[c#] task cancelation token

https://binary-studio.com/2015/10/23/task-cancellation-in-c-and-things-you-should-know-about-it/

[C#] Create Method Flow and Run Flow

        static void Main( string [ ] args )
        {
            Func temp = new Func(x =>
            {
                Console.WriteLine("temp done // input is : " +  x.ToString());
                return "g0";

            } );
            Func temp1 = new Func(x =>  {
                Console.WriteLine("temp1 done");
                return "g1";

            } );
            Func temp2 = new Func(x =>  {
                Console.WriteLine("temp2 done");
                return 4.5;

            } );
            List any = new List();
            any.Add( temp );
            any.Add( temp1 );
            any.Add( temp2 );

            Console.WriteLine( "anycount = " + any.Count.ToString() );
            var result = runme( 0, any , 10 );
            Console.WriteLine( result );
            Console.ReadLine();
        }


        static object runme( int idx , List list , object input  )
        {
            Console.WriteLine( idx );
            if ( idx == list.Count )
            {
                return input;
            }
            var output =  list [ idx ].DynamicInvoke( input );
            return runme( idx + 1 , list , output );
        }

[ Python] Tensorflow on windows10 and vision lib setting

Install Anadonda Installer 4.2.1

Install Tensorflow

Install keras (option)

Install opencv3

-- conda install -c https://conda.binstar.org/menpo opencv3

[TF] tensor to ndarray

https://stackoverflow.com/questions/34097281/how-can-i-convert-a-tensor-into-a-numpy-array-in-tensorflow


predict =   tf.argmax(model, 1)
result =    sess.run(predict , feed_dict = {
    X: x_data,
    Y: y_data,
    keep_prob: 1
    })

print(type(result)) << ndarray
print( 'Predict' , result)

[keras] image generater

from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
import cv2
import numpy as np


datagen = ImageDataGenerator(
        rotation_range=180,
        width_shift_range=0.5,
        height_shift_range=0.5,
        shear_range=0.3,
        zoom_range=0.6,
        horizontal_flip=True,
        vertical_flip = True,
        fill_mode = "wrap")


img = cv2.imread(r"C:\image data\test\defect 001.jpg", 0)

#tensorflow backend
x = img_to_array(img)  # this is a Numpy array with shape (150, 150 , 1)

x = x.reshape( (1,) + x.shape )  # this is a Numpy array with shape (1, 150, 150 , 1~3(ch) )
i = 0
for batch in datagen.flow_from_directory( directory= r"C:\image data\defect"
                                         , target_size = (64,64)
                                         , color_mode = "grayscale"
                                         , batch_size=1
                                         , shuffle = True
                                         , save_to_dir=r'C:\image data\test\result'
                                         , save_prefix='defect'
                                         ):
    i += 1
    if i > 50000:
        break

new keras install

I uninstalled Keras using 

pip uninstall keras

Then I executed the following commands.

1. C:\Users\tjhau>conda create -n keras_tensorflow python=3.5.2 anaconda=4.3
2. C:\Users\tjhau>activate keras_tensorflow
3. C:\Users\tjhau>conda install -c conda-forge tensorflow keras

I understand that keras will be available in a directory after I execute the command 

 C:\Users\tjhau>activate keras_tensorflow

Thanks for your help.

[python] keras image dim converting

keras image dim convert

tensorflow image <-> theano image

https://github.com/fchollet/keras/issues/3994