Search Results for "raw"
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Showing 8 open source projects for "raw"
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1
Flower
Flower: A Friendly Federated Learning Framework
...Flower can be used with any machine learning framework, for example, PyTorch, TensorFlow, Hugging Face Transformers, PyTorch Lightning, scikit-learn, JAX, TFLite, MONAI, fastai, MLX, XGBoost, Pandas for federated analytics, or even raw NumPy for users who enjoy computing gradients by hand. -
2
wger
Self hosted FLOSS fitness/workout, nutrition and weight tracker
...The application will calculate the nutritional values (total energy, proteins, carbohydrates, etc.) of the entire plan and of each of the meals. Enter the weights and reps you've done for each exercise to generate diagrams that let you see at a glance how well you're doing. Of course, the raw numbers are still accessible. -
3
Pwntools
CTF framework and exploit development library
...This means that if you do import pwn or from pwn import , you will have access to everything you need to write an exploit. Calls pwnlib.term.init() to put your terminal in raw mode and implements functionality to make it appear like it isn’t. Tries to parse some of the values in sys.argv and every value it succeeds in parsing it removes. -
4
spacy-transformers
Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spaCy supports a number of transfer and multi-task learning workflows that can often help improve your pipeline’s efficiency or accuracy. Transfer learning refers to techniques such as word vector tables and language model pretraining. These techniques can be used to import knowledge from raw text into your pipeline, so that your models are able to generalize better from your annotated examples. You can convert word vectors from popular tools like FastText and Gensim, or you can load in any pre trained transformer model if you install spacy-transformers. You can also do your own language model pretraining via the spacy pre train command. ... -
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5
Grassroots DICOM
Cross-platform DICOM implementation
Grassroots DiCoM is a C++ library for DICOM medical files. It is accessible from Python, C#, Java and PHP. It supports RAW, JPEG, JPEG 2000, JPEG-LS, RLE and deflated transfer syntax. It comes with a super fast scanner implementation to quickly scan hundreds of DICOM files. It supports SCU network operations (C-ECHO, C-FIND, C-STORE, C-MOVE). PS 3.3 & 3.6 are distributed as XML files. It also provides PS 3.15 certificates and password based mecanism to anonymize and de-identify DICOM datasets. -
6
ReconSpider
Most Advanced Open Source Intelligence (OSINT) Framework
...ReconSpider can be used by Infosec Researchers, Penetration Testers, Bug Hunters, and Cyber Crime Investigators to find deep information about their target. ReconSpider aggregate all the raw data, visualize it on a dashboard, and facilitate alerting and monitoring on the data. Recon Spider also combines the capabilities of Wave, Photon and Recon Dog to do a comprehensive enumeration of attack surfaces. Reconnaissance is a mission to obtain information by various detection methods, about the activities and resources of an enemy or potential enemy, or geographic characteristics of a particular area. ... -
7
Rekall
Rekall Memory Forensic Framework
Rekall is a powerful memory forensics framework that turns raw RAM captures—or live system state—into structured artifacts investigators can query and script. It ships with a large collection of plugins that parse OS internals to recover processes, modules, sockets, registry hives, and file objects, even when rootkits try to hide them. The design emphasizes repeatability: investigators run well-defined analyses that produce timelines, indicators, and reports suitable for case work or automation. ... -
8
Flask-RESTful
Simple framework for creating REST APIs
...Flask-RESTful understands multiple kinds of return values from view methods. Similar to Flask, you can return any iterable and it will be converted into a response, including raw Flask response objects. Flask-RESTful also support setting the response code and response headers using multiple return values.
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