def cross_validation(data, K, epoch, class_num, batch_size):
category = len(data)
print(category)
print("=========================")
# if shuffle:
# for c in range(category):
# random.shuffle(data[c])
for i in range(0, K):
print("%d fold" % i)
train_data_path = []
train_label = []
test_data_path = []
test_label = []
for c in range(category):
part_trian_data_path, part_test_data_path = tools.slice_train_test(
data[c], i, K)
for train_len in range(len(part_trian_data_path)):
train_data_path.append(part_trian_data_path[train_len])
train_label.append(c)
for test_len in range(len(part_test_data_path)):
test_data_path.append(part_test_data_path[test_len])
test_label.append(c)
print(len(train_data_path), len(train_label))
print(len(test_data_path), len(test_label))
record = open('records.txt', 'a+')
record.write("%d fold\n" % i)
record.write(str(train_data_path) + '\n')
record.write(str(test_data_path) + '\n')
record.close()
'''
train_data_path = []
train_label = []
test_data_path = []
test_label = []
'''
train_data = []
test_data = []
for train_path in train_data_path:
train_data.append(tools.read_image(train_path, 224, 224, True))
for test_path in test_data_path:
test_data.append(tools.read_image(test_path, 224, 224, True))
Network_config(class_num=class_num,
epoch=epoch,
initial_epoch=0,
batch_size=batch_size,
train_data=train_data,
train_label=train_label,
test_data=test_data,
test_label=test_label,
fold=i)
return
def get_face(fname):
try:
encoding = pickle.loads(
piexif.load(fname)["0th"][piexif.ImageIFD.ImageDescription])
print('Use cached: ' + fname)
return encoding['encoding']
except Exception:
pass
try:
image = tools.read_image(fname, 1000)
except Exception:
print(f'image {fname} reading failed')
return None
boxes = face_recognition.face_locations(image, model='cnn')
if len(boxes) != 1:
print(f'Image contains {len(boxes)} faces')
return None
return encoder.encode(image, boxes)[0][0]
def update(patt, db, num_jitters, encoding_model, max_size, out_size):
encoder = faceencoder.FaceEncoder(encoding_model=encoding_model,
num_jitters=num_jitters,
align=True)
# TODO: add skip encoding loading or something like it
files_faces = list(db.get_all()[1])
encodings, names, filenames = patt.encodings()
for patt_fname, enc in zip(filenames, encodings):
fname, box = get_from_db(files_faces, db, patt_fname)
if fname is None:
log.warning(f'Not found in db: {patt_fname}')
continue
log.debug(f'Found in db file: {fname} {box}')
try:
image = tools.read_image(fname, max_size)
except Exception as ex:
log.warning(f'Cant' 't read image: {fname}: ' + str(ex))
continue
try:
encodings, landmarks = encoder.encode(image, (box, ))
if not tools.test_landmarks(landmarks[0]):
log.warning(f'bad face detected in {patt_fname}')
continue
enc = {
'box': box,
'encoding': encodings[0],
'frame': 0,
'landmarks': landmarks[0]
}
tools.save_face(patt_fname, image, enc, out_size, fname)
log.info(f'Updated: {patt_fname}')
except Exception as ex:
log.exception(f'Failed: {patt_fname}')