RodrigoCMoraes

from nltk.tokenize import word_tokenize
import nltk
nltk.download('punkt')

def tokenize(string, to_lower=True, is_alpha=False):
  """Get string and return a list with tokens.
  
    Token is the most simple chain of characters without any type of separation.   

    Args:

RodrigoCMoraes

# https://gist.github.com/RodrigoCMoraes/d76890fb8149182e2522014f308660ae

import keras

def read_model(arch_file, weights_file, optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy']):
    """Read custom keras model from files
    
    Args:
        arch_file(str): json file with model architecture
        weights_file(str): h5 file with weights of model

RodrigoCMoraes

"""
    Get frame from webcam and display it in real time

    OpenCv version: 3.4.1
    Installed with command: pip install opencv-python
    Python version: 3.6.5 :: Anaconda, Inc.
"""
import cv2

"""

RodrigoCMoraes

from tqdm import tqdm
import requests

chunk_size = 1024

url = "http://www.nervenet.org/pdf/python3handson.pdf"

r = requests.get(url, stream = True)

total_size = int(r.headers['content-length'])

RodrigoCMoraes

# batch_size = 1024
# num_epochs = 20
# history = model.fit(X_train, train_labels,
#                     batch_size=batch_size,
#                     epochs=num_epochs, 
#                     validation_data=(X_val, val_labels))

# summarize history for accuracy
plt.plot(history.history['acc'])
plt.plot(history.history['val_acc'])

RodrigoCMoraes

#!/bin/bash

# install CUDA Toolkit v9.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb)
CUDA_REPO_PKG="cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb"
wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda-9-0

RodrigoCMoraes

from IPython.core.display import display, HTML
display(HTML("<style>.container { width:90% !important; }</style>"))

import warnings
warnings.filterwarnings('ignore')

RodrigoCMoraes

def pairwise_indexes(array, mode='comb'):
    """
    Get indexes pairwise from array
    
    Params:
        array(list or numpy.array): array with shape(N,) where N is array size
        mode: comb=combinatations or perm=permutations
        
    Returns:
        pairs(numpy.array): array with pair elements

RodrigoCMoraes

#!/bin/bash
# Delete all containers
docker rm $(docker ps -a -q)
# Delete all images
docker rmi $(docker images -q)

RodrigoCMoraes

import cv2
import numpy as np 

screen_width, screen_height = 1920, 1080
window_width, window_height = 1270, 720

path = "template.jpeg"
image = cv2.imread(path)
image_width, image_height = image.shape[:2]