is it possible for you to upload a subset of your digits?
On Sat, May 24, 2014 at 2:52 AM, klo uo <[email protected]> wrote:
> Hi,
>
> thanks for your reply.
>
> 1. I tested about 100 samples with sklearn. In my example there was only
> one sample because of readability and simplicity.
>
> In short: I read image with opencv, then detect a region of interest and
> extract digits through contouring. These are machine written digits, but
> can have slight perspective distortion. Digits are around 20x25px on 72dpi
> jpeg. So these are far from optimal for OCR, but nonetheless tesseract does
> good job. Main reason for failure are perspective distortion (can be
> de-warped with coding, but I hope not to go there) and discontinuities in
> digit paths that sometimes emerge as I clean the image with morphological
> operators. I have roughly 90% success with tesseract and less then 50% with
> sklearn digits dataset, considering I further degrade image to fit 6x8
> shape which trained sklearn algorithm expects. Errors with sklearn are
> minimal in a sense that I always get result "5" for example while I feed
> predictor with image representing digit "6", and similar. When sklearn
> fails, I get as a result "1" and this is not so common.
>
> 2. No, I just used the code from sklearn documentation without further
> tweaking, as machine learning algorithms and most concepts are foreign to
> me. I mean I know the very basics, but for example I don't know what are
> hyper parameters, and will investigate later today.
>
> 3. Thanks for the link, it looks very promising (even the digits
> dimensions used). I'll follow the example and report back.
>
>
> Regards,
> klo
>
>
>
> On Sat, May 24, 2014 at 5:23 AM, Caleb wrote:
>
>> Hi,
>>
>> I am curious about few things:
>>
>> 1. what are the samples you use for testing your classifier? merely one
>> sample is hard to do justice for its accuracy.
>>
>> 2. did you try to fine tune the hyper parameters for your svm?
>>
>> 3. you might be interested in this blog post, the author get a very
>> impressive result
>> http://peekaboo-vision.blogspot.de/2010/09/mnist-for-ever.html
>>
>> regards,
>> Caleb
>>
>>
>
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