| 43 | |
| 44 | |
| 45 | def create_model(): |
| 46 | model = Sequential() |
| 47 | model.add(Convolution2D(4, 5, 5, border_mode='valid',input_shape=(1,28,28))) |
| 48 | model.add(Activation('relu')) |
| 49 | |
| 50 | model.add(Convolution2D(8,3, 3, border_mode='valid')) |
| 51 | model.add(Activation('relu')) |
| 52 | model.add(MaxPooling2D(pool_size=(2, 2))) |
| 53 | |
| 54 | model.add(Convolution2D(16,3, 3, border_mode='valid')) |
| 55 | model.add(Activation('relu')) |
| 56 | model.add(MaxPooling2D(pool_size=(2, 2))) |
| 57 | |
| 58 | model.add(Flatten()) |
| 59 | model.add(Dense(128, init='normal')) |
| 60 | model.add(Activation('relu')) |
| 61 | |
| 62 | model.add(Dense(nb_class, init='normal')) |
| 63 | model.add(Activation('softmax')) |
| 64 | return model |
| 65 | |
| 66 | |
| 67 | ############# |