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How do I deploy custom Image Processing algorithms in an android app?

By : Muratcan Ünsal
Date : September 14 2020, 07:00 PM
this one helps. You can deploy any Tensorflow, Keras and pytorch model on android devices using Tensorflow-lite. If you want to deploy your model for real time image/video processing then you should to go with Mediapipe. Mediapipe is google framework build on the top of tensorflow-lite. Mediapipe performance is fast as compare to normal tflite deployment because it uses Input/Output SSBO, It is cross platforms as well.
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Is it possible to use TDD with image processing algorithms?

By : shahesam84
Date : March 29 2020, 07:55 AM
wish help you to fix your issue The image processing tests that you describe in your question take place at a much higher level than most of the tests that you will write using TDD.
In a true Test Driven Development process you will first write a failing test before adding any new functionality to your software, then write the code that causes the test to pass, rinse and repeat.

Genetic algorithms for image processing project

By : sara
Date : March 29 2020, 07:55 AM
wish of those help if its for tuning parameters you could take a known image and apply a known blurring/low pass filter. Then sharpen this with your GA+USM algorithm. Calculate your fitness function making use of the original image, e.g maybe something as simple as the mean absolute error. May need to create different datasets, e.g. landscape images (mostly sharp, in focus with large depth of field), portrait images (could be large areas deliberately out of focus and "soft"), along with low noise and noisy images. Sharpening noisy images is actually quite a challenge.
It would definitely be worth taking a look at Bruce Frasier' work on sharpening techniques for Photoshop etc.

Performance of image processing algorithms over android smartphones

By : user3544618
Date : March 29 2020, 07:55 AM
like below fixes the issue It's only viable to do optimization after you have done measurements for your particular case.
If you need HW acceleration you might want to check out renderscript. It gives you access to GPU hardware to perform generic computations.

is jpg format good for image processing algorithms

By : user3784031
Date : March 29 2020, 07:55 AM
I hope this helps you . JPG is an entire family of implementations, there are actually 4 methods. The most common method is the "normal" method, based on the Discrete Cosine Transform. This simply divides the image in 8x8 blocks and calculates the DCT of this. This results in a list of coefficients. To store these coefficients efficiently, they are multiplied by some other matrix (quantization matrix), such that the higher frequencies are usually rounded to zero. This is the only lossy step in the process. The reason this is done is to be able to store the coefficients more efficiently than before.
So, your question is not answered very easily. It also depends on the size of the input, if you have a sufficiently large image (say 3000x2000), stored at a relatively high precision, you will have no trouble with artefacts. A small image with a high compression rate might cause troubles.

Amazing algorithms for image processing

By : Ollie Hulme
Date : March 29 2020, 07:55 AM
will help you Even though this is offtopic I'm going to answer ;)
In this page you can find algorithms which:
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