Advertisement
Guest User

Untitled

a guest
May 19th, 2019
78
0
Never
Not a member of Pastebin yet? Sign Up, it unlocks many cool features!
Python 1.34 KB | None | 0 0
  1. from tensorflow.keras.models import Sequential
  2. from tensorflow.keras.layers import Convolution2D
  3. from tensorflow.keras.layers import MaxPooling2D
  4. from tensorflow.keras.layers import Flatten
  5. from tensorflow.keras.layers import Dense
  6.  
  7. classifier = Sequential()
  8. classifier.add(Convolution2D(32,3,3, input_shape = (64,64,3), activation = 'relu'))
  9. classifier.add(MaxPooling2D(pool_size = (2,2)))
  10. classifier.add(Flatten())
  11. classifier.add(Dense(128, activation = 'relu')) #output_dim =
  12. classifier.add(Dense( 1, activation = 'sigmoid'))
  13. classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
  14.  
  15. from tensorflow.keras.preprocessing.image import ImageDataGenerator
  16.  
  17. train_datagen = ImageDataGenerator(
  18.     rescale=1./255,
  19.     shear_range=0.2,
  20.     zoom_range=0.2,
  21.     horizontal_flip=True)
  22.  
  23. test_datagen = ImageDataGenerator(rescale=1./255)
  24.  
  25. training_set = train_datagen.flow_from_directory(
  26.     './train',
  27.     target_size=(64,64),
  28.     batch_size=32,
  29.     class_mode='binary')
  30.  
  31. test_set = train_datagen.flow_from_directory(
  32.     './test',
  33.     target_size=(64,64),
  34.     batch_size=32,
  35.     class_mode='binary')
  36.  
  37. from IPython.display import display
  38. from PIL import Image
  39.  
  40. classifier.fit_generator(
  41.     training_set,
  42.     steps_per_epoch=36,
  43.     epochs=3,
  44.     validation_data=test_set,
  45.     validation_steps=5)
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement