def criminalinfo():
if 'auth' in session:
try:
c, conn = connection()
if request.method == "POST":
name = request.form['name']
nic = request.form['nic']
age = request.form['age']
add01 = request.form['add01']
add02 = request.form['add02']
add03 = request.form['add03']
eye = request.form['eye']
hair = request.form['hair']
gender = request.form['gender']
data = c.execute("SELECT * FROM criminalinfo WHERE nic=(%s)", (thwart(nic)))
if int(data) > 0:
print(data)
else:
c.execute(
"INSERT INTO criminalinfo (nic,name,age,addressline01,addressline02,addressline03,eyecolor,haircolor,gender) values(%s,%s,%s,%s,%s,%s,%s,%s,%s)",
(thwart(nic), thwart(name), thwart(age), thwart(add01), thwart(add02), thwart(add03), thwart(eye),
thwart(hair), thwart(gender)))
conn.commit()
c.close()
conn.close()
target = os.path.join(APP_ROOT, 'uploads/train/' + nic)
print(target)
if not os.path.isdir(target):
os.mkdir(target)
count = 0
for file in request.files.getlist('img'):
print(file)
count = count + 1
filename = file.filename
print(filename)
destination = "/".join([target, filename])
print(destination)
file.save(destination)
# ttt
obj = preprocesses(TRAIN_FOLDER, PRE_FOLDER)
nrof_images_total, nrof_successfully_aligned = obj.collect_data()
print('Total number of images: %d' % nrof_images_total)
print('Number of successfully aligned images: %d' % nrof_successfully_aligned)
print("Training Start")
obj = training(PRE_FOLDER, MODEL_DIR, CLASSIFIER)
get_file = obj.main_train()
print('Saved classifier model to file "%s"' % get_file)
# flash('User registeration succeeded please log in', 's_msg')
return jsonify(success=["User Registration Success"], value=True)
except Exception as e:
return (str(e))
print(e)
else:
return render_template("login.html", data="please log in")
return render_template("criminalinfo.html")
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
from packages import classifier
datadir = './pre_img'
modeldir = './models/20170511-185253.pb'
classifier_filename = './class/classifier.pkl'
print("Training Start")
obj = classifier.training(datadir, modeldir, classifier_filename)
get_file = obj.main_train()
print('Saved classifier model to file "%s"' % get_file)
sys.exit("All Done")
import sys
from packages.classifier import training
datadir = './preprocessed_img'
modeldir = './models/20180408-102900'
classifier_filename = './class/classifier.pkl'
eval_score_path = './class/accuracy_score.txt'
print("Training Start")
obj = training(datadir, modeldir, classifier_filename, eval_score_path)
get_file = obj.main_train()
print('Saved classifier model to file "%s"' % get_file)
sys.exit("All Done")