def server_seg_blood_vessel(image1, preprocess=True):
from LIBS.ImgPreprocess.my_patches_based_seg import seg_blood_vessel
img_result = seg_blood_vessel(
image1,
dicts_models,
PATCH_H,
PATCH_W,
rop_resized=preprocess,
threshold=127,
min_size=10,
tmp_dir='/tmp',
test_time_image_aug=my_config.blood_vessel_seg_test_time_image_aug)
str_uuid = str(uuid.uuid1())
save_filename = os.path.join(dir_tmp, str_uuid + '.jpg')
os.makedirs(os.path.dirname(save_filename), exist_ok=True)
cv2.imwrite(save_filename, img_result)
return save_filename
os.environ["CUDA_VISIBLE_DEVICES"] = "2"
import cv2
img_file = '/tmp4/img1.png'
img_file = 'rop1.jpg'
img_file = '/media/ubuntu/data2/BloodVesselsSegment_2019_10_22/original/DRIVE/training/images/24_training.tif'
PATCH_H = 64
PATCH_W = 64
import keras
model_file = '/home/ubuntu/dlp/deploy_models/vessel_segmentation/transfer_vessel_seg_patch-012-0.968_0.68_0.81.hdf5'
model1 = keras.models.load_model(model_file, compile=False)
image1 = cv2.imread(img_file)
from LIBS.ImgPreprocess.my_patches_based_seg import seg_blood_vessel
img_result = seg_blood_vessel(image1,
model1,
PATCH_H,
PATCH_W,
threshold=127,
min_size=10,
tmp_dir='/tmp',
test_time_image_aug=True)
cv2.imwrite('a2.png', img_result)
pass
continue
if not extension.upper() in [
'.BMP', '.PNG', '.JPEG', '.JPG', '.TIFF', '.TIF'
]:
continue
if IMAGE_TO_SQUARE:
img_input = image_to_square(image_file)
else:
img_input = image_file
from LIBS.ImgPreprocess.my_patches_based_seg import seg_blood_vessel
img_result = seg_blood_vessel(img_input,
dicts_models,
PATCH_H,
PATCH_W,
rop_resized=True,
threshold=127,
min_size=10,
tmp_dir='/tmp',
test_time_image_aug=True)
image_file_dest = image_file.replace(dir_preprocess, dir_dest)
if not os.path.exists(os.path.dirname(image_file_dest)):
os.makedirs(os.path.dirname(image_file_dest))
print(image_file_dest)
cv2.imwrite(image_file_dest, img_result)
print('ok')
# dir_dest = '/media/ubuntu/data2/STAGE/vessel_seg/'
dir_source = '/media/ubuntu/data2/ROP_vessel_seg/PLUS血管自动分割_20191014/'
dir_dest = '/media/ubuntu/data2/ROP_vessel_seg/PLUS血管自动分割_20191014_my_results/'
for dir_path, subpaths, files in os.walk(dir_source, False):
for f in files:
image_file = os.path.join(dir_path, f)
(filepath, tempfilename) = os.path.split(image_file)
(filename, extension) = os.path.splitext(tempfilename)
if not extension.upper() in [
'.BMP', '.PNG', '.JPEG', '.JPG', '.TIFF', '.TIF'
]:
continue
from LIBS.ImgPreprocess.my_patches_based_seg import seg_blood_vessel
img_result = seg_blood_vessel(image_file,
model1,
PATCH_H,
PATCH_W,
rop_resized=False,
test_time_image_aug=True)
image_file_dest = image_file.replace(dir_source, dir_dest)
os.makedirs(os.path.dirname(image_file_dest), exist_ok=True)
print(image_file_dest)
cv2.imwrite(image_file_dest, img_result)
print('ok')