imshashwataggarwal

from __future__ import division, print_function, absolute_import

from keras.models import Sequential, model_from_json
from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPool2D, BatchNormalization
from keras.optimizers import RMSprop
from keras.preprocessing.image import ImageDataGenerator
from keras.utils.np_utils import to_categorical
from keras.callbacks import ReduceLROnPlateau, TensorBoard

import h5py

mjdietzx

"""
Clean and simple Keras implementation of network architectures described in:
    - (ResNet-50) [Deep Residual Learning for Image Recognition](https://arxiv.org/pdf/1512.03385.pdf).
    - (ResNeXt-50 32x4d) [Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/pdf/1611.05431.pdf).
    
Python 3.
"""

from keras import layers
from keras import models

miguelgrinberg

#!flask/bin/python
from flask import Flask, jsonify, abort, request, make_response, url_for
from flask_httpauth import HTTPBasicAuth

app = Flask(__name__, static_url_path = "")
auth = HTTPBasicAuth()

@auth.get_password
def get_password(username):
    if username == 'miguel':

shlomibabluki

# coding=UTF-8
import nltk
from nltk.corpus import brown

# This is a fast and simple noun phrase extractor (based on NLTK)
# Feel free to use it, just keep a link back to this post
# http://thetokenizer.com/2013/05/09/efficient-way-to-extract-the-main-topics-of-a-sentence/
# Create by Shlomi Babluki
# May, 2013