marvin

import socket

HOST = 'localhost'
PORT = 9876
ADDR = (HOST,PORT)
BUFSIZE = 4096
videofile = "videos/royalty-free_footage_wien_18_640x360.mp4"

bytes = open(videofile).read()

n3wtron

#!/usr/bin/python
'''
	Author: Igor Maculan - n3wtron@gmail.com
	A Simple mjpg stream http server
'''
import cv2
import Image
import threading
from BaseHTTPServer import BaseHTTPRequestHandler,HTTPServer
from SocketServer import ThreadingMixIn

yetithefoot

{url:'stun:stun01.sipphone.com'},
{url:'stun:stun.ekiga.net'},
{url:'stun:stun.fwdnet.net'},
{url:'stun:stun.ideasip.com'},
{url:'stun:stun.iptel.org'},
{url:'stun:stun.rixtelecom.se'},
{url:'stun:stun.schlund.de'},
{url:'stun:stun.l.google.com:19302'},
{url:'stun:stun1.l.google.com:19302'},
{url:'stun:stun2.l.google.com:19302'},

oneyoung

    private void doTakePicture(final int cameraId) throws Exception {
         /*
         Camera class is not thread-safe, and is meant for use from one event thread. 
         Most long-running operations (preview, focus, photo capture, etc) happen asynchronously
         and invoke callbacks as necessary. 
         Callbacks will be invoked on the event thread open(int) was called from.
         This class's methods must never be called from multiple threads at once.
         */
         
        /* Important: mCamera object must be alloc in another Thread, othwerwise, callback will NOT be invoked.

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

poolio

def _phase_shift(I, r):
    bsize, a, b, c = I.get_shape().as_list()
    X = tf.reshape(I, (bsize, a, b, r, r))
    X = tf.transpose(X, (0, 1, 2, 4, 3))  # bsize, a, b, 1, 1
    X = tf.split(1, a, X)  # a, [bsize, b, r, r]
    X = tf.concat(2, [tf.squeeze(x, [1]) for x in X])  # bsize, b, a*r, r
    X = tf.split(1, b, X)  # b, [bsize, a*r, r]
    X = tf.concat(2, [tf.squeeze(x, [1]) for x in X])  # bsize, a*r, b*r
    return tf.reshape(X, (bsize, a*r, b*r, 1))

omimo

# Create a simple TF Graph 
# By Omid Alemi - Jan 2017
# Works with TF <r1.0

import tensorflow as tf

I = tf.placeholder(tf.float32, shape=[None,3], name='I') # input
W = tf.Variable(tf.zeros_initializer(shape=[3,2]), dtype=tf.float32, name='W') # weights
b = tf.Variable(tf.zeros_initializer(shape=[2]), dtype=tf.float32, name='b') # biases
O = tf.nn.relu(tf.matmul(I, W) + b, name='O') # activation / output

revsic

# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

rwb27

from __future__ import print_function
import PIL.Image
import PIL.ExifTags
import sys
import os

def formatted_exif_data(image):
    """Retrieve an image's EXIF data and return as a dictionary with string keys"""
    # with thanks to https://stackoverflow.com/questions/4764932/in-python-how-do-i-read-the-exif-data-for-an-image
    exif_data = {}

gnperdue

from __future__ import print_function
from __future__ import absolute_import
from __future__ import division

import os
import h5py
import numpy as np
import tensorflow as tf

# Get path to data