Update: I tried the Google Vision API, and it is actually ridiculously
good. It hit all the targets except two, and that's without a tag
dictionary.

On Tue, Nov 14, 2023 at 8:26 AM Olav Storøy <olavstor...@gmail.com> wrote:

> Interesting! I'd be worried it could remove important text features, but
> maybe tune it to not remove lines shorter than x. I definitely need to look
> at cv2. Until now I've sort of assumed it's best to make Tesseract do as
> much of this process as possible... Thanks for your input
>
> On Mon, Nov 13, 2023 at 8:05 PM Art Rhyno <artrh...@uwindsor.ca> wrote:
>
>> With such clear diagrams, there might be value in having OpenCV remove
>> the horizontal and vertical lines, and then identifying and merging the
>> blobs that are left to get the regions for recognition. I tried this a bit
>> with one of your examples, it would take more refinement but there might be
>> a path to getting good bounding boxes at the image level.
>>
>>
>>
>> art
>>
>>
>>
>> *From:* tesseract-ocr@googlegroups.com <tesseract-ocr@googlegroups.com> *On
>> Behalf Of *Tom Morris
>> *Sent:* Monday, November 13, 2023 11:14 AM
>> *To:* tesseract-ocr <tesseract-ocr@googlegroups.com>
>> *Subject:* Re: [tesseract-ocr] Re: Tesseract on technical drawings
>>
>>
>>
>>
>>
>> On Monday, November 13, 2023 at 5:35:20 AM UTC-5 olavs...@gmail.com
>> wrote:
>>
>>
>>
>> Yeah it seems page segmentation is the crucial issue. If the bounding
>> boxes are good, the recognition is usually very good.
>>
>>
>>
>> I think I've sort of reached the limit on what I can do with base
>> Tesseract. I think the next step would be custom training / fine-tuning.
>>
>>
>>
>> Tesseract's page layout analysis / segmentation isn't training based, so
>> I don't think this is going to help you. If you wanted to recognize the C/L
>> glyph, you could do fine tuning training for it, but it's not going to help
>> you with the problem of finding rotated text and accurately determining
>> bounding boxes for text of interest.
>>
>>
>>
>> It's been ages since I've done serious image processing, but I'd
>> recommend looking at something like OpenCV's text detection:
>>
>> https://docs.opencv.org/4.8.0/d4/d43/tutorial_dnn_text_spotting.html
>>
>>
>>
>> Aspirationally, you can get some idea of what's possible by playing with
>> Google's Cloud Vision API demo
>>
>> https://cloud.google.com/vision/docs/drag-and-drop
>>
>>
>>
>> It lets you just drag & drop an image and then inspect the results both
>> visually and via the JSON that the API produces.
>>
>>
>>
>> Good luck!
>>
>>
>>
>> Tom
>>
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