA is a plugin for TerraView software, used for geographical data mining. With a single image, the user can perform segmentation, attributes extraction, normalization and classification. -
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Consistency Models
Official repo for consistency models
consistency_models is the repository for Consistency Models, a new family of generative models introduced by OpenAI that aim to generate high-quality samples by mapping noise directly into data — circumventing the need for lengthy diffusion chains. It builds on and extends diffusion model frameworks (e.g. based on the guided-diffusion codebase), adding techniques like consistency distillation and consistency training to enable fast, often one-step, sample generation. The repo is implemented in PyTorch and includes support for large-scale experiments on datasets like ImageNet-64 and LSUN variants. ... -
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LM Human Preferences
Code for the paper Fine-Tuning Language Models from Human Preferences
lm-human-preferences is the official OpenAI codebase that implements the method from the paper Fine-Tuning Language Models from Human Preferences. Its purpose is to show how to align language models with human judgments by training a reward model from human comparisons and then fine-tuning a policy model using that reward signal. The repository includes scripts to train the reward model (learning to rank or score pairs of outputs), and to fine-tune a policy (a language model) with... -
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MANTI
MANTI - Mastering Advanced N-Termini Interpretation
MANTI is a one-stop shop N-termini annotation & evaluation solution. MANTI was previously (un)known as muda.pl ahead of v3.7, the project was renamed to MANTI.pl with v3.7 on 2019-06-24. It congregates information from different MaxQuant or DiaNN/MSFragger output files into a master file suitable explicitly for protein neo-termini analyses. The central anchor for the data congregation is the modificationSpecificPeptides.txt or diann-output.pr_matrix.tsv file - additional data is inferred... -
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CAM
Class Activation Mapping
This repository implements Class Activation Mapping (CAM), a technique to expose the implicit attention of convolutional neural networks by generating heatmaps that highlight the most discriminative image regions influencing a network’s class prediction. The method involves modifying a CNN model slightly (e.g., using global average pooling before the final layer) to produce a weighted combination of feature maps as the class activation map. -
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DensePose
A real-time approach for mapping all human pixels of 2D RGB images
...The repository includes the DensePose network architecture, training code, pretrained models, and dataset tools for annotation and visualization. DensePose is widely used in augmented reality, motion capture, virtual try-on, and visual effects applications because it enables real-time 3D human mapping from 2D inputs. The model architecture builds on Mask R-CNN, using additional regression heads to predict UV coordinates that map image pixels to 3D surfaces. -
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MANTI.pl / muda.pl
muda.pl - MQ unified data assembler
-------- ATTENTION START: RENAMING muda.pl was renamed to MANTI.pl with v3.7, project development can be tracked on the MANTI project page on sourceforge.net. Old versions remain here for archival purposes. -------- ATTENTION END muda.pl is an evaluation script (written in Perl) without great dependencies. It congregates information from 4 different MaxQuant output files into a master file suitable explicitly for protein neo-termini analyses. The central anchor for the data... -
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MUSE
A library for Multilingual Unsupervised or Supervised word Embeddings
...The code can align pre-trained monolingual embeddings (such as fastText) across dozens of languages and provides standardized evaluation scripts and dictionaries. By mapping languages into a common vector space, MUSE makes it straightforward to build cross-lingual applications where resources are scarce for some languages. The training and evaluation pipeline is lightweight and fast, so experimenting with different languages or initialization strategies is easy. Beyond dictionary induction, the learned embeddings are often used as building blocks for downstream tasks like classification, retrieval, or machine translation. -
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BioRec:Bird Census field data annotation
Recognizing biological data from a notebook.
This project helps to digitize field data for a certain Bird Census method. Namely, bird census based on personal inspection or small (~10 km^2) regions with recording birds' position and behaviour on paper. This project makes it easy to annotate such field data and to make this data available for statistical analysis. -
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It gives facility of collecting tweets through Twitter Streaming API w.r.t different search criteria and to save tweets in CSV and ARFF (WEKA) file formats.
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Dinapter:
Generate adaptation contracts between incompatible services
Dinapter automatically generates a mapping between methods of incompatible components/services based on their public interfaces and behaviors. It uses a combination of expert system and A* algorithm. Dinapter is the prototype resulting from a couple of research papers: * J.A. Martín, E. Pimentel. Automatic Generation of Adaptation Contracts, FOCLASA'08, ENTCS, 2008 - http://goo.gl/21iJZ * J.A. martín, E. -
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Ontology MApping FRAmework Toolkit allows to create semantic relations between two (source and target) ontologies, and apply such relations in translating source ontology instances into target ontology instances.
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Siafu simulates individual agents and their context, from home to city-wide scenarios. As a developer, you use the API to write your simulation for the purposes of data-set generation, test or visualization, optionally hooking it to your own application.
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Earnest is a A PHP-MYSQL AI EXPERT SYSTEM for creating powerful expert system easily. Its simple PHP API can also be called from JAVA, browsers or other software to perform GIS and other comparisons. Also has ability to create XML results.
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RegMAS (Regional Multi Agent Simulator) is a spatially explicit multi-agent model framework, developed in C++ language and designed for long-term simulations of effects of government policies over agricultural systems (farm sizes, incomes, land use..).
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EcoMod is an OpenGL application for 3D modelling, simulation and visualization of ecosystems. Trees are modelled and used within simulation to render the emerging natural phenomena of spontaneous afforestation process. Multidisciplinary.
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Allows approximate mapping between two different ontologies. The mapping is obtained combining sets of matchers that compare different features of elements from the two ontologies.
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MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.
