VolodymyrChapman

VolodymyrChapman's Stars

• ultralytics/yolov5

  YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

  Language:Python51.7k3729.3k16.5k

• facebookresearch/sam2

  The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook13.3k764001.3k

• facebookresearch/dinov2

  PyTorch code and models for the DINOv2 self-supervised learning method.

  Language:Jupyter Notebook9.5k96411850

• OWASP/wstg

  The Web Security Testing Guide is a comprehensive Open Source guide to testing the security of web applications and web services.

  Language:Dockerfile7.5k3413491.4k

• justcallmekoko/ESP32Marauder

  A suite of WiFi/Bluetooth offensive and defensive tools for the ESP32

  Language:C++6.4k138425678

• EvolvingLMMs-Lab/lmms-eval

  Accelerating the development of large multimodal models (LMMs) with one-click evaluation module - lmms-eval.

  Language:Python2.2k4235178

• fepegar/torchio

  Medical imaging toolkit for deep learning

  Language:Python2.1k19465240

• jrfiedler/causal_inference_python_code

  Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins

  Language:Jupyter Notebook1.3k522389

• moshi4/pyCirclize

  Circular visualization in Python (Circos Plot, Chord Diagram, Radar Chart)

  Language:Python789104550

• Hari-prasaanth/Web-App-Pentest-Checklist

  A OWASP Based Checklist With 500+ Test Cases

  660120137

• Yijunmaverick/UniversalStyleTransfer

  The source code of NIPS17 'Universal Style Transfer via Feature Transforms'.

  Language:Lua602291589

• Aptive/penetration-testing-tools

  Penetration Testing tools - one repo to clone them all... containing latest pen testing tools

  524442188

• prov-gigapath/prov-gigapath

  Prov-GigaPath: A whole-slide foundation model for digital pathology from real-world data

  Language:Python448611262

• McGill-NLP/medal

  Large medical text dataset curated for abbreviation disambiguation, designed for natural language understanding pre-training in the medical domain

  Language:Python25011741

• florencejt/fusilli

  A Python package housing a collection of deep-learning multi-modal data fusion method pipelines! From data loading, to training, to evaluation - fusilli's got you covered 🌸

  Language:Python1665413

• mlcommons/medperf

  An open benchmarking platform for medical artificial intelligence using Federated Evaluation.

  Language:Python1481329232

• owkin/HistoSSLscaling

  Code associated to the publication: Scaling self-supervised learning for histopathology with masked image modeling, A. Filiot et al., MedRxiv (2023). We publicly release Phikon 🚀

  Language:Jupyter Notebook14851111

• NanoNets/ocr-with-tesseract

  A comprehensive tutorial for OCR in python using Tesseract-OCR and OpenCV

  Language:Jupyter Notebook1186371

• pietrocarbo/deep-transfer

  PyTorch implementation of "Universal Style Transfer via Feature Trasforms"

  Language:Python8881119

• georg-wolflein/pathology-foundation-models

  List of pathology feature extractors and foundation models

  73237

• DIAGNijmegen/pathology-hooknet

  Language:Jupyter Notebook5652310

• LinkedInLearning/advanced-ai-transformers-for-computer-vision-3085710

  This repo is for the Linkedin Learning course: Advanced AI: Transformers for Computer Vision

  Language:Jupyter Notebook349033

• choosehappy/HoverFast

  Blazing fast nuclei segmentation for brightfield Whole Slide Images

  Language:Jupyter Notebook30544

• BiomedicalMachineLearning/HEMnet

  A neural network software for using Molecular labelling to improve pathological annotation of H and E tissues

  Language:Jupyter Notebook29507

• serrob23/falsecolor

  FalseColor Python is a rapid digital staining module designed for translating two-channel fluorescence images (i.e. a nuclear and cytoplasmic stain) to the traditional H&E histopathology color space.

  Language:Jupyter Notebook29327

• fuscc-deep-path/sc_MTOP

  sc-MTOP is an analysis framework based on deep learning and computational pathology. This framework aims to characterize the tumor ecosystem diversity at the single-cell level. This code provide 1) Hover-Net-based nuclear segmentation and classification; 2) Nuclear morphological and texture feature extraction; 3) Multi-level pairwise nuclear graph construction and spatial topological feature extraction.

  Language:Python283116

• jmhb0/o2vae

  O2VAE: a model for orientation-invariant representation learning (phenotyping) in cell biology data

  Language:Python24423

• georg-wolflein/good-features

  Official code for the paper "A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification"

  Language:Jupyter Notebook17112

• MECLabTUDA/Med-NCA

  Language:Python8001

• KatherLab/visualizing_image_embeddings

  Language:Python2100