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adding options to select the model and folder #154

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adding options to select the model and folder #154

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17 changes: 13 additions & 4 deletions u2net_train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,16 @@
from model import U2NET
from model import U2NETP

import argparse

parser = argparse.ArgumentParser(description='Bot trainer')

parser.add_argument('--input_images', help='path to the image folder')
parser.add_argument('--input_masks', help='path to the masks folder')
parser.add_argument('--model_name', help='can either be u2net or u2netp')

args = parser.parse_args()

# ------- 1. define loss function --------

bce_loss = nn.BCELoss(size_average=True)
Expand All @@ -46,11 +56,11 @@ def muti_bce_loss_fusion(d0, d1, d2, d3, d4, d5, d6, labels_v):

# ------- 2. set the directory of training dataset --------

model_name = 'u2net' #'u2netp'
model_name = args.model_name

data_dir = os.path.join(os.getcwd(), 'train_data' + os.sep)
tra_image_dir = os.path.join('DUTS', 'DUTS-TR', 'DUTS-TR', 'im_aug' + os.sep)
tra_label_dir = os.path.join('DUTS', 'DUTS-TR', 'DUTS-TR', 'gt_aug' + os.sep)
tra_image_dir = args.input_images
tra_label_dir = args.input_masks

image_ext = '.jpg'
label_ext = '.png'
Expand Down Expand Up @@ -161,4 +171,3 @@ def muti_bce_loss_fusion(d0, d1, d2, d3, d4, d5, d6, labels_v):
running_tar_loss = 0.0
net.train() # resume train
ite_num4val = 0