checkpoint = os.path.join(checkpoint, checkpoint)
outs = model.test8(N_ITER_MAX, checkpoint, p1)
outs = [LOG] + list(outs) + [p1, 0.5]
NAMES = ["ID", "Loss", "Acc", "F1", "Recall", "Precision", "ROC", "Jaccard", "AJI", "p1", "p2"]
f.write('{},{},{},{},{},{},{},{},{},{},{}\n'.format(*NAMES))
f.write('{},{},{},{},{},{},{},{},{},{},{}\n'.format(*outs))
elif SPLIT == "validation":
TEST_PATIENT = ["testbreast", "testliver", "testkidney", "testprostate",
"bladder", "colorectal", "stomach"]
file_name = options.output
f = open(file_name, 'w')
NAMES = ["NUMBER", "ORGAN", "Loss", "Acc", "ROC", "Jaccard", "Recall", "Precision", "F1", "AJI", "p1", "p2"]
f.write('{},{},{},{},{},{},{},{},{},{},{}\n'.format(*NAMES))
transform_list, transform_list_test = ListTransform()
PATH = options.path
for organ in TEST_PATIENT:
DG_TEST = DataGenMulti(PATH, split="test", crop = 1, size=(1000, 1000),num=[organ],
transforms=transform_list_test, UNet=False, mean_file=None)
save_organ = os.path.join(options.save_path, organ)
CheckOrCreate(save_organ)
outs = model.validation(DG_TEST, 2, options.p1, 0.5, save_organ)
for i in range(len(outs)):
small_o = outs[i]
small_o = [i, organ] + small_o + [options.p1, 0.5]
f.write('{},{},{},{},{},{},{},{},{},{},{}\n'.format(*small_o))
f.close()
parser.add_option("--test", dest="test", type="int")
parser.add_option("--mu", dest="mu", type="int")
parser.add_option("--sigma", dest="sigma", type="int")
parser.add_option("--sigma2", dest="sigma2", type="int")
parser.add_option("--normalized", dest='normalized', type='int')
(options, args) = parser.parse_args()
if (options.normalized != 0 and options.normalized != 1):
raise AssertionError(
'normalized not define, give --normalized 0 or --normalized 1')
path = "/data/users/pnaylor/Bureau/ToAnnotate"
path = "/Users/naylorpeter/Documents/Histopathologie/ToAnnotate/ToAnnotate"
path = options.path
transf, transf_test = ListTransform()
size = (512, 512)
crop = 1
DG = DataGenMulti(path,
crop=crop,
size=size,
transforms=transf_test,
split="train",
num="",
seed_=42)
Slide_train = join(options.output, "Slide_train")
CheckOrCreate(Slide_train)
Gt_train = join(options.output, "GT_train")
CheckOrCreate(Gt_train)
OUTNAME = options.TFRecord
PATH = options.path
CROP = options.crop
SIZE = options.size_train
SPLIT = options.split
var_elast = [1.3, 0.03, 0.15]
var_he = [0.01, 0.2]
var_hsv = [0.2, 0.15]
UNET = options.UNet
SEED = options.seed
N_EPOCH = options.epoch
TYPE = options.type
transform_list, transform_list_test = ListTransform(var_elast=var_elast,
var_hsv=var_hsv,
var_he=var_he)
if options.split == "train":
TEST_PATIENT = [
"testbreast", "testliver", "testkidney", "testprostate", "bladder",
"colorectal", "stomach", "test"
]
TRANSFORM_LIST = transform_list
elif options.split == "test":
TEST_PATIENT = ["test"]
TRANSFORM_LIST = transform_list_test
SIZE = options.size_test
elif options.split == "validation":
options.split = "test"
TEST_PATIENT = [
LRSTEP = "4epoch"
SUMMARY = True
S = SUMMARY
N_EPOCH = options.epoch
PATH = options.path
HEIGHT = 212
WIDTH = 212
SIZE = (HEIGHT, WIDTH)
N_TRAIN_SAVE = 10
CROP = 4
transform_list, transform_list_test = ListTransform(n_elastic=0)
DG_TRAIN = DataGenMulti(PATH,
split='train',
crop=CROP,
size=(HEIGHT, WIDTH),
transforms=transform_list,
num="test",
UNet=True,
mean_file=None)
test_patient = ["test"]
DG_TRAIN.SetPatient(test_patient)
N_ITER_MAX = N_EPOCH * DG_TRAIN.length // BATCH_SIZE
DG_TEST = DataGenMulti(PATH,