As configured in my dotfiles.
start new:
tmux
start new with session name:
using System; | |
using System.Text; | |
using System.Net; | |
using System.Net.Sockets; | |
namespace Server | |
{ | |
class Program | |
{ |
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) |
**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 |
# 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) |
As configured in my dotfiles.
start new:
tmux
start new with session name:
##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
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 |
# Written by MSK | |
import glob | |
import cv2 | |
pngs = glob('./*.png') | |
for png in pngs: | |
img = cv2.imread(png) | |
cv2.imwrite(png[:-3] + 'jpg', img) |
7 | |
2 | |
1 | |
0 | |
4 | |
1 | |
4 | |
9 | |
5 | |
9 |
mkdir /truba/home/{username}/python3 | |
cd python3 | |
wget https://www.python.org/ftp/python/3.5.2/Python-3.5.2.tgz | |
tar zxfv Python-3.5.2.tgz | |
cd Python-3.5.2.tgz | |
./configure --prefix=/truba/home/{username}/python3 | |
make && make install | |
export PATH=/truba/home/{username}/python3/Python-3.5.2/:$PATH | |
export PYTHONPATH=/truba/home/{username}/python3/Python-3.5.2 |