Tensorflow Image segmentation

For my Image colorization project, I am trying to be able to get the class label for a given pixel in an image. For example, I want to be able to know if a given pixel of the image belongs to sky, person, tree, flower, ocean, etc.

I am looking to be able to use a pre-trained model which does this, as my main goal is to implement an Image colorizer (similar to this research paper: https://link.springer.com/article/10.1007/s11263-019-01271-4).

I have looked at: https://www.tensorflow.org/tutorials/images/segmentation and https://www.tensorflow.org/tutorials/images/classification

but it looks like the model needs to be trained.

I am new to tensorflow so anyone knows about something similar, please let me know.

I need help with my Logic (Resize an image)

Hey Guys!!

I'm trying to put some PHP code to resize an image.

Basically users upload an image. And that image gets placed on a PDF document but I need to limit how big (Pixels) that image is. If it's height is too large it will push the contents on to the 2nd page. Which I don't want.

Currently, I have this code which works to some extent but what I want is if the width of the picture is more than 80 that's totally ok as it doesn't push the page down.:

But then again I wanna…

I need help with my Logic (Resize an image)

How to automatically set ‘default image size’ for specific Custom Post Type

I’m looking to automatically set the default image size in the WordPress WYSIWYG, but only on certain Custom Post Types. For example, my CPT ‘products’ would default to ‘medium’, and CPT ‘staff’ would default to ‘full’.

I’ve used the following code below to update media sizes for all CPT’s, not just a specific one. Is this possible?

Here is the code I’m using for site-wide definitions:

function custom_image_size() {   update_option('image_default_size', 'full' ); }  add_action('after_setup_theme', 'custom_image_size'); 

Deep learning: how to represent 24 fraction image into 1 image?

Goal: Represent 24 fractions images into one image. These 24 fractions belong to one patient. We want to represent one patient with one image. How to manipulate the data to achieve it: (T.A. suggested to divide the picture in 100 key parts with crucial data and merge only those key parts)

My Take on this: I have tried HOG and SIFT(Scale-Invariant Feature Transform)enter image description here algorithm and as you can see the HOG results in Black and white output picture as attached and the colorful picture is the SIFT output. The problem with this is that: The output image does not distinguish the red (cancer) and blue (non-cancer).i.e the color changes.

My Question: I am still learning Deep learning as I go along. Please excuse the naive questions. What are the steps necessary to represent 24 fraction images (red-blue dotted ones) into one image? without changing the colors? enter image description here

Is Silent Image animated if an action is not used to move it?

You can use your action to cause the image to move to any spot within range. As the image changes location you can alter its appearance so that its movement appear naturel for the image.

So, we know that when the caster use an action to move the image, the movement appears natural. But what happen if the caster uses his action to do something else, like, cast a firebolt? Will the image become perfectly still?

Let’s say a caster uses his action to cast the image of a campfire with silent image.

  1. Will the flames flicker naturally? Or does he have to use his action so the flames keep moving? What happen if he doesnt use his action? Do the flames froze and become perfectly still?

  2. When casting silent image to create the image of a campfire, can the caster make it looks like the fire is lighting up (starting from a spark then grow)