Open kbrajwani opened 3 years ago
Can you provide the test image to us? We can use it to analyze the issue. Btw, to solve this problem, the best solution may be: train a new model on your dataset instead of use the one trained on icdar2017, since most annotated boxes in icdar2017 is word instead of sentance.
Hey i will try to train model. I want to finetune the model psenet_r50_fpnf_600e_icdar2017 on 200 images. what you think it's sufficient data for finetune?
I have done data preparation https://mmocr.readthedocs.io/en/latest/datasets.html according to this.
Then I am running
./tools/dist_train.sh configs/textdet/psenet/psenet_r50_fpnf_600e_icdar2017.py /content/psenet 1
This command but I think it will start training from scratch rather than finetuning. Can you tell me where i can give the model path to start finetuning?
Here is the sample of my data.
load_from = "/path/to/pretrained_checkpoint.pth"
to the config file psenet_r50_fpnf_600e_icdar2017.py
to load pretrained model.Hi @cuhk-hbsun can you tell me that psenet_r50_fpnf_600e_icdar2017 is trained on synthtext or not? Currently i know that first it's trined on icdar2017 then icdar2015 so it's trained in synthtext also? I am asking because i have trained it on my images but it's not performing well as i have created annotation from google document ocr which divides the words like date 21/10/1997 will be returning as [21, / , 10 , / , 1997] . so i can't show the correct annotation to the psenet training. Thanks
Please check out the model zoo page. Each model has its training configs.
https://mmocr.readthedocs.io/en/latest/textdet_models.html#psenet Yes i have checked this page but it didn't show the synthtext dataset that's the reason I have asked.
The page should contain the full reproducible information. If not, then we will fix it.
Hi, i have done the training on my images. I am getting number now but i have one problem of not detecting single or two character word or a small word in images. Can you guide me which parameter i can change to achieve the small text in image. Thanks
One more issue in robust_scanner model it will misclassify / as 1 also if number have .000 then . will classify as C and result we get c000 . Can you tell me how can i make this correct also.
First thing to try is to check the data. Make sure there are sufficiently large number of high quality training samples for the bad cases
Hey can you tell me how to convert synthtext dataset for text detection? it is given here https://github.com/open-mmlab/mmocr/blob/main/docs/datasets.md but steps are missing to convert. So how can i trained the psenet on synthtext ?
@innerlee can you please guide me about synthtext training for text detection part and which config i can use for psenet to train on synthtext.
@cuhk-hbsun
@cuhk-hbsun
Hey can you tell me how to convert synthtext dataset for text detection? it is given here https://github.com/open-mmlab/mmocr/blob/main/docs/datasets.md but steps are missing to convert. So how can i trained the psenet on synthtext ?
can you please guide me about synthtext training for text detection part and which config i can use for psenet to train on synthtext.
Hi,
Single character numbers are not detecting properly in 'psenet_r50_fpnf_600e_icdar2017.pth' unable to extract the numeric values, attached the sample image for your reference. Thanks in advance.
Psenet is working great in the alphabets but if we consider the float numbers then it will separate numbers by comma (,) or decimal sign( . ) . Like 1,000,00.00 it will be detect line [ "1" , ",000" , ",00" , "00" ] So it will miss decimal sign or comma sometime. Also it will miss the 1 in 1,000,00.00 so we will only get ,000,00.00 . Can you tell me how can we resolve this issue?