pmutua

How to Do a Clean Restart of a Docker Instance
If you are using Docker-Machine, make sure your are talking to the right one. Execute the command docker-machine ls to find which one is currently active. It is also recommended to always redo the command:
`eval "$(docker-machine env <docker machine name>)" `
Note: Deleting volumes will wipe out their data. Back up any data that you need before deleting a container.
Procedure
Stop the container(s) using the following command:
`docker-compose down`
Delete all containers using the following command:
`docker rm -f $(docker ps -a -q)`
Delete all volumes using the following command:

colematt

Source: F9, Help - Quick Start Guide

• Official site
• 10 min video tutorial
• Stack Overflow

Byobu is a suite of enhancements to tmux, as a command line
tool providing live system status, dynamic window management,
and some convenient keybindings:

omry

server:
  host: 127.0.0.1
  port: 8081

app:
  username: ${env:USER}

flask:
  ENV: production
  DEBUG: false

gagregrog

import cv2
import imutils
from imutils.video import VideoStream

# replace this with the url generated by the Wyze app
rtsp_url = "rtsp://<camera_name>:<some_uuid>@<some_ip>/live"

vs = VideoStream(rtsp_url).start()

while True:

1f0

import numpy as np
import cv2

cap = cv2.VideoCapture('rtmp://localhost/live/stream')

while(True):
    # Capture frame-by-frame
    ret, frame = cap.read()

    # Our operations on the frame come here

krishvishal

from model import Net
from trainer import Trainer 
import torch
from torch import nn
from matplotlib import pyplot as plt

model = Net()
ckpt = torch.load('path_to_checkpoint')
model.load_state_dict(ckpt['state_dict'])
filter = model.conv1.weight.data.numpy()

jimfleming

import matplotlib
import matplotlib.cm

import tensorflow as tf

def colorize(value, vmin=None, vmax=None, cmap=None):
    """
    A utility function for TensorFlow that maps a grayscale image to a matplotlib
    colormap for use with TensorBoard image summaries.

danielmahal

ffmpeg -i input.mov -vf mpdecimate,setpts=N/FRAME_RATE/TB output.mov

nomanr

package noman.counterhelper;

import android.os.Bundle;
import android.support.v7.app.AppCompatActivity;
import android.view.View;
import android.widget.Button;
import android.widget.TextView;
/**
 * Created by Noman on 11/8/2016.
 */

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward