def deletar(name):
all_face_encodings = {}
pickle_file = 'dataset_faces.pickle'
try:
all_face_encodings = pickle.load(pickle_file)
except:
print("Arquivo vazio")
try:
all_face_encodings.pop(name)
pickle.safe_dump(all_face_encodings, pickle_file)
print("Depois : " + str(all_face_encodings))
except:
return "Ocorreu um erro ao salvar os dados"
return "Usuário removido com sucesso."
def atualizar(file, name):
all_face_encodings = {}
pickle_file = 'dataset_faces.pickle'
load_image = face_recognition.load_image_file(file)
image_encoding = face_recognition.face_encodings(load_image)[0]
try:
all_face_encodings = pickle.load(pickle_file)
except:
print("Arquivo vazio")
try:
all_face_encodings[name] = image_encoding
pickle.safe_dump(all_face_encodings, pickle_file)
except:
raise
return "Ocorreu um erro ao salvar os dados"
return "Foto atualizada com sucesso"
def cadastrar(file, name):
all_face_encodings = {}
pickle_file = 'dataset_faces.pickle'
load_image = face_recognition.load_image_file(file)
image_encoding = face_recognition.face_encodings(load_image)[0]
try:
all_face_encodings = pickle.load(pickle_file)
except:
print("Arquivo vazio")
print("Depois : " + str(all_face_encodings))
try:
all_face_encodings[name] = image_encoding
pickle.safe_dump(all_face_encodings, pickle_file)
except:
raise
return "Ocorreu um erro ao salvar os dados"
return image_encoding
def test_compress():
"""Test whether data compression is working.
"""
pk.safe_dump({"value": 1}, path_gz, enable_verbose=False)
assert pk.load(path_gz, enable_verbose=False) == {"value": 1}
os.remove(path_gz)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
from dataIO import js
from dataIO import pk
from dataIO import textfile
data = {
"name": "John",
"age": 18,
"favorite number": 3.1415926535,
"hobby": ["Music", "Sport"]
}
js.safe_dump(data,
"data.json",
indent_format=True,
float_precision=2,
enable_verbose=True)
pk.safe_dump(data, "data.pickle", enable_verbose=True)
s = "This\nis\nPython!"
textfile.write(s, "text.txt")