Hi, I like your project and I trained it for ICDAR2017, but I met a problem.

reading file error: data\ICDAR17MLT\gts\gt_ICDAR17MLT_img_199.txt ثوار substring not found

ICDAR2017 DATA contains multi languages, such as Arabic, Korean. I know maybe I should modify the config.py, but I‘m not clear about how to do it. Could you please give me any suggestion? Thanks a lot.

Hi, why did you choose to set lambda to 1 when calculating the total loss? I know that in the FOTS paper they set lambda to 1, but in other FOTS repos the value is often 0,01. Do you know in which interval the values of the recognition loss and the detection loss are?

When I try to restore training using the previous checkpoint, I get the following error:

continue training from previous checkpoint ERROR:tensorflow:Couldn't match files for checkpoint [my checkpoint path]/model.ckpt-20041 E1126 14:28:09.314913 139785224988480 checkpoint_management.py:346] Couldn't match files for checkpoint [my checkpoint path]/model.ckpt-20041 ... File "train.py", line 216, in main saver.restore(sess, ckpt) File "[python path]/lib/python3.7/site-packages/tensorflow_core/python/training/saver.py", line 1277, in restore raise ValueError("Can't load save_path when it is None.") ValueError: Can't load save_path when it is None.

How can I fix it? If I check the checkpoint after training is complete, only checkpoint, events.out.tfevents.1606212446, model.ckpt-20041.data-00000-of-00001 , model.ckpt-20041.index and model.ckpt-20041.meta are created. Even if an absolute path is used for the first training, multiple checkpoints are created and are not restored.

Or am I misusing the following? python train.py --gpu_list='0' --checkpoint_path=[check point path (absolute path)]/ --training_img_data_dir=[images path]/ --training_gt_data_dir=[gts path]/ (I set FLAG.Restore to True in train.py)

1. We are applying an additional Korean language when studying on config.py in order to do Korean ocr. Does fosts support multi-language features?

2. Even though we completed the recognition test through the github readme, there seems to be a problem in detection, but we don’t know that is the cause of the error.

My error is

2020-11-15 22:28:43.704077: W tensorflow/core/framework/op_kernel.cc:1651] OP_REQUIRES failed at ctc_loss_op.cc:168 : Invalid argument: Labels length is zero in batch 25 Traceback (most recent call last): File "/home/nplab6/anaconda3/envs/tf115-cu100/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call return fn(*args) File "/home/nplab6/anaconda3/envs/tf115-cu100/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn target_list, run_metadata) File "/home/nplab6/anaconda3/envs/tf115-cu100/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun run_metadata) tensorflow.python.framework.errors_impl.InvalidArgumentError: 2 root error(s) found. (0) Invalid argument: Labels length is zero in batch 25 [[{{node CTCLoss}}]] (1) Invalid argument: Labels length is zero in batch 25 [[{{node CTCLoss}}]] [[gradients/Mean_3_grad/Shape/_595]] 0 successful operations. 0 derived errors ignored.

Error("CTC Loss label length is zero with ICDAR 2013") occurs when using ICDAR2013.

ICDAR 2013 text label content for recognition training is 72,271,382,312,"Greenstead" (four digits).

but ICDAR 2015 and 2017 label content is eight digits.

Why is it different from ICDAR2013 and ICDAR015/2017?

using your pretrained model, restore the weights, errorKey Conv/biases/ExponentialMovingAverage not found in checkpoint [[node save/RestoreV2 which version tensorflow are you using?