chexov

# coding: utf-8
import cv2
import h5py
import numpy

img = cv2.imread('/Users/chexov/opencv-lena.jpg', 1)

f = h5py.File('test2.hdf5', mode='w')

group = f.create_group("images")

chexov

export OPENCV_OPENCL_RUNTIME=""
find positives/ -type f | \
  xargs -P 8 -n 1 -INAME opencv_createsamples -bgcolor 0 -bgthresh 0 -maxxangle 1.1 -maxyangle 1.1 -maxzangle 0.5 -maxidev 40 -w 80 -h 40 -img 'NAME' -bg ./negs/negatives.txt -vec samples/NAME.vec -num 1 
 
wget 'https://raw.githubusercontent.com/wulfebw/mergevec/master/mergevec.py'
python mergevec.py  -v ./samples/cuts/ -o samples.vec


OPENCV_OPENCL_RUNTIME=NVIDIA:GPU:1 opencv_traincascade -data classifier -vec samples.vec -bg negs/negatives.txt   -numStages 20 -minHitRate 0.999 -maxFalseAlarmRate 0.5 -numPos 70000 -numNeg 78678 -w 80 -h 40 -mode ALL -precalcValBufSize 1024 -precalcIdxBufSize 1024

chexov

Tensorflow

System information

• OS - High Sierra 10.13
• Tensorflow - 1.4
• Xcode command line tools - 8.2 (Download from here: Xcode - Support - Apple Developer & Switch to different clang version: sudo xcode-select --switch/Library/Developer/CommandLineTools & check version: clang -v)
• Cmake - 3.7
• Bazel - 0.7.0

chexov

#!/bin/sh

NVIDIA_GPGKEY_SUM=d1be581509378368edeec8c1eb2958702feedf3bc3d17011adbf24efacce4ab5 && \
    NVIDIA_GPGKEY_FPR=ae09fe4bbd223a84b2ccfce3f60f4b3d7fa2af80 && \
    apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub && \
    apt-key adv --export --no-emit-version -a $NVIDIA_GPGKEY_FPR | tail -n +5 > cudasign.pub && \
    echo "$NVIDIA_GPGKEY_SUM  cudasign.pub" | sha256sum -c --strict - && rm cudasign.pub

echo "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/cuda.list
echo "deb http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/ /" > /etc/apt/sources.list.d/nvidia-machine-learning.list

chexov

```
Just put it into your code and import like this
  import android.org.apache.commons.codec.binary.Hex;

```


package android.org.apache.commons.codec.binary;

import java.nio.charset.Charset;

chexov

var zeroPad2 = function (n) {
    var _n = n + "";
    if (_n.length < 2) {
        return "0" + _n;
    } else {
        return _n;
    }
};
var zeroPad = function (n, width) {
    var z = "0";

chexov

Maven release plugin cheat sheet

Perform release dry run

During the dry run and again during the release proper you will be prompted for version information. The release plugin will attempt to guess the release, tag and snapshot versions. You can accept the values as is or supply your own.

mvn release:prepare -DdryRun=true

chexov

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

chexov

GPU as profile

lxc profile create gpu
lxc profile device add gpu /dev/nvidia0 unix-char path=/dev/nvidia0
lxc profile device add gpu /dev/nvidia1 unix-char path=/dev/nvidia1
lxc profile device add gpu /dev/nvidiactl unix-char path=/dev/nvidiactl
lxc profile device add gpu /dev/nvidia-uvm unix-char path=/dev/nvidia-uvm
lxc profile device add gpu  /dev/nvidia-uvm-tools unix-char path=/dev/nvidia-uvm-tools

lxc profile assign modelAgency default,gpu

chexov

#cloud-config

apt_sources:
    - source: "ppa:webupd8team/java"

package_upgrade: true
package_update: true
packages:
    - mysql-server
    - apache2-utils