Search Results for "match" - Page 3
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Showing 123 open source projects for "match"
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1
openSkyMatch
Matches OpenScience Observatories images with astronomical catalogs
openSkyMatch is a collection of Linux shell and Python scripts designed for the OpenScience Observatories program. It automates the identification and matching of detected celestial objects in locally captured FITS images with entries in large-scale sky catalogs, notably Pan-STARRS1 DR2 (II/389/ps1_dr2). The toolkit supports data preprocessing, coordinate correlation, and catalog-based validation of astronomical detections. All tools are open-source and optimized for reproducibility and... -
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LangChain Extract
Did you say you like data?
...The project implements a lightweight web service that allows developers to define extraction schemas and apply them to various sources such as plain text, HTML, or PDF documents. Built using FastAPI and the LangChain framework, the application exposes a REST API that can process documents and return structured outputs that match user-defined JSON schemas. Developers can create reusable “extractors” that define what type of information should be pulled from a document, along with example prompts that improve extraction quality through in-context learning. -
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Evolutionary Algorithm
Evolutionary Algorithm using Python
...Rather than being a single monolithic library, this repository provides a series of self-contained examples showing how different population-based search methods solve optimization problems and adapt candidate solutions over generations. Users can explore basic genetic algorithm setups, match phrase examples, pathfinding challenges, and microbial GA variants, as well as evolution strategy approaches like NES. The project also links classical evolutionary approaches with neural networks, illustrating how evolution can be used for model training in reinforcement learning and supervised contexts. -
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VALL-E X
Open source implementation of Microsoft's VALL-E X zero-shot TTS model
...It is capable of synthesizing speech in English, Chinese, and Japanese from text while mimicking the voice characteristics of a speaker given only a short 3–10 second prompt. The model attempts to match not just timbre, but also tone, pitch, emotion, and prosody of the reference audio, resulting in highly personalized output. VALL-E-X supports zero-shot cross-lingual synthesis, meaning a monolingual speaker’s voice can be used to speak other languages without additional training. It also preserves aspects of the acoustic environment, such as background noise or reverb, making the generated audio feel more like it came from the same setting as the prompt. ... -
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5
CrossLinked
LinkedIn employee enumeration tool using search engine scraping
...CrossLinked is commonly used by penetration testers and security professionals during the reconnaissance phase to identify potential usernames or email address formats for a target organization. It also supports customizable naming templates, enabling users to generate usernames or email formats that match corporate account conventions. -
6
sense2vec
Contextually-keyed word vectors
sense2vec (Trask et. al, 2015) is a nice twist on word2vec that lets you learn more interesting and detailed word vectors. This library is a simple Python implementation for loading, querying and training sense2vec models. For more details, check out our blog post. To explore the semantic similarities across all Reddit comments of 2015 and 2019, see the interactive demo. -
7
Stable-Dreamfusion
Text-to-3D & Image-to-3D & Mesh Exportation with NeRF + Diffusion
A pytorch implementation of the text-to-3D model Dreamfusion, powered by the Stable Diffusion text-to-2D model. This project is a work-in-progress and contains lots of differences from the paper. The current generation quality cannot match the results from the original paper, and many prompts still fail badly! Since the Imagen model is not publicly available, we use Stable Diffusion to replace it (implementation from diffusers). Different from Imagen, Stable-Diffusion is a latent diffusion model, which diffuses in a latent space instead of the original image space. ... -
8
Point-E
Point cloud diffusion for 3D model synthesis
...The model works via a two-stage diffusion approach: first, it uses a text → image diffusion network to produce a synthetic 2D view consistent with the prompt; then a second diffusion model converts that image into a 3D point cloud. While it does not match the fine detail of some slower methods, the tradeoff in speed makes it practical for prototyping and interactive 3D generation. The repository includes inference scripts, utilities for converting point clouds to meshes (e.g. via signed distance function regression), sample notebooks, and weight checkpoints. It also provides documentation on limitations, usage instructions, and example outputs. -
9
Minimal text diffusion
A minimal implementation of diffusion models for text generation
...However, you can change this to any text file using the --train_data argument. Note that you may have to increase the sequence length (--seq_len) if your corpus is longer than the simple corpus. The other default arguments are set to match the best setting I found for the simple corpus. -
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10
LaserBlast
A Laser Cannon Strategy Game
...First I wanted to quickly test various game rules and strategies. Python and pygames made prototyping quick and easy. This is actually about the twentieth version of the game. Second I wanted to try the new match/case statements that were added in Python 3.10. I found lots of uses for match/case and I really like it. -
11
Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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Arxiv Sanity Lite
arxiv-sanity lite: tag arxiv papers of interest get recommendations
...Recommendations are generated with support vector machines trained on TF-IDF features extracted from paper abstracts. The web interface supports searching, ranking, sorting, and filtering the indexed collection. Optional daily emails can surface newly added papers that match a user’s interests. The project can be self-hosted with a Flask server and scheduled background update jobs. -
13
yesitsme
Simple OSINT script to find Instagram profiles by name
yesitsme is a Python-based OSINT utility designed to help investigators identify potential Instagram accounts associated with a specific person using limited identifying data. The script works by querying indexed public information and comparing obfuscated email addresses and phone numbers against user-provided inputs to estimate match confidence. It is intended to automate a time-consuming manual investigation process by aggregating candidate usernames and classifying them into match levels such as high, medium, or low. The tool requires an Instagram session cookie to operate and includes configurable timeout controls to help avoid detection or rate limiting during searches. ... -
14
The Fuck
Magnificent app which corrects your previous console command
The Fuck is an app that corrects errors in previous console commands. It works by matching these previous commands with a rule. When it finds a match, it creates a new command based on the matched rule and executes this command. It has numerous rules enabled by default, including ones for fixing misspelled commands, fixing wrong commands, spell checking and correcting failed commands, and many, many others. You can also create your own rules and set certain parameters. -
15
PyCls
Codebase for Image Classification Research, written in PyTorch
...It popularized families like RegNet and supports classic architectures (ResNet, ResNeXt) with clean implementations and consistent training recipes. The repository includes highly tuned schedules, augmentations, and regularization settings that make it straightforward to match reported accuracy without guesswork. Distributed training and mixed precision are first-class, enabling fast experiments on multi-GPU setups with simple, declarative configs. Model definitions are concise and modular, making it easy to prototype new blocks or swap backbones while keeping the rest of the pipeline unchanged. Pretrained weights and evaluation scripts cover common datasets, and the logging/metric stack is designed for quick comparison across runs. ... -
16
video-to-ascii
It is a simple python package to play videos in the terminal
...It processes each frame of a video, maps pixel brightness and color values to characters, and renders them in real time within terminal constraints. The tool adapts video resolution to match terminal dimensions, ensuring a coherent and readable output despite limited character space. It can optionally include audio playback when additional dependencies such as FFmpeg and PortAudio are installed. The project supports multiple rendering strategies and allows exporting ASCII output to files for sharing or reuse. It also includes color approximation using ANSI palettes to enhance visual fidelity within terminal limitations. ... -
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Linux-Intelligent-Ocr-Solution
Easy-OCR solution and Tesseract trainer for GNU/Linux
Linux-intelligent-ocr-solution Lios is a free and open source software for converting print in to text using either scanner or a camera, It can also produce text out of scanned images from other sources such as Pdf, Image, Folder containing Images or screenshot. Program is given total accessibility for visually impaired. A Tesseract Trainer GUI is also shipped with this package. Forum : https://groups.google.com/forum/#!forum/lios Video Tutorial :... -
18
FavFreak
Favicon hash–based reconnaissance tool for security research
...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. If a match is found, it displays the corresponding technology information in the output, helping researchers quickly identify potential targets or related infrastructure. This approach is particularly useful during reconnaissance phases of security assessments because many web services share identical favicon hashes. -
19
DETR
End-to-end object detection with transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture. ... -
20
Python Handout
Turn Python scripts into handouts with Markdown and figures
...Handout supports embedding executable exercises where learners can type code, run it in place, and receive immediate feedback inline; it also integrates seamlessly with charting libraries so that data visualizations can be interactive rather than static. With customizable styling and extension hooks, authors can tailor the interactive elements to match the look and feel of their content. -
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Reliable Metrics for Generative Models
Code base for the precision, recall, density, and coverage metrics
...In this paper, we show that even the latest version of the precision and recall (Kynkäänniemi et al., 2019) metrics are not reliable yet. For example, they fail to detect the match between two identical distributions, they are not robust against outliers, and the evaluation hyperparameters are selected arbitrarily. We propose density and coverage metrics that solve the above issues. -
22
Retro
Retro Games in Gym
RETRO (Retrieval-Enhanced Transformer) is a large language model architecture developed by OpenAI that augments transformer models with a retrieval mechanism. Instead of relying solely on learned parameters, RETRO retrieves relevant documents from a large external database during inference, allowing it to ground responses in external knowledge. This design improves factual accuracy, reduces hallucinations, and enables smaller models to perform comparably to much larger ones by leveraging... -
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This project is a set of usefull classes to manage data from de database to the user interface. Based on a dictionary who match the DB table, the panel will be created.
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gpt2-client
Easy-to-use TensorFlow Wrapper for GPT-2 117M, 345M, 774M, etc.
...You can play around with all four GPT-2 models in less than five lines of code. Install client via pip. The generation options are highly flexible. You can mix and match based on what kind of text you need generated, be it multiple chunks or one at a time with prompts. -
25
Fav-up
Look up IP addresses using favicon hashes via Shodan
...This technique is commonly used in security research and OSINT investigations to discover related infrastructure or services that may belong to the same organization. fav-up can retrieve favicon data from several sources, including local files, direct favicon URLs, or full web pages where the favicon is automatically extracted. fav-up then computes the favicon hash and performs Shodan queries to locate IP addresses that match the same hash. To support larger investigations, the tool can iterate over lists of URLs, domains, or favicon files in bulk. Results can be printed to the console or exported into structured formats such as CSV or JSON for further analysis and reporting.
