Ando takuya-andou

## classifier_from_little_data_script_3.py
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.

It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data

In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/

## googlenet.py
from scipy.misc import imread, imresize

from keras.layers import Input, Dense, Convolution2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, merge, Reshape, Activation
from keras.models import Model
from keras.regularizers import l2
from keras.optimizers import SGD
from googlenet_custom_layers import PoolHelper,LRN


def create_googlenet(weights_path=None):
	'''This script goes along the blog post
	"Building powerful image classification models using very little data"
	from blog.keras.io.

	It uses data that can be downloaded at:
	https://www.kaggle.com/c/dogs-vs-cats/data

	In our setup, we:
	- created a data/ folder
	- created train/ and validation/ subfolders inside data/
	from scipy.misc import imread, imresize

	from keras.layers import Input, Dense, Convolution2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, merge, Reshape, Activation
	from keras.models import Model
	from keras.regularizers import l2
	from keras.optimizers import SGD
	from googlenet_custom_layers import PoolHelper,LRN


	def create_googlenet(weights_path=None):