liviust’s gists

liviust / rank_metrics.py

Created February 1, 2018 22:11 — forked from bwhite/rank_metrics.py

Ranking Metrics

	"""Information Retrieval metrics

	Useful Resources:
	http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt
	http://www.nii.ac.jp/TechReports/05-014E.pdf
	http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf
	http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf
	Learning to Rank for Information Retrieval (Tie-Yan Liu)
	"""
	import numpy as np

liviust / install.sh

Created January 24, 2018 21:00 — forked from NLKNguyen/install.sh

Install Hadoop on Ubuntu 16.04

	# Copy line by line and paste to an interactive shell

	# Update system
	sudo apt-get update && sudo apt-get dist-upgrade

	# Install Java
	sudo add-apt-repository ppa:openjdk-r/ppa
	sudo apt-get update
	sudo apt-get install openjdk-7-jdk

liviust / install_tensorflow.sh

Created January 24, 2018 14:20 — forked from izmailoff/install_tensorflow.sh

install tensorflow on Fedora

	# install protobuf
	sudo dnf install protobuf*

	# install bazel
	# https://docs.bazel.build/versions/master/install-redhat.html
	sudo dnf copr enable vbatts/bazel
	sudo dnf install bazel

	# get TF src
	git clone https://github.com/tensorflow/tensorflow.git

liviust / CaffeBatchPrediction.cpp

Created May 16, 2017 17:26 — forked from erogol/CaffeBatchPrediction.cpp

Caffe c++ batch based prediction

	#include "caffeclassifier.h"

	CaffeClassifier::CaffeClassifier(const string& model_file,
	const string& trained_file,
	const string& mean_file,
	const string& label_file,
	const bool use_GPU,
	const int batch_size) {
	if (use_GPU)
	Caffe::set_mode(Caffe::GPU);

liviust / C++ Predict with caffe

Created May 16, 2017 17:25 — forked from onauparc/C++ Predict with caffe

sample code for caffe C++ prediction

liviust / swap_input_channels.py

Created May 15, 2017 15:55 — forked from shelhamer/swap_input_channels.py

Net Surgery

	import sys
	import numpy as np
	import scipy.io

	import caffe

	# take args for model arch (prototxt), input/output models (binaryproto ),
	# layer name, and channel permutation.
	arch_f, in_f, out_f = sys.argv[1:4]
	layer = sys.argv[4]

liviust / Readme.md

Created May 3, 2017 22:02 — forked from myfavouritekk/Readme.md

Extract dense optical flow and save as grayscale or RGB images

#Extract dense optical flow and save as grayscale or RGB images Copyright @ Kai Kang (myfavouritekk@gmail.com) 2016

##Dependencies

##Usages

# help messages

Liviu-Daniel liviust