Stopping and starting is not good idea. I have been advised to train step by step manner: slowly increasing the iterations. Turns out, that makes Tesseract never train the last lines of texts.
https://github.com/tesseract-ocr/tesseract/issues/3954 So, the best approach is to run the training for a higher number of iterations in one round. On Sunday, October 29, 2023 at 3:18:32 PM UTC+3 Des Bw wrote: > > *BCER is a lie: * > > (B)CER is unrealistic measure of accuracy. I*t is a lie. * I have said it > a couple of times already. The BCER we get during the training is nowhere > close to the reality of the accuracy of our model. I have many occasions > where my training achieved 0 error rate and stopped the training. But, when > I tested the output using independent evaluation tools, the best I can get > was 95-97% accuracy on the synthetic data and 90-92% accuracy on actual > scanned documents (data). > - So, we need to find a way to turn off the target_error-rate parameter > which stops the training when the model thinks it achieved 0% error. May be > can assign a negative value to it. I am going to try it if it will turn it > off. > On Tuesday, October 24, 2023 at 3:55:54 PM UTC+3 Des Bw wrote: > >> You can add *training >> data/lang.log &* to the end of your training >> script (shell) to get a log saved inside your data folder. You also add >> *DEBUG_INTERVAL=-1 >> training >> data/lang.log &. *This one flashes more detailed information >> on the console; and saves a short log inside the data folder. If you want >> to save everything displayed in the console saved to log file, you can >> check out methods listed here: >> >> https://unix.stackexchange.com/questions/200637/save-all-the-terminal-output-to-a-file >> >> >> On Tuesday, October 24, 2023 at 3:45:23 PM UTC+3 [email protected] >> wrote: >> >>> I have made a first try for a fine tuning, the script run a second and >>> end without any error message. Where can I find a log file ? >>> >>> Le lun. 23 oct. 2023 à 14:01, Keith Smith <[email protected]> a >>> écrit : >>> >>>> Rene, the name “foo” is simply an example (or fictitious) font or >>>> language name. When training a new language or font, you should replace >>>> “foo” with the name of your language or font. The standard is to choose 3 >>>> letters, but that is not required. In fact, I have been training a font >>>> named “micr_e13b” and it is working technically for me (though the >>>> accuracy >>>> isn’t good enough yet). Note the underscore character between sections of >>>> the name. >>>> >>>> >>>> >>>> Internal >>>> >>>> *From: *[email protected] <[email protected]> on >>>> behalf of René JM Clais <[email protected]> >>>> *Date: *Sunday, October 22, 2023 at 12:41 PM >>>> *To: *[email protected] <[email protected]> >>>> *Subject: *[EXTERNAL] Re: [tesseract-ocr] Lessons, best practices, >>>> recommendations, strategies, hacks >>>> >>>> *CAUTION EXTERNAL EMAIL * >>>> *DO NOT open attachments or click on links from unknown senders or >>>> unexpected emails.* >>>> >>>> >>>> >>>> Hi Keith, >>>> >>>> The foo.traindedata is not existing but do you mean : the trainedata I >>>> want to train ex: hye.traineddata ? >>>> >>>> In my case I should add a new character in the hye.traineddata >>>> >>>> It seems that I can do this using the option 2 ! >>>> >>>> But how ? Which command should I use to execute this function and >>>> what does mean this process ? >>>> >>>> >>>> >>>> Thank you for your help >>>> >>>> Regards >>>> >>>> René >>>> >>>> >>>> >>>> Le sam. 21 oct. 2023 à 17:18, Keith Smith <[email protected]> a >>>> écrit : >>>> >>>> Thank you Des for your help in this community. It is greatly >>>> appreciated! >>>> >>>> As one who is struggling, may I make a suggestion. >>>> >>>> I have started a google doc here >>>> <https://urldefense.com/v3/__https://docs.google.com/document/d/1Vz6y4LcqczAAE2yKc_xYecy1eChjHZbsxb13_7ntUh0/edit?usp=sharing__;!!MjXRb4uW6x5k!HFOAD-quUbb2dHADKsKiyk_BK3xW49ZAh87HZ3mPU9myi2Zk2t-bdP3ptvhcsV64KhX43EgYbPFZJ5M8Lr1zVHA$> >>>> >>>> with a suggested format for a tutorial which would be very helpful to me >>>> and I think to others. It is editable by anyone with the link. >>>> >>>> I'm glad to put in any work myself, but my guess is that there are >>>> things in the doc that could be filled without much effort by you or >>>> others. >>>> >>>> If this is true, once the doc is filled out, the contents of the google >>>> doc could be submitted as a PR to the tesstrain repo. >>>> >>>> Again, just a suggestion that I hope would be helpful to all. >>>> >>>> >>>> >>>> Thanks, >>>> >>>> Keith >>>> >>>> >>>> >>>> On Sat, Oct 21, 2023 at 8:28 AM Des Bw <[email protected]> wrote: >>>> >>>> There is no exhaustive user manual for training tesseract. We all start >>>> in the darkness; and accumulate bits of information in different places to >>>> learn the ins and outs of tesseract. >>>> >>>> >>>> >>>> It would be great if we can collectively write a better manual. Up >>>> until then, we can drop /collect our observations, best practices, hacks >>>> and lessons we accumulated in our adventure with tesseract. >>>> >>>> >>>> >>>> I will start with some of my observations. I collect them by reading in >>>> between the lines: from my own failed experiments: >>>> >>>> 1. Training from scratch is very difficult because tesseract requires >>>> extensive data set. It looks like it requires over 300,000 test lines >>>> (around 26mb text file). >>>> >>>> https://github.com/tesseract-ocr/tesseract/issues/3909 >>>> <https://urldefense.com/v3/__https://github.com/tesseract-ocr/tesseract/issues/3909__;!!MjXRb4uW6x5k!HFOAD-quUbb2dHADKsKiyk_BK3xW49ZAh87HZ3mPU9myi2Zk2t-bdP3ptvhcsV64KhX43EgYbPFZJ5M8Yk4Xcmo$> >>>> >>>> >>>> >>>> Multiple that with the fonts you want to train, the data grows >>>> exponentially. That requires very powerful computers running for weeks and >>>> months. >>>> >>>> So, for the regular users, training from a network layer, or fine >>>> tuning are the most plausible options. >>>> >>>> >>>> >>>> 2. Best practice: make your text lines not too long. The recommended >>>> number of works in a line is 10-12. 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