kechan

kechan

kechan

kechan

import numpy as np

# original image is 224x224x3 of dtype uint8 


renorm_image = np.reshape(original_image, (original_image.shape[0]*original_image.shape[1],3))

renorm_image = renorm_image.astype('float32')
renorm_image -= np.mean(renorm_image, axis=0)
renorm_image /= np.std(renorm_image, axis=0)

kechan

a = tf.constant(2)
b = tf.constant(3)
x = tf.add(a, b)

writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())

with tf.Session() as sess:
  print(sess.run(x))
  
writer.close() 

kechan

extension Double {   
   var km: Double { return self }   // This is stored as km, everything else will need conversion instead.   
   var mile: Double { return 0.6214 * self }
}

10.km
10.mile
let x = 10.0  // if user unit is miles

let dist = x/1.mile

kechan

let docsDir = FileManager().urls(for: .documentDirectory, in: .userDomainMask).first!
print(docsDir)

let archiveURL = docsDir.appendingPathComponent("landmark")
print(archiveURL.path)

class LandmarkClass : NSObject, NSCoding {
   var name = ""
   init(name: String) {
       self.name = name

kechan

// Paste this in Playground

import CoreData

let url = Bundle.main.url(forResource: "HikingApp", withExtension: "momd")

let model = NSManagedObjectModel(contentsOf: url!)

let container = NSPersistentContainer(name: "HikingApp")

kechan

// Paste this in Playground

infix operator ∘
prefix operator ∑^

typealias ItoD = (Int) -> Double

func *(lhs: Int, rhs: Double) -> Double {
    return Double(lhs)*rhs
}