xeron56

$connectstr_dbhost = '';
$connectstr_dbname = '';
$connectstr_dbusername = '';
$connectstr_dbpassword = '';

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server {
        listen 80 default_server;
        server_name _;
        root /var/www/zm;
        index index.php;

        location / {
                try_files $uri $uri/ /index.php?$args;
        }

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#CODE

#Generate root password
import random, string
password = ''.join(random.choice(string.ascii_letters + string.digits) for i in range(20))

#Download ngrok
! wget -q -c -nc https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
! unzip -qq -n ngrok-stable-linux-amd64.zip
#Setup sshd

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import xml.etree.ElementTree as ET
import os
import json

coco = dict()
coco['images'] = []
coco['type'] = 'instances'
coco['annotations'] = []
coco['categories'] = []

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"""
author: Timothy C. Arlen
date: 28 Feb 2018

Calculate Mean Average Precision (mAP) for a set of bounding boxes corresponding to specific
image Ids. Usage:

> python calculate_mean_ap.py

Will display a plot of precision vs recall curves at 10 distinct IoU thresholds as well as output

xeron56

"""
author: Timothy C. Arlen
date: 28 Feb 2018

Calculate Mean Average Precision (mAP) for a set of bounding boxes corresponding to specific
image Ids. Usage:

> python calculate_mean_ap.py

Will display a plot of precision vs recall curves at 10 distinct IoU thresholds as well as output

xeron56

'''
Extract a known face from a video.

Uses a combination of a deep learning CNN model to batch detect faces
in video frames, or a sequence of images, in GPU with CUDA and HoG to compare
the detected faces with a computed reference set of face encodings.
'''
from os import path, listdir
from typing import NamedTuple

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'''
Extract a known face from a video.

Uses a combination of a deep learning CNN model to batch detect faces
in video frames, or a sequence of images, in GPU with CUDA and HoG to compare
the detected faces with a computed reference set of face encodings.
'''
from os import path, listdir
from typing import NamedTuple

xeron56

# For Windows users# Note: <> denotes changes to be made

#Create a conda environment
conda create --name <environment-name> python=<version:2.7/3.5>

#To create a requirements.txt file:
conda list #Gives you list of packages used for the environment

conda list -e > requirements.txt #Save all the info about packages to your folder