CODEWITHSUNDEEP
pythonimagetensorflowopencvcolors
Ignacio Mtz De Salinas Ureta
Ignacio Mtz De Salinas Ureta

Reputation: 35

Get black region from image using Tensorflow and Python

I'm trying to get the black region from an image using TensorFlow. To this point I was using OpenCV but it fails to get the hole region given that the gray scale is very complicated.

The image I'm using is a photo of a electric meter, the whole meter is white(normally) except for the part with the numbers that is black. I would want to isolate this part in order to get the numbers later on.

To de the date, I have been using the function findContours from OpenCV, with a defined threshold .

I have seen that TensorFlow is very potent so I think this could no be a problem, but I can't find any documentation. Any hints? Thanks!

Upvotes: 0

Views: 278

Answers (1)

David Parks
David Parks

Reputation: 32111

Tensorflow is a general purpose math library that is unique in two respects:

  1. It provides automatic differentiation.
  2. It has efficient kernels built to run on either the CPU or GPU.

It does have a library of image functions, but it's nowhere near as extensive as OpenCV, and will never be. Those are mostly for data augmentation (as it pertains to ML) and data loading.

Note that you can run OpenCV code on the GPU in many cases (I'm not sure about findContours in particular. So sticking with OpenCV should be considered.

But within tensorflow you would have to re-write that function yourself. In looking at the code (which I provided a link to in your question) it doesn't look very hard to do. You could replicate that in symbolic tensorflow operations in relatively short order, but nothing like that exists pre-built in tensorflow. Nor is it likely to in the future.

Upvotes: 1

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