salihkaragoz

using System;
using System.Text;
using System.Net;
using System.Net.Sockets;


namespace Server
{
    class Program
    {

salihkaragoz

import socket
import time
import datetime

IPADDR = '192.168.1.141'
PORTNUM = 5600
PACKETDATA = "f1a525da11f6".encode()

while(True):
    s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM, 0)

salihkaragoz

**HEADER FILES**
deprecated.h
libvlc.h
libvlc_events.h
libvlc_media.h
libvlc_media_discoverer.h
libvlc_media_library.h
libvlc_media_list.h
libvlc_media_list_player.h
libvlc_media_player.h

salihkaragoz

# This lecture based on Stanford' Python Numpy Tutorial

def quicksort(arr):
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right = [x for x in arr if x > pivot]
    return quicksort(left) + middle + quicksort(right)

salihkaragoz

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

salihkaragoz

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

salihkaragoz

y_true = 2
y_pred = 0.2

if(K.backend()=="tensorflow"):
    import tensorflow as tf
    sess= tf.Session()
    with tf.device('/cpu:0'):
        pt = tf.where(tf.equal(y_true, 1), y_pred, 1 - y_pred)
    print(sess.run(pt))
if(K.backend()=="theano"):

salihkaragoz

import numpy as np
from pycocotools.coco import COCO
import os
import math
import keras
from keras.models import Sequential, Model
from keras.layers import Dense, Activation, Input, Flatten, Dropout
from keras.utils import plot_model
import cv2
import matplotlib.pyplot as plt

salihkaragoz

# Written by MSK
import glob                                                           
import cv2 
pngs = glob('./*.png')

for png in pngs:
    img = cv2.imread(png)
    cv2.imwrite(png[:-3] + 'jpg', img)

salihkaragoz

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