import cv2
from src.controller.video_capture.VideoCapture import VideoCapture
from src.debug.debugutils import DebugUtils
debug = DebugUtils.get_instance()
# TODO get_event
class VideoCaptureOpenCV(VideoCapture):
def __init__(self, camera):
super().__init__(camera)
# rtsp://USUARIO:SENHA@IP:PORTA/cam/realmonitor?channel=1&subtype=0
if camera.camera_string == '0':
camera.camera_string = 0
self.video_capturer = cv2.VideoCapture(camera.camera_string)
def initialize(self):
# self.videoCap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc('H', '2', '6', '4'));
if not self.video_capturer.isOpened():
debug.msg("Cannot open the video cam")
return False
# TODO nao funciona
# self.video_capturer.set(cv2.CAP_PROP_FRAME_HEIGHT, self.camera.y_res)
# self.video_capturer.set(cv2.CAP_PROP_FRAME_WIDTH, self.camera.x_res)
return True
def rewind(self):
self.video_capturer.set(cv2.CAP_PROP_POS_FRAMES, 1)
def test_face_trainer_lfw(self):
tfe = tec.create_tf_env_default()
# Experiment LFW
exp = tec.create_experiment('lfw', tfe)
logfilename = "{}{date:%Y%m%d-%H%M%S}.txt".format(exp.log_dir(),
date=datetime.now())
DebugUtils.get_instance().set_logfilename(logfilename)
DebugUtils.get_instance().open_file()
camera = camera_controller.create_camera('camera_front', 'stringf',
exp)
dir_lfw = '/media/denis/dados/face_bds/lfw_face100_min30_max500'
for person_name in os.listdir(dir_lfw):
try:
shutil.copytree(
os.path.join(dir_lfw, person_name),
os.path.join(exp.face_records_dir(), person_name))
except FileExistsError:
pass
for person_name in os.listdir(exp.face_records_dir()):
pfr = pfrdao.create_person_face_records(exp, person_name, camera)
pfrdao.update_object(pfr.person)
fnumber = 0
person = pfr.person
for file in [
f for f in os.listdir(person.person_db_dir())
if os.path.isfile(os.path.join(person.person_db_dir(), f))
]:
fnumber += 1
pfrc.person_add_face_record(person, file)
train = tcc.create_train_configuration(5000, 128)
id_train = train.id
id_exp = exp.id
results = {}
for image_size in reversed(
TrainConfiguration.get_architecture_sizes()):
for relative_size in TrainConfiguration.get_architecture_relative_sizes(
):
# for image_size in ['224']:
# for relative_size in ['0.50']:
tcc.set_image_size(train, int(image_size))
tcc.set_relative_size(train, relative_size)
train_exec = train_test_invoker.invoke_trainer(exp, train)
# Connection is loosy, invoke_trainer reconnects
train = tcc.get_object_by_id(id_train)
exp = ec.get_object_by_id(id_exp)
results['{}_{}'.format(
image_size, relative_size)] = train_exec.test_accuracy
# TODO - accuracy varying
# self.assertGreater(train_exec.test_accuracy, 0.80)
debug.flush_file()
debug.msg('Results:')
configs = results.keys()
for config in sorted(configs):
debug.msg('Test accuracy for {}: {}'.format(
config, '{0:.4f}%%'.format(results[config] * 100)))