Hi,
I have been trying to work on detecting words in images of invoices.
Word detection is working for images with smaller dimensions. But it is not detecting higher dimension images.
I read in 354 and 274 that if the images is cropped into smaller pieces it is working fine. But i want to detect word on an whole image.
If training needs to be done with more images, what would be the ideal number to chose and in what basis should the training be, to get a good results with detection.
I observed the output for images in different ranges of dimensions and i found out that images with resolution around 500pixels, detections are good. as the resolution increases detection goes wrong.
Attaching the images below, might be useful
907x791 pixels389x339 pixels
Here we can see the detections are better for second image. To improve detections for all dimension, will it be a good start with 10000 images?
Hi, I have been trying to work on detecting words in images of invoices. Word detection is working for images with smaller dimensions. But it is not detecting higher dimension images. I read in 354 and 274 that if the images is cropped into smaller pieces it is working fine. But i want to detect word on an whole image. If training needs to be done with more images, what would be the ideal number to chose and in what basis should the training be, to get a good results with detection.