def test_preprocessing(self):
test_cases = [
'This sentence should be converted to lowercase.',
'Twitter url should be removed! http://t.co/ba784',
'Stopwords like: me myself and i should be removed! :)',
'#Hashtag mentions will be deleted by preprocessing',
'Special characters like: $[ ] ( }{-.- :( >_< +.+ should be removed',
'@mentions to other users should be removed',
'Year numbers like 2014 will be remain in text'
]
target_results = [
'sentenc convert lowercas', 'twitter url remov',
'stopword like remov', 'mention delet preprocess',
'special charact like remov', 'user remov',
'year number like 2014 remain text'
]
processed_results = []
for sentence in test_cases:
processed_results.append(preprocessing.preprocessing(sentence))
message = 'Sentences of test cases are processed otherwise than desired'
self.assertEqual(target_results, processed_results, message)
targetfn = xray_dir + "/data/LL/" + filenum + ".jpg" target_arr = filename2arr(targetfn) # TODO: crop up ROI from target_arr filenum = "1" modelfn = xray_dir + "/data/train/L3/" + filenum + ".jpg" model_arr = filename2arr(modelfn) """ ################################### preprocessing ################################### """ from src.utils.preprocessing import preprocessing target = preprocessing(target_arr) model = preprocessing(model_arr) """ ################################### constructing pyramids and use sliding windows to match features. ################################### """ from src.utils.features import sift_descriptor m_kp, m_des = sift_descriptor(model, show=False) from skimage.transform import pyramid_gaussian from src.utils.util import sliding_window
import os import sys import inspect from src.utils.io import filename2arr """ ############################### set env path ############################### """ tests_dir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) # script directory src/ src_dir = os.path.dirname(tests_dir) xray_dir = os.path.dirname(src_dir) #xray directory os.chdir(xray_dir) sys.path.append(src_dir) filenum = '1' targetfn = xray_dir+ '/data/LL/' + filenum + '.jpg' target_arr = filename2arr(targetfn) from src.utils.preprocessing import preprocessing target = preprocessing(target_arr) from src.utils.features import sift_descriptor t_kp, t_des = sift_descriptor(target,show=True)
