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ds...@google.com
ds...@google.com
Hi there,
I am unable to retrieve and test your image as the bucket you provided does not seem to be available anymore. Would it be possible for you to share the original image(twoc.png) that you’ve used in the Cloud Vision API Explorer?
Alternatively, it would be important to verify if any of the best practices would apply to your image. For example, when using TEXT_DETECTION the OCR of Cloud Vision API requires more resolution to detect characters and therefore, a minimum image size of 1024 x 768 pixels is advised.
I am unable to retrieve and test your image as the bucket you provided does not seem to be available anymore. Would it be possible for you to share the original image(twoc.png) that you’ve used in the Cloud Vision API Explorer?
Alternatively, it would be important to verify if any of the best practices would apply to your image. For example, when using TEXT_DETECTION the OCR of Cloud Vision API requires more resolution to detect characters and therefore, a minimum image size of 1024 x 768 pixels is advised.
ru...@gmail.com
i attached example image file.
when i use other language in "Language Hints" like Arabic,English it show bad output.line will be break wrong.
but when i use Google doc , that will show correct output.i think Google doc use other mechanism of OCR or any preprocessing (ex:change size,layer recognition,stronger language analyzer or even any image processing and etc).
may be when you test this image it show good output but in other image (Asian language like Arabic) file it has bad output and user should edit text file.
how can i get output like Google doc with Google cloud text_detection.
when i use other language in "Language Hints" like Arabic,English it show bad output.line will be break wrong.
but when i use Google doc , that will show correct output.i think Google doc use other mechanism of OCR or any preprocessing (ex:change size,layer recognition,stronger language analyzer or even any image processing and etc).
may be when you test this image it show good output but in other image (Asian language like Arabic) file it has bad output and user should edit text file.
how can i get output like Google doc with Google cloud text_detection.
Description
Brown 98%
Pollinator 96%
Insect 95%
Arthropod 93%
Butterfly 92%
useless generic labels, It had same issues when I have tried it 10 years ago, sad in 2024 to not see any noticeable improvement
If I try same picture with your own lens app search I get Schrankia that is correct.
Why? Does Google use a different and more outdated and lackluster model for cloud API compared to what is currently in use in its app or I'm missing something?