yashugupta786

#=======================================================================#
# extract_data.py                                                       #
#=======================================================================#
# usage: extract_data.py [-h] [-i INPUT_DIR] [-o OUTPUT_DIR]
#
# This program extracts provision numbers from a set of documents.
#
# optional arguments:
#  -h, --help            show this help message and exit
#  -i INPUT_DIR, --input_dir INPUT_DIR

yashugupta786

#!/usr/bin/env python
'''Crop an image to just the portions containing text.

Usage:

    ./crop_morphology.py path/to/image.jpg

This will place the cropped image in path/to/image.crop.png.

For details on the methodology, see

yashugupta786

# Keras==1.0.6
import numpy as np
from keras.models import Sequential
from keras.layers.recurrent import LSTM
from keras.layers.core import TimeDistributedDense, Activation
from keras.preprocessing.sequence import pad_sequences
from keras.layers.embeddings import Embedding
from sklearn.cross_validation import train_test_split
from sklearn.metrics import confusion_matrix, accuracy_score, precision_recall_fscore_support