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run_sample.py
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import argparse
import os
from misc import pyutils
os.environ['CUDA_VISIBLE_DEVICES']='6'
if __name__ == '__main__':
parser = argparse.ArgumentParser()
# Environment
parser.add_argument("--num_workers", default=os.cpu_count()//2, type=int)
parser.add_argument("--voc12_root", required=True, type=str,
help="Path to VOC 2012 Devkit, must contain ./JPEGImages as subdirectory.")
# Dataset
parser.add_argument("--train_list", default="voc12/train_aug.txt", type=str)
parser.add_argument("--val_list", default="voc12/val.txt", type=str)
parser.add_argument("--test_list", default="voc12/test.txt", type=str)
parser.add_argument("--infer_list", default="voc12/train.txt", type=str,
help="voc12/train_aug.txt to train a fully supervised model, "
"voc12/train.txt or voc12/val.txt to quickly check the quality of the labels.")
parser.add_argument("--chainer_eval_set", default="train", type=str)
# Class Activation Map
parser.add_argument("--cam_network", default="net.resnet50_cam", type=str)
parser.add_argument("--cam_crop_size", default=512, type=int)
parser.add_argument("--cam_batch_size", default=16, type=int)
parser.add_argument("--cam_num_epoches", default=5, type=int)
parser.add_argument("--cam_learning_rate", default=0.1, type=float)
parser.add_argument("--cam_weight_decay", default=1e-4, type=float)
parser.add_argument("--cam_eval_thres", default=0.15, type=float)
parser.add_argument("--cam_scales", default=(1.0, 0.5, 1.5, 2.0),
help="Multi-scale inferences")
# Mining Inter-pixel Relations
parser.add_argument("--conf_fg_thres", default=0.30, type=float)
parser.add_argument("--conf_bg_thres", default=0.05, type=float)
# Inter-pixel Relation Network (IRNet)
parser.add_argument("--irn_network", default="net.resnet50_irn", type=str)
parser.add_argument("--irn_crop_size", default=512, type=int)
parser.add_argument("--irn_batch_size", default=32, type=int)
parser.add_argument("--irn_num_epoches", default=3, type=int)
parser.add_argument("--irn_learning_rate", default=0.1, type=float)
parser.add_argument("--irn_weight_decay", default=1e-4, type=float)
# Random Walk Params
parser.add_argument("--beta", default=10)
parser.add_argument("--exp_times", default=8,
help="Hyper-parameter that controls the number of random walk iterations,"
"The random walk is performed 2^{exp_times}.")
parser.add_argument("--ins_seg_bg_thres", default=0.25)
parser.add_argument("--sem_seg_bg_thres", default=0.25)
# Output Path
parser.add_argument("--log_name", default="sample_train_eval", type=str)
parser.add_argument("--cam_weights_name", default="sess/res50_cam.pth", type=str)
parser.add_argument("--irn_weights_name", default="sess/res50_irn.pth", type=str)
parser.add_argument("--cam_out_dir", default="result/cam", type=str)
parser.add_argument("--ir_label_out_dir", default="result/ir_label", type=str)
parser.add_argument("--sem_seg_out_dir", default="result/sem_seg", type=str)
parser.add_argument("--ins_seg_out_dir", default="result/ins_seg", type=str)
# Step
parser.add_argument("--train_cam_pass", default=True)
parser.add_argument("--make_cam_pass", default=True)
parser.add_argument("--eval_cam_pass", default=True)
parser.add_argument("--cam_to_ir_label_pass", default=True)
parser.add_argument("--train_irn_pass", default=True)
parser.add_argument("--make_ins_seg_pass", default=True)
parser.add_argument("--eval_ins_seg_pass", default=True)
parser.add_argument("--make_sem_seg_pass", default=True)
parser.add_argument("--eval_sem_seg_pass", default=True)
#######################自定义参数######################
parser.add_argument("--cam_weights_aug_name", default="sess/res50_cam_aug.pth", type=str)
parser.add_argument("--irn_weights_aug_name", default="sess/res50_irn_aug.pth", type=str)
parser.add_argument("--cam_out_aug_dir", default="result_aug/cam_aug", type=str)
parser.add_argument("--ir_label_out_aug_dir", default="result_aug/ir_label_aug", type=str)
parser.add_argument("--sem_seg_out_aug_dir", default="result_aug/sem_seg_aug", type=str)
parser.add_argument("--sem_seg_out_fg_dir", default="result/sem_seg_fg", type=str)
#######################自定义参数######################
args = parser.parse_args()
os.makedirs("sess", exist_ok=True)
os.makedirs(args.cam_out_dir, exist_ok=True)
os.makedirs(args.ir_label_out_dir, exist_ok=True)
os.makedirs(args.sem_seg_out_dir, exist_ok=True)
#######################修改代码######################
os.makedirs(args.cam_out_aug_dir, exist_ok=True)
os.makedirs(args.ir_label_out_aug_dir, exist_ok=True)
os.makedirs(args.sem_seg_out_aug_dir, exist_ok=True)
#######################修改代码######################
pyutils.Logger(args.log_name + '.log')
print(vars(args))
if args.train_cam_pass is True:
import step.train_cam
timer = pyutils.Timer('step.train_cam:')
step.train_cam.run(args)
if args.make_cam_pass is True:
import step.make_cam
timer = pyutils.Timer('step.make_cam:')
step.make_cam.run(args)
if args.eval_cam_pass is True:
import step.eval_cam
timer = pyutils.Timer('step.eval_cam:')
step.eval_cam.run(args)
# if args.cam_to_ir_label_pass is True:
# import step.cam_to_ir_label
# timer = pyutils.Timer('step.cam_to_ir_label:')
# step.cam_to_ir_label.run(args)
# if args.train_irn_pass is True:
# import step.train_irn
# timer = pyutils.Timer('step.train_irn:')
# step.train_irn.run(args)
# if args.make_sem_seg_pass is True:
# import step.make_sem_seg_labels
# timer = pyutils.Timer('step.make_sem_seg_labels:')
# step.make_sem_seg_labels.run(args)
# if args.eval_sem_seg_pass is True:
# import step.eval_sem_seg
# timer = pyutils.Timer('step.eval_sem_seg:')
# step.eval_sem_seg.run(args)
# ###########增强部分############
# import step.make_aug_fg
# step.make_aug_fg.run(args)
# import aug_step.train_cam
# aug_step.train_cam.run(args)
# import aug_step.make_cam
# aug_step.make_cam.run(args)
# import aug_step.eval_cam
# aug_step.eval_cam.run(args)
# import aug_step.cam_to_ir_label
# aug_step.cam_to_ir_label.run(args)
# import aug_step.train_irn
# aug_step.train_irn.run(args)
# import aug_step.make_sem_seg_labels
# aug_step.make_sem_seg_labels.run(args)
# import aug_step.eval_sem_seg
# aug_step.eval_sem_seg.run(args)