Use git lfs
to track very big files. For more info about github lfs, see here.
Ignore all intermediate files of UE4, only left those essential files to run the project.
import numpy as np | |
import StringIO | |
filename = 'C:/qiuwch/workspace/cnpy/cnpy/cnpy/arr1.npy' | |
arr = np.load(filename) | |
print 'Loading from file %s is done' % filename | |
print arr.shape | |
# (64, 64, 128) = 524288 | |
# 8388688, file size |
project_folder=$1 | |
if [[ -z ${project_folder} ]]; then | |
echo Please specify project folder | |
else | |
echo Project folder is ${project_folder} | |
rm -rf ${project_folder}/Plugins | |
cp -r /c/qiuwch/workspace/unrealcv/unrealcv/Plugins ${project_folder} | |
fi |
double random_num = (double)rand() / RAND_MAX; | |
for (k = 0; k <= MAX_INTENSITY; k++) | |
{ | |
if (random_num < probs[k]) | |
{ | |
synthesized[i*im_width+j] = k; // update synthesized image | |
break; | |
} | |
else | |
random_num = random_num - probs[k]; |
identify *.png |
Use git lfs
to track very big files. For more info about github lfs, see here.
Ignore all intermediate files of UE4, only left those essential files to run the project.
import unittest, time, random | |
from testcfg import client | |
class FPSCounter: | |
def __init__(self): | |
self.start_index = 0 | |
self.start_time = time.time() | |
def tick(self, current_index): | |
current_time = time.time() |
class Solution { | |
vector<int> a; | |
public: | |
Solution(vector<int> nums) : a(nums) {} | |
/** Resets the array to its original configuration and return it. */ | |
vector<int> reset() { return a; } | |
/** Returns a random shuffling of the array. */ | |
vector<int> shuffle() { |
folder_name=${PWD##*/} | |
unrealcv_zip=unrealcv-5c4762b.zip | |
if [ ${folder_name} = 'plugins' ] || [ ${folder_name} = 'Plugins' ]; then | |
echo "Download plugin" | |
wget www.cs.jhu.edu/~qiuwch/unrealcv-plugin/${unrealcv_zip} -c | |
echo "Extract files from zip" | |
unzip -q -d unrealcv ${unrealcv_zip} | |
else | |
echo "Please run this script in Plugins folder" |
%pylab inline | |
import pandas as pd | |
import sqlite3 | |
con = sqlite3.connect("../Project_202a/yelp.db") | |
df = pd.read_sql(“select * from xx", con) | |
import MySQLdb | |
import pandas as pd | |
db = MySQLdb.connect(host="localhost", # your host, usually localhost |
"""Simple utility script for semi-gracefully downgrading v3 notebooks to v2""" | |
import io | |
import os | |
import sys | |
from IPython.nbformat import current | |
def heading_to_md(cell): | |
"""turn heading cell into corresponding markdown""" |