Lorenzo, We both have got the same case. It seems a solution to this problem would save a lot of people.
Shree, I pulled the current head of master branch but it doesn't seem to contain the merges you pointed that have been merged 3 to 4 days ago. How can I get them? ElMagoElGato 2019年7月19日金曜日 17時02分53秒 UTC+9 Lorenzo Blz: > > > > PSM 7 was a partial solution for my specific case, it improved the > situation but did not solve it. Also I could not use it in some other cases. > > The proper solution is very likely doing more training with more data, > some data augmentation might probably help if data is scarce. > Also doing less training might help is the training is not done correctly. > > There are also similar issues on github: > > https://github.com/tesseract-ocr/tesseract/issues/1465 > ... > > The LSTM engine works like this: it scans the image and for each "pixel > column" does this: > > M M M M N M M M [BLANK] F F F F > > (here i report only the highest probability characters) > > In the example above an M is partially seen as an N, this is normal, and > another step of the algorithm (beam search I think) tries to aggregate back > the correct characters. > > I think cases like this: > > M M M N N N M M > > are what gives the phantom characters. More training should reduce the > source of the problem or a painful analysis of the bounding boxes might fix > some cases. > > > I used the attached script for the boxes. > > > Lorenzo > > > > > Il giorno ven 19 lug 2019 alle ore 07:25 ElGato ElMago < > [email protected] <javascript:>> ha scritto: > >> Hi, >> >> Let's call them phantom characters then. >> >> Was psm 7 the solution for the issue 1778? None of the psm option didn't >> solve my problem though I see different output. >> >> I use tesseract 5.0-alpha mostly but 4.1 showed the same results anyway. >> How did you get bounding box for each character? Alto and lstmbox >> only show bbox for a group of characters. >> >> ElMagoElGato >> >> 2019年7月17日水曜日 18時58分31秒 UTC+9 Lorenzo Blz: >> >>> Phantom characters here for me too: >>> >>> https://github.com/tesseract-ocr/tesseract/issues/1778 >>> >>> Are you using 4.1? Bounding boxes were fixed in 4.1 maybe this was also >>> improved. >>> >>> I wrote some code that uses symbols iterator to discard symbols that are >>> clearly duplicated: too small, overlapping, etc. But it was not easy to >>> make it work decently and it is not 100% reliable with false negatives and >>> positives. I cannot share the code and it is quite ugly anyway. >>> >>> Here there is another MRZ model with training data: >>> >>> https://github.com/DoubangoTelecom/tesseractMRZ >>> >>> >>> >>> >>> Lorenzo >>> >>> >>> Il giorno mer 17 lug 2019 alle ore 11:26 Claudiu <[email protected]> ha >>> scritto: >>> >>>> I’m getting the “phantom character” issue as well using the OCRB that >>>> Shree trained on MRZ lines. For example for a 0 it will sometimes add both >>>> a 0 and an O to the output , thus outputting 45 characters total instead >>>> of >>>> 44. I haven’t looked at the bounding box output yet but I suspect a >>>> phantom >>>> thin character is added somewhere that I can discard .. or maybe two chars >>>> will have the same bounding box. If anyone else has fixed this issue >>>> further up (eg so the output doesn’t contain the phantom characters in the >>>> first place) id be interested. >>>> >>>> On Wed, Jul 17, 2019 at 10:01 AM ElGato ElMago <[email protected]> >>>> wrote: >>>> >>>>> Hi, >>>>> >>>>> I'll go back to more of training later. Before doing so, I'd like to >>>>> investigate results a little bit. The hocr and lstmbox options give some >>>>> details of positions of characters. The results show positions that >>>>> perfectly correspond to letters in the image. But the text output >>>>> contains >>>>> a character that obviously does not exist. >>>>> >>>>> Then I found a config file 'lstmdebug' that generates far more >>>>> information. I hope it explains what happened with each character. I'm >>>>> yet to read the debug output but I'd appreciate it if someone could tell >>>>> me >>>>> how to read it because it's really complex. >>>>> >>>>> Regards, >>>>> ElMagoElGato >>>>> >>>>> 2019年6月14日金曜日 19時58分49秒 UTC+9 shree: >>>>> >>>>>> See https://github.com/Shreeshrii/tessdata_MICR >>>>>> >>>>>> I have uploaded my files there. >>>>>> >>>>>> https://github.com/Shreeshrii/tessdata_MICR/blob/master/MICR.sh >>>>>> is the bash script that runs the training. >>>>>> >>>>>> You can modify as needed. Please note this is for legacy/base >>>>>> tesseract --oem 0. >>>>>> >>>>>> On Fri, Jun 14, 2019 at 1:26 PM ElGato ElMago <[email protected]> >>>>>> wrote: >>>>>> >>>>>>> Thanks a lot, shree. It seems you know everything. >>>>>>> >>>>>>> I tried the MICR0.traineddata and the first two mcr.traineddata. >>>>>>> The last one was blocked by the browser. Each of the traineddata had >>>>>>> mixed >>>>>>> results. All of them are getting symbols fairly good but getting >>>>>>> spaces >>>>>>> randomly and reading some numbers wrong. >>>>>>> >>>>>>> MICR0 seems the best among them. Did you suggest that you'd be able >>>>>>> to update it? It gets tripple D very often where there's only one, and >>>>>>> so >>>>>>> on. >>>>>>> >>>>>>> Also, I tried to fine tune from MICR0 but I found that I need to >>>>>>> change the language-specific.sh. It specifies some parameters for each >>>>>>> language. Do you have any guidance for it? >>>>>>> >>>>>>> 2019年6月14日金曜日 1時48分40秒 UTC+9 shree: >>>>>>>> >>>>>>>> see >>>>>>>> http://www.devscope.net/Content/ocrchecks.aspx >>>>>>>> https://github.com/BigPino67/Tesseract-MICR-OCR >>>>>>>> >>>>>>>> https://groups.google.com/d/msg/tesseract-ocr/obWI4cz8rXg/6l82hEySgOgJ >>>>>>>> >>>>>>>> >>>>>>>> On Mon, Jun 10, 2019 at 11:21 AM ElGato ElMago <[email protected]> >>>>>>>> wrote: >>>>>>>> >>>>>>>>> That'll be nice if there's traineddata out there but I didn't find >>>>>>>>> any. I see free fonts and commercial OCR software but not >>>>>>>>> traineddata. >>>>>>>>> Tessdata repository obviously doesn't have one, either. >>>>>>>>> >>>>>>>>> 2019年6月8日土曜日 1時52分10秒 UTC+9 shree: >>>>>>>>>> >>>>>>>>>> Please also search for existing MICR traineddata files. >>>>>>>>>> >>>>>>>>>> On Thu, Jun 6, 2019 at 1:09 PM ElGato ElMago <[email protected]> >>>>>>>>>> wrote: >>>>>>>>>> >>>>>>>>>>> So I did several tests from scratch. In the last attempt, I >>>>>>>>>>> made a training text with 4,000 lines in the following format, >>>>>>>>>>> >>>>>>>>>>> 110004310510< <02 :4002=0181:801= 0008752 <00039 ;0000001000; >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> and combined it with eng.digits.training_text in which symbols >>>>>>>>>>> are converted to E13B symbols. This makes about 12,000 lines of >>>>>>>>>>> training >>>>>>>>>>> text. It's amazing that this thing generates a good reader out of >>>>>>>>>>> nowhere. But then it is not very good. For example: >>>>>>>>>>> >>>>>>>>>>> <01 :1901=1386:021= 1111001<10001< ;0000090134; >>>>>>>>>>> >>>>>>>>>>> is a result on the image attached. It's close but the last '<' >>>>>>>>>>> in the result text doesn't exist on the image. It's a small >>>>>>>>>>> failure but it >>>>>>>>>>> causes a greater trouble in parsing. >>>>>>>>>>> >>>>>>>>>>> What would you suggest from here to increase accuracy? >>>>>>>>>>> >>>>>>>>>>> - Increase the number of lines in the training text >>>>>>>>>>> - Mix up more variations in the training text >>>>>>>>>>> - Increase the number of iterations >>>>>>>>>>> - Investigate wrong reads one by one >>>>>>>>>>> - Or else? >>>>>>>>>>> >>>>>>>>>>> Also, I referred to engrestrict*.* and could generate similar >>>>>>>>>>> result with the fine-tuning-from-full method. It seems a bit >>>>>>>>>>> faster to get >>>>>>>>>>> to the same level but it also stops at a 'good' level. I can go >>>>>>>>>>> with >>>>>>>>>>> either way if it takes me to the bright future. >>>>>>>>>>> >>>>>>>>>>> Regards, >>>>>>>>>>> ElMagoElGato >>>>>>>>>>> >>>>>>>>>>> 2019年5月30日木曜日 15時56分02秒 UTC+9 ElGato ElMago: >>>>>>>>>>>> >>>>>>>>>>>> Thanks a lot, Shree. I'll look it in. >>>>>>>>>>>> >>>>>>>>>>>> 2019年5月30日木曜日 14時39分52秒 UTC+9 shree: >>>>>>>>>>>>> >>>>>>>>>>>>> See https://github.com/Shreeshrii/tessdata_shreetest >>>>>>>>>>>>> >>>>>>>>>>>>> Look at the files engrestrict*.* and also >>>>>>>>>>>>> https://github.com/Shreeshrii/tessdata_shreetest/blob/master/eng.digits.training_text >>>>>>>>>>>>> >>>>>>>>>>>>> Create training text of about 100 lines and finetune for 400 >>>>>>>>>>>>> lines >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On Thu, May 30, 2019 at 9:38 AM ElGato ElMago < >>>>>>>>>>>>> [email protected]> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>>> I had about 14 lines as attached. How many lines would you >>>>>>>>>>>>>> recommend? >>>>>>>>>>>>>> >>>>>>>>>>>>>> Fine tuning gives much better result but it tends to pick >>>>>>>>>>>>>> other character than in E13B that only has 14 characters, 0 >>>>>>>>>>>>>> through 9 and 4 >>>>>>>>>>>>>> symbols. I thought training from scratch would eliminate such >>>>>>>>>>>>>> confusion. >>>>>>>>>>>>>> >>>>>>>>>>>>>> 2019年5月30日木曜日 10時43分08秒 UTC+9 shree: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> For training from scratch a large training text and hundreds >>>>>>>>>>>>>>> of thousands of iterations are recommended. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> If you are just fine tuning for a font try to follow >>>>>>>>>>>>>>> instructions for training for impact, with your font. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> On Thu, 30 May 2019, 06:05 ElGato ElMago, < >>>>>>>>>>>>>>> [email protected]> wrote: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Thanks, Shree. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Yes, I saw the instruction. The steps I made are as >>>>>>>>>>>>>>>> follows: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Using tesstrain.sh: >>>>>>>>>>>>>>>> src/training/tesstrain.sh --fonts_dir /usr/share/fonts >>>>>>>>>>>>>>>> --lang eng --linedata_only \ >>>>>>>>>>>>>>>> --noextract_font_properties --langdata_dir ../langdata \ >>>>>>>>>>>>>>>> --tessdata_dir ./tessdata \ >>>>>>>>>>>>>>>> --fontlist "E13Bnsd" --output_dir ~/tesstutorial/e13beval >>>>>>>>>>>>>>>> \ >>>>>>>>>>>>>>>> --training_text ../langdata/eng/eng.training_e13b_text >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Training from scratch: >>>>>>>>>>>>>>>> mkdir -p ~/tesstutorial/e13boutput >>>>>>>>>>>>>>>> src/training/lstmtraining --debug_interval 100 \ >>>>>>>>>>>>>>>> --traineddata ~/tesstutorial/e13beval/eng/eng.traineddata >>>>>>>>>>>>>>>> \ >>>>>>>>>>>>>>>> --net_spec '[1,36,0,1 Ct3,3,16 Mp3,3 Lfys48 Lfx96 Lrx96 >>>>>>>>>>>>>>>> Lfx256 O1c111]' \ >>>>>>>>>>>>>>>> --model_output ~/tesstutorial/e13boutput/base >>>>>>>>>>>>>>>> --learning_rate 20e-4 \ >>>>>>>>>>>>>>>> --train_listfile >>>>>>>>>>>>>>>> ~/tesstutorial/e13beval/eng.training_files.txt \ >>>>>>>>>>>>>>>> --eval_listfile >>>>>>>>>>>>>>>> ~/tesstutorial/e13beval/eng.training_files.txt \ >>>>>>>>>>>>>>>> --max_iterations 5000 >>>>>>>>>>>>>>>> &>~/tesstutorial/e13boutput/basetrain.log >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Test with base_checkpoint: >>>>>>>>>>>>>>>> src/training/lstmeval --model >>>>>>>>>>>>>>>> ~/tesstutorial/e13boutput/base_checkpoint \ >>>>>>>>>>>>>>>> --traineddata ~/tesstutorial/e13beval/eng/eng.traineddata >>>>>>>>>>>>>>>> \ >>>>>>>>>>>>>>>> --eval_listfile >>>>>>>>>>>>>>>> ~/tesstutorial/e13beval/eng.training_files.txt >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Combining output files: >>>>>>>>>>>>>>>> src/training/lstmtraining --stop_training \ >>>>>>>>>>>>>>>> --continue_from ~/tesstutorial/e13boutput/base_checkpoint >>>>>>>>>>>>>>>> \ >>>>>>>>>>>>>>>> --traineddata ~/tesstutorial/e13beval/eng/eng.traineddata >>>>>>>>>>>>>>>> \ >>>>>>>>>>>>>>>> --model_output ~/tesstutorial/e13boutput/eng.traineddata >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Test with eng.traineddata: >>>>>>>>>>>>>>>> tesseract e13b.png out --tessdata-dir >>>>>>>>>>>>>>>> /home/koichi/tesstutorial/e13boutput >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> The training from scratch ended as: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> At iteration 561/2500/2500, Mean rms=0.159%, delta=0%, char >>>>>>>>>>>>>>>> train=0%, word train=0%, skip ratio=0%, New best char error = >>>>>>>>>>>>>>>> 0 wrote best >>>>>>>>>>>>>>>> model:/home/koichi/tesstutorial/e13boutput/base0_561.checkpoint >>>>>>>>>>>>>>>> wrote >>>>>>>>>>>>>>>> checkpoint. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> The test with base_checkpoint returns nothing as: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> At iteration 0, stage 0, Eval Char error rate=0, Word error >>>>>>>>>>>>>>>> rate=0 >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> The test with eng.traineddata and e13b.png returns >>>>>>>>>>>>>>>> out.txt. Both files are attached. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Training seems to have worked fine. I don't know how to >>>>>>>>>>>>>>>> translate the test result from base_checkpoint. The generated >>>>>>>>>>>>>>>> eng.traineddata obviously doesn't work well. I suspect the >>>>>>>>>>>>>>>> choice of >>>>>>>>>>>>>>>> --traineddata in combining output files is bad but I have no >>>>>>>>>>>>>>>> clue. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Regards, >>>>>>>>>>>>>>>> ElMagoElGato >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> BTW, I referred to your tess4training in the process. It >>>>>>>>>>>>>>>> helped a lot. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> 2019年5月29日水曜日 19時14分08秒 UTC+9 shree: >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> see >>>>>>>>>>>>>>>>> https://github.com/tesseract-ocr/tesseract/wiki/TrainingTesseract-4.00#combining-the-output-files >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> On Wed, May 29, 2019 at 3:18 PM ElGato ElMago < >>>>>>>>>>>>>>>>> [email protected]> wrote: >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Hi, >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> I wish to make a trained data for E13B font. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> I read the training tutorial and made a base_checkpoint >>>>>>>>>>>>>>>>>> file according to the method in Training From Scratch. Now, >>>>>>>>>>>>>>>>>> how can I make >>>>>>>>>>>>>>>>>> a trained data from the base_checkpoint file? >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> -- >>>>>>>>>>>>>>>>>> You received this message because you are subscribed to >>>>>>>>>>>>>>>>>> the Google Groups "tesseract-ocr" group. >>>>>>>>>>>>>>>>>> To unsubscribe from this group and stop receiving emails >>>>>>>>>>>>>>>>>> from it, send an email to [email protected]. >>>>>>>>>>>>>>>>>> To post to this group, send email to >>>>>>>>>>>>>>>>>> [email protected]. >>>>>>>>>>>>>>>>>> Visit this group at >>>>>>>>>>>>>>>>>> https://groups.google.com/group/tesseract-ocr. >>>>>>>>>>>>>>>>>> To view this discussion on the web visit >>>>>>>>>>>>>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/4848cfa5-ae2b-4be3-a771-686aa0fec702%40googlegroups.com >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/4848cfa5-ae2b-4be3-a771-686aa0fec702%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>>>>>>>>>>>>>> . >>>>>>>>>>>>>>>>>> For more options, visit >>>>>>>>>>>>>>>>>> https://groups.google.com/d/optout. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> -- >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> ____________________________________________________________ >>>>>>>>>>>>>>>>> भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> -- >>>>>>>>>>>>>>>> You received this message because you are subscribed to the >>>>>>>>>>>>>>>> Google Groups "tesseract-ocr" group. >>>>>>>>>>>>>>>> To unsubscribe from this group and stop receiving emails >>>>>>>>>>>>>>>> from it, send an email to [email protected]. >>>>>>>>>>>>>>>> To post to this group, send email to >>>>>>>>>>>>>>>> [email protected]. >>>>>>>>>>>>>>>> Visit this group at >>>>>>>>>>>>>>>> https://groups.google.com/group/tesseract-ocr. >>>>>>>>>>>>>>>> To view this discussion on the web visit >>>>>>>>>>>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/7f29f47e-c6f5-4743-832d-94e7d28ab4e8%40googlegroups.com >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/7f29f47e-c6f5-4743-832d-94e7d28ab4e8%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>>>>>>>>>>>> . >>>>>>>>>>>>>>>> For more options, visit https://groups.google.com/d/optout. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>> -- >>>>>>>>>>>>>> You received this message because you are subscribed to the >>>>>>>>>>>>>> Google Groups "tesseract-ocr" group. >>>>>>>>>>>>>> To unsubscribe from this group and stop receiving emails from >>>>>>>>>>>>>> it, send an email to [email protected]. >>>>>>>>>>>>>> To post to this group, send email to >>>>>>>>>>>>>> [email protected]. >>>>>>>>>>>>>> Visit this group at >>>>>>>>>>>>>> https://groups.google.com/group/tesseract-ocr. >>>>>>>>>>>>>> To view this discussion on the web visit >>>>>>>>>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/2c6fe865-911d-41f3-9926-cbfb56db794f%40googlegroups.com >>>>>>>>>>>>>> >>>>>>>>>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/2c6fe865-911d-41f3-9926-cbfb56db794f%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>>>>>>>>>> . >>>>>>>>>>>>>> For more options, visit https://groups.google.com/d/optout. >>>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> -- >>>>>>>>>>>>> >>>>>>>>>>>>> ____________________________________________________________ >>>>>>>>>>>>> भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com >>>>>>>>>>>>> >>>>>>>>>>>> -- >>>>>>>>>>> You received this message because you are subscribed to the >>>>>>>>>>> Google Groups "tesseract-ocr" group. >>>>>>>>>>> To unsubscribe from this group and stop receiving emails from >>>>>>>>>>> it, send an email to [email protected]. >>>>>>>>>>> To post to this group, send email to [email protected]. >>>>>>>>>>> Visit this group at >>>>>>>>>>> https://groups.google.com/group/tesseract-ocr. >>>>>>>>>>> To view this discussion on the web visit >>>>>>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/5b151e61-5b41-4191-8d26-784809ef8e10%40googlegroups.com >>>>>>>>>>> >>>>>>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/5b151e61-5b41-4191-8d26-784809ef8e10%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>>>>>>> . >>>>>>>>>>> For more options, visit https://groups.google.com/d/optout. >>>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> -- >>>>>>>>>> >>>>>>>>>> ____________________________________________________________ >>>>>>>>>> भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com >>>>>>>>>> >>>>>>>>> -- >>>>>>>>> You received this message because you are subscribed to the Google >>>>>>>>> Groups "tesseract-ocr" group. >>>>>>>>> To unsubscribe from this group and stop receiving emails from it, >>>>>>>>> send an email to [email protected]. >>>>>>>>> To post to this group, send email to [email protected]. >>>>>>>>> Visit this group at https://groups.google.com/group/tesseract-ocr. >>>>>>>>> To view this discussion on the web visit >>>>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/09d3119c-d093-4269-bf3a-3ddb467ed0ed%40googlegroups.com >>>>>>>>> >>>>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/09d3119c-d093-4269-bf3a-3ddb467ed0ed%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>>>>> . >>>>>>>>> For more options, visit https://groups.google.com/d/optout. >>>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> -- >>>>>>>> >>>>>>>> ____________________________________________________________ >>>>>>>> भजन - कीर्तन - 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