from LIBS.DLP.my_predict_helper import do_predict
DO_PREPROCESS = False
GEN_CSV = True
COMPUTE_DIR_FILES = True
dir_original = '/media/ubuntu/data1/screen/original'
dir_preprocess = '/media/ubuntu/data1/screen/preprocess384/'
dir_dest = '/media/ubuntu/data1/ROP项目/screen/results/LaserSpot'
pkl_prob = os.path.join(dir_dest, 'probs.pkl')
from LIBS.ImgPreprocess import my_preprocess_dir
if DO_PREPROCESS:
my_preprocess_dir.do_preprocess_dir(dir_original,
dir_preprocess,
image_size=384,
is_rop=False,
add_black_pixel_ratio=0.07)
dicts_models = []
model_dir = '/tmp5/models_2020_6_19/DR_english/v1'
dict_model1 = {
'model_file': os.path.join(model_dir, 'InceptionV3-004-0.982.hdf5'),
'input_shape': (299, 299, 3),
'model_weight': 1
}
dicts_models.append(dict_model1)
dict_model1 = {
'model_file': os.path.join(model_dir, 'InceptionResnetV2-004-0.984.hdf5'),
'input_shape': (299, 299, 3),
'model_weight': 1
from LIBS.Generator import my_images_generator_2d
from LIBS.Neural_Networks.Heatmaps.CAM import my_helper_cam, my_helper_grad_cam, my_helper_grad_cam_plusplus
from tensorflow import keras
DO_PREPROCESS = False
GEN_CSV = True
DIR_ORIGINAL = '/media/ubuntu/data1/糖网项目/DR分级英国标准_20190119_无杂病/DR/original'
DIR_PREPROCESS = '/media/ubuntu/data1/糖网项目/DR分级英国标准_20190119_无杂病/DR/preprocess384/'
DIR_DEST = '/media/ubuntu/data1/糖网项目/DR分级英国标准_20190119_无杂病/DR/results/CAM/'
from LIBS.ImgPreprocess import my_preprocess_dir
if DO_PREPROCESS:
my_preprocess_dir.do_preprocess_dir(DIR_ORIGINAL,
DIR_PREPROCESS,
image_size=384,
is_rop=False,
add_black_pixel_ratio=0.07)
filename_csv = os.path.join(DIR_DEST, 'csv', 'predict_dir.csv')
if GEN_CSV:
os.makedirs(os.path.dirname(filename_csv), exist_ok=True)
from LIBS.DataPreprocess.my_data import write_csv_dir_nolabel
write_csv_dir_nolabel(filename_csv, DIR_PREPROCESS)
#region load and convert models
model_dir = '/tmp5/models_2020_6_19/DR_english/v1'
dicts_models = []
dict_model1 = {
'model_file': os.path.join(model_dir, 'InceptionResnetV2-004-0.984.hdf5'),
