It's a great job.Before your update, I tried to train PAN, but the loss was still high until the end of the training.Does the current version support effective training and inference?

谢谢大佬的分享，有一些疑问就是，在predict测试的时候，（model用resnet18的，mac os上测试）提示以下错误，不知能否给些意见？ 0.0, best wishes!

pse.cpp:49:29: error: variable-sized object may not be initialized
        float kernel_vector[label_num][5] = {0};
                            ^~~~~~~~~
1 error generated.
make: *** [pse.so] Error 1
Traceback (most recent call last):
  File "/Users/abelleon/Documents/project/PAN.pytorch-master/predict.py", line 13, in <module>
    from post_processing import decode
  File "/Users/abelleon/Documents/project/PAN.pytorch-master/post_processing/__init__.py", line 17, in <module>
    raise RuntimeError('Cannot compile pse: {}'.format(BASE_DIR))
RuntimeError: Cannot compile pse: /Users/abelleon/Documents/project/PAN.pytorch-master/post_processing

/utils/cal_recall/rrc_evaluation_funcs.py", line 102, in load_folder_file raise Exception('ZIP entry not valid: %s' % name) Exception: ZIP entry not valid: res_100104531.txt

验证和eval的时候都报这个错，请问这个是什么意思，我应该怎么解决呢？

when i run predict.py

[shakey@xiaoi-778 PAN]$ python predict.py make: Entering directory /opt/shakey/deep-learning/PAN/post_processing' make:pse.so' is up to date. make: Leaving directory `/opt/shakey/deep-learning/PAN/post_processing' self。gpu 1 ininstance True torch.cuda.is True self。gpu 1 ininstance True torch.cuda.is True device: cuda:0 Segmentation fault (core dumped)

@WenmuZhou Thank you for your hard work,

It would be great if you would add:

• Script to detect/ inference on multiple images.
• The option to export the detected boxes, perhaps .txt containing x1,y1,x2,y2,x3,y3,x4,y4

@WenmuZhou Thank you for your hard work,

I am trying to train icdar2015, when running train.py I get error. My config.json My training & testing list, and file tree.

The error message:

(final) home@home-desktop:~/p2/PAN.pytorch-master$ python train.py
Traceback (most recent call last):
  File "train.py", line 33, in <module>
    main(config)
  File "train.py", line 18, in main
    train_loader, eval_loader = get_dataloader(config['data_loader']['type'], config['data_loader']['args'])
  File "/home/home/p2/PAN.pytorch-master/data_loader/__init__.py", line 98, in get_dataloader
    num_workers=module_args['loader']['num_workers'])
  File "/home/home/anaconda3/envs/final/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 213, in __init__
    sampler = RandomSampler(dataset)
  File "/home/home/anaconda3/envs/final/lib/python3.6/site-packages/torch/utils/data/sampler.py", line 94, in __init__
    "value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0

您好，在您的FPEM模块的实现中,有self.add_up和self.add_down， 这两块应该相当于是将不同大小的feature map进行up-sample和down-sample并相加后再进行feature map的融合，而这个融合模块实例应该是每次融合都不一样，而不是每次融合都是同一个模块实例，比如在Up-scale Enhancement中c5和c4down-sample相加后的add_up与c4和c3down-sample相加后的add_up实例应该是不同的两个模块实例，虽然两个add_up结构相同，但是其参数并不能共享，论文中好像也没有强调这些参数是共享的，所以我的理解是每个add_up部分应该创建不同的nn.sequential，down-sample同理。不知道我说的对不对。。。还是说我的理解有偏差 唉，语死早，感觉很难说清楚我要表达的意思

There is a parameter "finetune_checkpoint", I want to know how does it work here, and does it freeze any initial layers, if yes then how one can control it?

File "/Users/liubowen/Downloads/PAN.pytorch-master/post_processing/init.py", line 17, in raise RuntimeError('Cannot compile pse: {}'.format(BASE_DIR)) RuntimeError: Cannot compile pse: /Users/liubowen/Downloads/PAN.pytorch-master/post_processing

有没有解决方案？please！！