selfie | educational software system of a tiny self | Emulator library

--LONG VERSION--

I made a super basic REST API to handle user account management (account creation, checking login credentials, etc.) that I will call from a Unity3D game, for which I plan to support mobile (mainly android).

Players would upload drawings that they'd make with a drawing tool that exists inside of the Unity game. I made that tool for the sole purpose of preventing the possibility of someone either uploading a screenshot of a drawing that they didn't draw themselves, or someone uploading a selfie or a pornographic photo (for which I cannot allow the possibility to happen, since my game is primarily targeted to children), and those drawings can be publicly viewed by other players.

--SHORT VERSION--

To store an uploaded drawing I would use a simple $_GET['base64'], but in order to prevent disallowed images from coming in, how can I assure that the request is coming from an official android build and not, say, some cURL or a reverse-engineered Unity project?

That's the whole question.

In the case of a WebGL build I could just block any web request that is not coming from the domain that the WebGL build is in, but in the case of the android build however, as far as I know the server can't really tell a request sent by an official android build from some request sent by a cURL. And I'm pretty sure that someone, with a bit of effort, can figure out how my REST API works. I have no idea of how to effectively secure it.

I'd like some suggestions, and if you think that my current approach is terrible (and it probably is) tell me how to improve on it or what to replace it with.

I need to auto capture the selfie image when smile or movement detected through camera in flutter. How can I achieve this, is there any tool or libraries?

I'm trying to write a regular expression that needs to return every tag name, attribute name, and attribute value

Here is the code example

I am using Google ML Kit to do selfie segmentation (https://developers.google.com/ml-kit/vision/selfie-segmentation). However, the output am getting is exteremely poor -

Initial image:

Segmented image with overlay: Observe how the woman's hair is marked pink and the gym equipment and surrounds near her legs are marked non-pink. Even her hands are marked pink (meaning its a background).

When this is overlayed on another image, to create a background removal effect, it looks terrible

The segmentation mask returned by the ML Kit has confidence of 1.0 for all the above non-pink areas, meaning its absolutely certain that the areas non-pink are part of the person!!

Am seeing this for several images, not just this one. Infact, the performance (confidence) is pretty poor for an image segmenter.

Question is - is there a way to improve it, maybe by providing a different/better model? If I use something like the PixelLib, the segmentation is way better, albeit the performance of the library is not low latency, hence can't be run on the mobile.

Any pointers/help regardig this would be really appreciated.

I'm trying to upload a photo and pass it's data and one more data on another php file.When I select the photo and upload it a current php file give an error: Uncaught ReferenceError: PZ71AUGW5O295 is not defined. PZ71AUGW5O295 is the teamCode which gets.Sorry for the possible grammatical mistakes.

So my task is to clean up the data in a giant table, and create a linear regression model with the data. I noticed a problem that one of the columns store a bunch of tags in a string. The following snippet is two elements in that column.

I currently have a form in my app that looks like this:

However I would like to add a white panel behind the form, the panel must still show the background behind it

When I use the

Does anyone know how I can add this with HTML / CSS

Please see the below code for assistance:

I am using strong loop for api creation. But it is giving me error. Properties of my json file are :

So I have an application that uses CameraX ImageCapture use case to take a selfie picture than then is passed to an AI algorithm to do some stuff with it.

Now, I have an user with a Samsung Galaxy S21 who when taking pictures in one specific place with some specific light conditions is producing an image that doesn't work as expected with the AI algorithm. I have examined these images myself and noticed that the problem seems to be that ImageCapture applies strong noise reduction, so strong that even for the human eye it looks wrong, like if it was a painting instead of a photograph.

I sent a modified version of such app to this user for trying which captures the image from the Analysis use case instead and the produced image does not have that problem, so it seems whatever it is, it's some post-processing done by the ImageCapture use case that's not done in the Analysis use case.

Now, I don't seem to find a way to tweak this post-processing in CameraX, in fact I haven't even found how to do it with Camera2 neither. At first I thought it may be HDR, and I found there are some extensions to enable HDR, Night Mode and such in CameraX, but all these are disabled by default according to the documentation, and as far as you use the DEFAULT_FRONT_CAMERA none should be applied, and that's what I'm using.

CameraSelector.DEFAULT_FRONT_CAMERA

In any case it's clear that some heavy post-processing is being done to these images in the ImageCapture use case, so I'm wondering how could I disable these.

BTW, I tried initialising the ImageCapture use case with CAPTURE_MODE_MINIMIZE_LATENCY in the hope that such flag would reduce the post-processing and hopefully remove noise reduction, but that didn't work.