tldrafael

import numpy as np

class inputGen:
    def __init__(self, batch_size, X, y, shuffle=True):
        self.batch_size = batch_size
        self.X = X
        self.y = y
        self.cursor = 0
        self.n_samples = X.shape[0]
        self.ids_sequence = np.arange(X.shape[0])

tldrafael

from glob import iglob

def return_impaths(dpath):
  impaths = [list(iglob('{}/*.{}'.format(dpath, e))) for e in ['png', 'jpg', 'jpeg']]
  impaths = sum(impaths, [])
  return impaths

tldrafael

# https://arxiv.org/pdf/1602.07360.pdf
#
from keras import backend as K
from keras.layers import Input, Convolution2D, MaxPooling2D, Activation, concatenate
from keras.layers import GlobalAveragePooling2D
from keras.models import Model


class SqueezeNet:
    def __init__(self, input_shape, n_classes):

tldrafael

from line_profiler import LineProfiler
def do_profile(follow=[]):
    def inner(func):
        def profiled_func(*args, **kwargs):
            try:
                profiler = LineProfiler()
                profiler.add_function(func)
                for f in follow:
                    profiler.add_function(f)
                profiler.enable_by_count()

tldrafael

# Install cuda-10.0 because the newest one (for now the version 10.2) mismatchs the tensorflow 1.14.0 requirements
wget https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd6
 
dpkg -i cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd6

apt-key add /var/cuda-repo-10-0-local-10.0.130-410.48/7fa2af80.pub

apt-get install cuda

# This cuda version install nvidia v410 drivers. Remove it.

tldrafael

import logging
from logging.handlers import RotatingFileHandler
import traceback

logger = logging.getLogger()
logger.setLevel(logging.DEBUG)

handler = RotatingFileHandler('app.log', mode='a', maxBytes=50e6, backupCount=2)
formatter = logging.Formatter('%(asctime)s,%(message)s', datefmt='%Y-%m-%d %H:%M:%S')
handler.setFormatter(formatter)

tldrafael

import traceback
import sys


try:
    pass
except Exception as e:
    traceback_info = ''.join(traceback.format_exception(*sys.exc_info()))
    logger.info(traceback_info)

tldrafael

xgb_params = {'objective': 'multi:softmax',
              'num_class': 19,
              'tree_method': 'exact',
#                      'max_bin': 64,
              'colsample_bytree': 0.75,
              'subsample': 0.75,
#               'lambda': 2,
#               'alpha': 2,
#               'min_child_weight': 10,
#               'max_delta_step': 10,

tldrafael

# Code adapted from skimage
# https://github.com/riaanvddool/scikits-image/blob/master/skimage/color/delta_e.py#L123

import numpy as np
import tensorflow as tf

def tf_deg2rad(deg):
    return (deg / 180) * np.pi

def tf_rad2deg(rad):

tldrafael

def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument('-d', type=str, help='directory path', dest='dpath')
    parser.add_argument('-f', type=str, help='filepath', dest='fpath')
    return parser.parse_args()


if __name__ == '__main__':
    args = parse_args()
    if not any([args.dpath, args.fpath]):