dryuna Goto Github PK

neon

Nervana's python based Deep Learning Framework

nmt

TensorFlow Neural Machine Translation Tutorial

objectdetectionusingcntk

Fast R-CNN Object Detection on Azure using CNTK

opencv

Open Source Computer Vision Library

opencv_contrib

Repository for OpenCV's extra modules

opencv_dollar_detector

This is a port of Dóllar person detector to OpenCV in C++

opennmt-py

Open-Source Neural Machine Translation in PyTorch http://opennmt.net/

opentld

Official source code for TLD

optics_clustering

MATLAB Implementation of the OPTICS unsupervised clustering algorithm

partsbaseddetector

C++ implementation of Deva Ramanan's "Articulated Pose Estimation with Flexible Mixtures of Parts"

pcl

Point cloud library

pdist

Distance functions on subsets of matrices

person_detector

Our ROS-Node to do person detection

persondetector

(C++) Implementation of person detector with Kalman Filter

persondetector-1

A python based person detector using OpenCv.

pg_bow_demo

Image Classification using Bag of Words and Spatial Pyramid BoW

pipol_tracker

Multi target people tracker for mobile robots. It uses multiple detector modalities, is based on particle filtering and outputs a set of nearb person positions.

pmtk3

Probabilistic Modeling Toolkit for Matlab/Octave.

pooled_time_series

PoT java implementation

pso-clustering

PSO-Clustering algorithm [Matlab code]

psvm

proportion-SVM (pSVM, $\propto$SVM) for learning with label proportions

py-faster-rcnn

Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

python_brisk_demo

Quick demo using BRISK feature descriptors in Python to identify and then extract a target image from a scene.

pyvision

Official github branch from the source forge site.

rcnn-depth

Learning Rich Features from RGB-D Images for Object Detection and Segmentation

ret_2014

rnn

Recurrent Neural Network library for Torch7's nn

samf

samf code

scikit-learn

scikit-learn: machine learning in Python

shallowlearn

A collection of supervised learning models based on shallow neural network approaches (e.g., word2vec and fastText) with some additional exclusive features. Written in Python and fully compatible with Scikit-learn.