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mbencherif's Projects

cvzone icon cvzone

This is a Computer vision package that makes its easy to run Image processing and AI functions. At the core it uses OpenCV and Mediapipe libraries.

cyclegan icon cyclegan

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

d2l-en icon d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

data-visualisation-using-streamlit icon data-visualisation-using-streamlit

Streamlit’s open-source app framework is the easiest way for data scientists and machine learning engineers to create beautiful, performant apps

datacamp-light icon datacamp-light

Convert any blog or website to an interactive learning platform for data science

datasets icon datasets

Utility stuff for downloading and processing datsets

datasets2darknet icon datasets2darknet

Modular tool that extracts images and labels from multiple datasets and parses them to Darknet format.

davenet-pytorch icon davenet-pytorch

Deep Audio-Visual Embedding network (DAVEnet) implementation in PyTorch

daz3dcharacterue4 icon daz3dcharacterue4

Demonstration of an easy way to import a character from Daz Studio to Unreal Engine.

dd-net icon dd-net

A lightweight network for body/hand action recognition

de-stress icon de-stress

Prototype German Computer-Assisted Pronunciation Training tool for lexical stress errors

dee icon dee

Dee - the DeepLens Educating Entertainer #AWSDeepLensChallenge

deep-high-resolution-net.pytorch icon deep-high-resolution-net.pytorch

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

deep-learning-book icon deep-learning-book

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

deep-learning-containers icon deep-learning-containers

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

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