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a guest Mar 20th, 2019 75 Never
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  1. model = Sequential()
  2.  
  3. #1st Conv layer
  4. model.add(Conv2D(filters = 32, kernel_size=(4,4), input_shape = (512,512,3), strides=2, activation=LeakyReLU(), padding='same'))
  5.  
  6. model.add(Conv2D(filters = 32, kernel_size=(4,4), strides=1, activation=LeakyReLU(), padding='same'))#input_shape = (256,256,32),
  7. model.add(MaxPooling2D(pool_size=(3,3),strides=2))
  8.  
  9. #2nd Conv layer
  10. model.add(Conv2D(filters=64, kernel_size=(4,4), strides=2, activation=LeakyReLU(), padding='same'))#input_shape = (127,127,32),
  11.  
  12. model.add(Conv2D(filters = 64, kernel_size=(4,4),  strides=1, activation=LeakyReLU(), padding='same'))#input_shape = (62,62,64),
  13.  
  14. model.add(MaxPooling2D(pool_size=(3,3),strides=2,padding='valid'))
  15.  
  16. #3rd Conv layer
  17. model.add(Conv2D(filters=128, kernel_size=(4,4), strides=1, activation=LeakyReLU(), padding='same'))#input_shape = (31,31,64),
  18.  
  19. model.add(Conv2D(filters = 128, kernel_size=(4,4),  strides=1, activation=LeakyReLU(), padding='same'))#input_shape = (32,32,128),
  20.  
  21. model.add(MaxPooling2D(pool_size=(3,3),strides=2,padding='valid'))
  22.  
  23. #4th Conv layer
  24. model.add(Conv2D(filters=256, kernel_size=(4,4), strides=1, activation=LeakyReLU(), padding='same'))#input_shape = (16,16,128),
  25.  
  26. model.add(MaxPooling2D(pool_size=(3,3),strides=2,padding='valid'))
  27.  
  28. #5th Conv layer
  29. model.add(Conv2D(filters=384, kernel_size=(4,4), strides=1, activation=LeakyReLU(), padding='same'))#input_shape = (8,8,256),
  30.  
  31. model.add(MaxPooling2D(pool_size=(3,3),strides=2,padding='valid'))
  32.  
  33. #6th Conv layer
  34. model.add(Conv2D(filters=512, kernel_size=(4,4), strides=1, activation=LeakyReLU(), padding='same'))#input_shape = (4,4,384),
  35.  
  36. model.add(MaxPooling2D(pool_size=(3,3),strides=2,padding='valid'))
  37.  
  38. #FC
  39. model.add(Flatten())
  40. #1st FC
  41. model.add(Dense(1024))
  42. model.add(Activation(LeakyReLU()))
  43. model.add(Dropout(0,5))
  44. #2nd FC
  45. model.add(Dense(1024))
  46. model.add(Activation(LeakyReLU()))
  47. model.add(Dropout(0,5))
  48. # Output Layer
  49. model.add(Dense(5))
  50. model.add(Activation('softmax'))
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