DrSleep

tensorflow-deeplab-resnet

DeepLab-ResNet rebuilt in TensorFlow

light-weight-refinenet

Light-Weight RefineNet for Real-Time Semantic Segmentation

tensorflow-deeplab-lfov

DeepLab-LargeFOV implemented in tensorflow

multi-task-refinenet

Multi-Task (Joint Segmentation / Depth / Surface Normas) Real-Time Light-Weight RefineNet

refinenet-pytorch

RefineNet-101 VOC in PyTorch

nas-segm-pytorch

Code for Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells, CVPR '19

DenseTorch

An easy-to-use wrapper for work with dense per-pixel tasks in PyTorch (including multi-task learning)

GDN

Code for "Global Deconvolutional Networks" paper (BMVC 2016)

deeplab-ver2-docker

Dockerfile for deeplab-public-ver2

pytorch-deeplab-v3-plus

DeepLab-v3+ in PyTorch

blitznet

Deep neural network for object detection and semantic segmentation in real-time. Official code for the paper "BlitzNet: A Real-Time Deep Network for Scene Understanding"

informative-drawings

Unpaired line drawing generation

solyanka

Source code for my blog posts

drsleep.github.io

blog

refinenet

RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

arch_summary

barrista

The best way to get your caffe served!

bme403

S.T. in BME III (Bio data programming), 2016-1

caffe

Caffe: a fast open framework for deep learning.

caffe-tensorflow

Caffe models in TensorFlow

deeplab-public-ver2

This repo was mirrored from here: https://bitbucket.org/aquariusjay/deeplab-public-ver2

epl_away_map

EPL Away Fixtures Map

example-app-speech-to-text-transcription

FlowNetPytorch

Pytorch implementation of FlowNet by Dosovitskiy et al.

football-stats-quiz

Football Stats Quiz game made in Streamlit

gpu_monitor

A simple visualisation of gpu consumption

kloppy

kloppy: standardizing soccer tracking- and event data

models

Models built with TensorFlow

openias.github.io

Blog for the Open Institute for Advanced Study

segment-anything

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