if I'm right, a neural net is about the engine parts, not the image characterisation rendering method, am I right? because I see many presentations, and most of them talk about the history of tesseract, but that's not what I need
2018-04-27 14:27 GMT+00:00 ShreeDevi Kumar <[email protected]>: > Please see > > https://github.com/tesseract-ocr/tesseract/wiki/4.0-with-LSTM > > For info about neural nets used by tesseract > > On Fri 27 Apr, 2018, 7:48 PM Janpieter Sollie, <[email protected]> > wrote: > >> I had a quick thought about what you could offload to opencl. I will >> need some help from you people (I am a C programmer, not C++, at least not >> experienced) to do the host code, but this algorithm is perfectly >> optimizeable in openCL. >> the way I'd do it: >> >> prerequirements: >> - you can define 65k offsets (x,y) in whose you want the openCL engine to >> look for dots (x,y), the optimal position and closest neighbour can be >> reported in the first part. >> - you can make a RAW image of both the image and the characters. size of >> the letters doesn't matter, but they must be trimmed properly >> >> 1. you give me a matrix of 256*256 offsets(short, short) to analyze, with >> a max of 64 dots (char, char) (I assume these are neurons) to analyze in >> each offset. >> so, this gives you a start memory usage of 2⁸ * 2⁸ *4 + 64*2 = 256k + >> 128 bytes >> each dot MUST contain a black pixel. >> then we add the image, this is a charimage of max (to be discussed with >> you guys), I assume a 4096*4096 pixel image would be fine, especially when >> a character can contain a 4x4 matrix defining a 0/1 (black/white) value. >> 2. Then I follow these steps in the openCL engine: >> - we analyze the neurons >> - draw a cirle around them of x black points. (this circle can be 0, >> in which case the neuron is white), for which the circle is completely >> black >> - when we encounter one or more white points, a direction of the >> points is calculated. if there's no whitespace at the other side, the >> neuron offset is moved for x/2 in the opposite direction and analyze neuron >> is restarted for x/2. else, quit the 'analyze neuron' part. This can be >> done in local memory, in which case it will cost you 256*2=512 bytes of >> local ram to determine the optimal neuron position. Most graphic cards have >> a limit of 32k ram, so this is no problem :-) >> - determine the closest dot next to this one: >> for each dot != this one, draw a line of black points, if no line can >> be found, jump to next dot. >> watch distance. If it's smaller than the previous neuron && this dot >> id hasn't a link pointing from the destination to this one, save dot id. >> so, at the end: >> - each neuron of each offset is optimally centered in a return matrix >> of 256*256*64*2 = 2²³ = 8M of memory >> - each neuron has a unique id to its closest neighbour, to which it's >> guaranteed to be attached. an id of -1 means no id could be found. >> 256*256*64 = 4M of memory >> >> 3. we focus on neuron list -> character mapping. this is a separate >> kernel. A "probability" factor is involved here, but I will think about it >> further. I suggest to use a list of 64 character images at once, otherwise >> you need lots of memory :-) >> - define the top, left and right neuron. create a zoom factor for the >> image. calculate the aspect ratio. The probability is >> 1-diff(aspect_ratio1, aspect_ratio2) >> - analyze each link in the font character. total probability *= >> (found_link_length / total_link_length) >> - report the probability. >> On the PC: the character with the highest probability is the character >> you 're looking for. Be aware that you need to compare the possibilities >> of the different offsets if they overlap. >> >> if the tesseract project can use this, please let me know >> >> 2018-04-27 9:36 GMT+00:00 Zdenko Podobny <[email protected]>: >> >>> Only documentation we have is code itself ;-) But you can start with >>> searching for opencl issue in tesseract issue tracker on github... >>> >>> Zdenko >>> >>> >>> pi 27. 4. 2018 o 10:56 Janpieter Sollie <[email protected]> >>> napísal(a): >>> >>>> I'd be glad to help. using tesseract 4, I am able to perform a 90% >>>> accuracy on OpenCL. I do not have any experience with neural networks (i'm >>>> just a high-school (no college educated IT-support guy with some knowledge >>>> about OpenCL), so can you recommend me some documentation to understand the >>>> engine of tesseract 4? >>>> >>>> 2018-04-27 10:50 GMT+02:00 Zdenko Podobny <[email protected]>: >>>> >>>>> If you have experience your help will be warmly welcomed. >>>>> OpenCL is not maintained and it is on good way to be removed if >>>>> maintainer/contributor will not be found. >>>>> Anyway it is not used extensively, so there is a place for >>>>> improvement, >>>>> >>>>> Zdenko >>>>> >>>>> >>>>> pi 27. 4. 2018 o 10:21 Janpieter Sollie <[email protected]> >>>>> napísal(a): >>>>> >>>>>> Hello everyone, >>>>>> >>>>>> I have a question about the openCL selection procedure of tesseract: >>>>>> >>>>>> my output: >>>>>> >>>>>> [DS] Profile read from file (tesseract_opencl_profile_devices.dat). >>>>>> [DS] Device[1] 1:Fiji score is 0.202927 >>>>>> [DS] Device[2] 1:Ellesmere score is 1.468799 >>>>>> [DS] Device[3] 1:Ellesmere score is 1.468799 >>>>>> [DS] Device[4] 1:Bonaire score is 1.533776 >>>>>> [DS] Device[5] 1:Tonga score is 0.184236 >>>>>> [DS] Device[6] 0:(null) score is 1.123015 >>>>>> [DS] Selected Device[5]: "Tonga" (OpenCL) >>>>>> >>>>>> Ugh, this is weird .. why does tesseract take my Tonga instead of my >>>>>> fiji device? can I force it to use the fiji? >>>>>> I understand the ellesmere have lower access times (they 're behind a >>>>>> pcie switch), but fiji and tonga are both directly connected via a pcie >>>>>> 2.0 >>>>>> X16 bus. Do we need a better tesseract selection procedure? >>>>>> If so, I'm quite skilled at opencl, I'd be glad to help! >>>>>> >>>>>> kind regards, >>>>>> >>>>>> Janpieter >>>>>> >>>>>> -- >>>>>> 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/4568b2b8-532d-457c-920b-60407e7b278e% >>>>>> 40googlegroups.com >>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/4568b2b8-532d-457c-920b-60407e7b278e%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>> . >>>>>> For more options, visit https://groups.google.com/d/optout. >>>>>> >>>>> -- >>>>> You received this message because you 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