azamsharp

import tfcoreml as tf_converter
tf_converter.convert(tf_model_path = 'inception_v1_2016_08_28_frozen.pb',
                     mlmodel_path = 'InceptionV1.mlmodel',
                     output_feature_names = ['InceptionV1/Logits/Predictions/Softmax:0'])

azamsharp

import tfcoreml as tf_converter
tf_converter.convert(tf_model_path = 'inception_v1_2016_08_28_frozen.pb',
                     mlmodel_path = 'InceptionV1.mlmodel',
                     output_feature_names = ['InceptionV1/Logits/Predictions/Softmax:0'],
                     image_input_names = 'input:0',
                     class_labels = 'imagenet_slim_labels.txt'
                     )

azamsharp

import tfcoreml as tf_converter
tf_converter.convert(tf_model_path = 'inception_v1_2016_08_28_frozen.pb',
                     mlmodel_path = 'InceptionV1.mlmodel',
                     output_feature_names = ['InceptionV1/Logits/Predictions/Softmax:0'],
                     image_input_names = 'input:0',
                     class_labels = 'imagenet_slim_labels.txt',
                     red_bias = -1,
                     green_bias = -1,
                     blue_bias = -1,
                     image_scale = 2.0/255.0

azamsharp

# this script is used to download the images using the provided url
import requests
import ntpath

# the file which contain the images
image_urls_file_name = 'images_urls_cats.txt'
# the destination of the images inside the images folder
destination_folder = 'images/cat/'

# save image data

azamsharp

  import turicreate as tc

# load the images
data = tc.image_analysis.load_images('images', with_path = True)

data['label'] = data['path'].apply(lambda path:'dog' if 'dog' in path else 'cat')

print(data.groupby('label',[tc.aggregate.COUNT]))

# save the data

azamsharp

import turicreate as tc

# load the data
data = tc.SFrame('cats-dogs.sframe')

train_data, test_data = data.random_split(0.8)

model = tc.image_classifier.create(train_data, target='label')

predictions = model.predict(test_data)

azamsharp

class Block {
    
    var index :Int = 0
    var dateCreated :String
    var previousHash :String!
    var hash :String!
    var nonce :Int
    var data :String
    
    var key :String {

azamsharp

class Blockchain {
    
    private (set) var blocks :[Block] = [Block]()
    
    init(_ genesisBlock :Block) {
        
        addBlock(genesisBlock)
    }
    
    func addBlock(_ block :Block) {

azamsharp

class Block : Codable {
    
    var index :Int = 0
    var dateCreated :String
    var previousHash :String!
    var hash :String!
    var nonce :Int
    var message :String = ""
    private (set) var transactions :[Transaction] = [Transaction]()
    

azamsharp

class Transaction :Codable {
    
    var from :String
    var to :String
    var amount :Double
    
    init(from :String, to :String, amount :Double) {
        self.from = from
        self.to = to
        self.amount = amount