def main_app(doc_name1, doc_name2, queue=None, test_mode=False):
_global.init('hebrew', test_mode=test_mode)
output = ""
gui_output = ""
'''
Prepare Documents, Detection & Recognition Phases
'''
doc1 = init_doc(Document(doc_name1))
doc2 = init_doc(Document(doc_name2))
'''
Verification Phase
'''
compare_docs = CompareDocuments(doc1, doc2)
compare_docs.monkey_results()
compare_docs.letters_autoencoder_results()
s_count = compare_docs.ssim_count
s_pred = s_count / compare_docs.ssim_total
print("Ssim: count: {}, pred: {}".format(s_count, s_pred))
output = output + "Monkey Result:{}\nAE result: {}".format(\
compare_docs.monkey_results,\
compare_docs.letters_ae_results)
gui_output += "Algo1: Monkey Result:\n\t<{0}> [Confident: {1:.2f}%]\n".format(compare_docs.monkey_results['result'],\
compare_docs.monkey_results['precent']*100)
gui_output += "Algo2: AutoEncoder Letters Result:\n\t<{}> [Confident: {:.2f}%]\n\tResult By Predictions:\n\t<{}> [Confident: {:.2f}%]\n".format(\
compare_docs.letters_ae_results['result'],\
compare_docs.letters_ae_results['precent']*100,
compare_docs.letters_ae_results['result_by_predictions'],\
compare_docs.letters_ae_results['precent_by_predictions']*100)
gui_output += "\n\nFinal Result:\n\t<"
conclusion = compare_docs.monkey_results['result'] + ">" if\
compare_docs.monkey_results['result'] == compare_docs.letters_ae_results['result']\
else "Conflict>"
gui_output += conclusion
conclusion2 = "\n\tWith AE by predictions:\n\t<"
conclusion2 += compare_docs.monkey_results['result'] + ">" if\
compare_docs.monkey_results['result'] == compare_docs.letters_ae_results['result_by_predictions']\
else "Conflict>"
gui_output += conclusion2
if queue is not None:
queue.put(gui_output)
print(output)
# +:+ +:+ +:+ #
# By: gaennuye <*****@*****.**> +#+ +:+ +#+ #
# +#+#+#+#+#+ +#+ #
# Created: 2020/02/29 14:29:06 by gaennuye #+# #+# #
# Updated: 2020/03/02 17:15:08 by gaennuye ### ########lyon.fr #
# #
# **************************************************************************** #
import _global as g
import plot as p
import matplotlib.pyplot as plt
import numpy as np
import progressbar
g.init()
# Estimating the price depending on the mileage
def estimatePrice(km):
res = g.theta[1] * km + g.theta[0]
return res
# For each point, calculating the difference between the
# computed price and the "real" price with the current thetas
def computeDiff(points):
error = [0, 0]
for km, price in points:
print("")
print("True-Negative-Precent: mean:{0:.2f} std:{0:.2f}".format(
np.mean(tn_prec, axis=0), np.std(tn_prec, axis=0)))
print("False-Negative-Precent: mean:{0:.2f} std:{0:.2f}".format(
np.mean(fn_prec, axis=0), np.std(fn_prec, axis=0)))
print("False-Positive-Precent: mean:{0:.2f} std:{0:.2f}".format(
np.mean(fp_prec, axis=0), np.std(fp_prec, axis=0)))
print("True-Positive-Precent: mean:{0:.2f} std:{0:.2f}".format(
np.mean(tp_prec, axis=0), np.std(tp_prec, axis=0)))
if __name__ == "__main__":
if len(sys.argv) > 1:
if 'by_vectors' in sys.argv:
BY_VECTORS = True
_global.init('hebrew', monkey_by_vectors=BY_VECTORS)
if sys.argv[1] == 'conf_matrix':
test_conf_matrix()
sys.exit(0)
if sys.argv[1] == 'all_same':
test_all_same()
sys.exit(0)
TEST_FILE_1 = sys.argv[1]
TEST_FILE_2 = sys.argv[2]
test_model(TEST_FILE_1, TEST_FILE_2)
else:
print(
'Usgae Option1: python test_monkey <file1> <file2> [by_sum/by_vectors]'
)
print('Usage Option2: python test_monkey all_same [by_sum/by_vectors]')
compare_docs = CompareDocuments(doc1, doc2)
get_ae_monkey_results(s, compare_docs)
s.count_num_of_tests += 1
if test_random_different != 0:
for i in range(test_random_different):
sampled_list = random.sample(all_files, 2)
doc1 = get_doc_by_name(all_docs, sampled_list[0])
doc2 = get_doc_by_name(all_docs, sampled_list[1])
if doc1.name.replace('b','') == doc2.name or doc2.name.replace('b','') == doc1.name\
or doc1.name == doc2.name:
continue
s.same_author = False
print("\n---------------------")
print("Test: {} {}".format(doc1.name, doc2.name))
compare_docs = CompareDocuments(doc1, doc2)
get_ae_monkey_results(s, compare_docs)
s.count_num_of_tests += 1
print_ae_monkey_results(s, len(b_files))
if __name__ == "__main__":
# if(len(sys.argv) < 2):
# print("Usage: python main.py <[save_all]/[file_name]> ")
# sys.exit(1)
#TODO: think how to determine monkey algo by_sum/by_vectors
_global.init('hebrew', monkey_by_vectors=True, print_globals=True)
test_all_same(106)
# main_app('10.tiff', '14.tiff', test_mode=True)
done_list.append(doc_name)
file = open(done_path, "a")
file.write("{}{}".format(doc_name,"\n"))
file.close()
def main_save_all():
done_list = read_done_file() # read the files we already done with
for root, dirs, files in os.walk(_global.DATA_PATH):
for file in files:
doc_name = file.split('.')[0]
print(doc_name)
if doc_name in done_list:
print("{} already done".format(file))
continue
img_name = _global.DATA_PATH + file
img = get_prepared_doc(img_name)
lines = get_lines(img, img_name)
letters = get_letters(lines)
found_letters = save_letters(letters, doc_name)
write_done_file(done_list,doc_name)
print("done")
if __name__ == "__main__":
_global.init('hebrew')
createOutputDirs() # create the folders to collect the data
main_save_all()