Svtter

"""Tools to compute sha256 of files and find duplicate files"""

import hashlib
import os

f = open("sha256.txt", "w")


def compute_sha256(file):
    with open(file, "rb") as f:

Svtter

import matplotlib.pyplot as plt
from keras.preprocessing import image



inx = 5000
x = x_train[inx]
x = x.reshape((1, ) + x.shape)

i = 1

Svtter

<template>
    <div id="app">
        <h1>test</h1>
        <p>{{ greeting }} world!</p>
    </div>
</template>

<script>
    export default {
        data: function () {

Svtter

The .npz file format is a zipped archive of files named after the variables they contain. The archive is not compressed and each file in the archive contains one variable in .npy format. For a description of the .npy format, see numpy.lib.format.

When opening the saved .npz file with load a NpzFile object is returned. This is a dictionary-like object which can be queried for its list of arrays (with the .files attribute), and for the arrays themselves.

Svtter

import tensorflow as tf 
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
print(sess.run(hello))

Svtter

import numpy as np

# shuffle the data.

idx = np.random.permutation(len(x_all))
x_all, y_all = x_all[idx], y_all[idx]

Svtter

#include <opencv/cv.h>
#include <iostream>

using namespace cv;

// sum up given row
long int sumup(Mat row, int width)
{
    std::cout << "Sumup" << std::endl;
    long int total = 0;

Svtter

• mnist_cnn
• imdb_cnn
• mnist.py

Svtter

# Put in const.py...:
# python2
class _const:
    class ConstError(TypeError): pass
    def __setattr__(self,name,value):
        if self.__dict__.has_key(name):
            raise self.ConstError, "Can't rebind const(%s)"%name
        self.__dict__[name]=value
import sys
sys.modules[__name__]=_const()

Svtter

import rospy
from sensor_msgs.msg import Image
from std_msgs.msg import String
from cv_bridge import CvBridge
import cv2
import numpy as np
import tensorflow as tf
from tensorflow.models.image.imagenet import classify_image