recognition | Reward users with points for their actions | Application Framework library

I am trying to code a bot to automate some tasks on a videogame with JS and Node, so far I've been using RobotJS. The problem I'm facing is that I need to find something on the screen as it moves from time to time to then click on it. Something similar to PyAutoGUI locateOnScreen() function.

It needs to use AI to have some tolerance too, as the image will not be exactly the same from time to time, though it's almost the same so I think any basic AI for image recognition would detect it fine.

Does anyone have an idea on what to use for this specific case?

I have a dataset of tens of thousands of dialogues / conversations between a customer and customer support. These dialogues, which could be forum posts, or long-winded email conversations, have been hand-annotated to highlight the sentence containing the customers problem. For example:

Dear agent, I am writing to you because I have a very annoying problem with my washing machine. I bought it three weeks ago and was very happy with it. However, this morning the door does not lock properly. Please help

Dear customer.... etc

The highlighted sentence would be:

However, this morning the door does not lock properly.

1. What approaches can I take to model this, so that in future I can automatically extract the customers problem? The domain of the datasets are broad, but within the hardware space, so it could be appliances, gadgets, machinery etc.
2. What is this type of problem called? I thought this might be called "intent recognition", but most guides seem to refer to multiclass classification. The sentence either is or isn't the customers problem. I considered analysing each sentence and performing binary classification, but I'd like to explore options that take into account the context of the rest of the conversation if possible.
3. What resources are available to research how to implement this in Python (using tensorflow or pytorch)

I found a model on HuggingFace which has been pre-trained with customer dialogues, and have read the research paper, so I was considering fine-tuning this as a starting point, but I only have experience with text (multiclass/multilabel) classification when it comes to transformers.

the grammar is simple enough:

I have created a spacy transformer model for named entity recognition. Last time I trained till it reached 90% accuracy and I also have a model-best directory from where I can load my trained model for predictions. But now I have some more data samples and I wish to resume training this spacy transformer. I saw that we can do it by changing the config.cfg but clueless about 'what to change?'

This is my config.cfg after running python -m spacy init fill-config ./base_config.cfg ./config.cfg:

I am using Microsoft Computer Vision API for OCR processing and I noticed that they are getting charged as S3 transactions instead of S2 in my bill.

I'm using the .NET SDK and the API I am using is this one. https://docs.microsoft.com/en-us/dotnet/api/microsoft.azure.cognitiveservices.vision.computervision.computervisionclientextensions.readasync?view=azure-dotnet

I have also confirmed that the actual REST API the SDK calls is the following POST /vision/v3.2/read/analyze https://centraluseuap.dev.cognitive.microsoft.com/docs/services/computer-vision-v3-2/operations/5d986960601faab4bf452005

According to documentation, that should be the OCR Read API, am I correct? https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/vision-api-how-to-topics/call-read-api

I am puzzled as to why my calls are getting charged as S3 instead of S2. This is important for me because S3 is 50% more expensive than S2. Using the Pricing Calculator, 1000 S2 transactions is $1, whereas 1000 S3 transactions is $1.5. https://azure.microsoft.com/en-us/pricing/calculator/?service=cognitive-services

What's the difference between OCR and "Describe and Recognize Text" anyways? OCR (Optical Character Recognition) by definition must recognize text. I am calling the Read API without any of the optional parameters so I did not ask for "Describe" hence the call should be S2 feature rather than S3 feature I think.

I already posted this question at Microsoft Q&A but I thought SO might get more traffic hence help me get an answer faster. https://docs.microsoft.com/en-us/answers/questions/689767/computer-vision-api-charged-as-s3-transaction-inst.html

I annotate text data (building data sets for named entity recognition models) using AlpacaTag, which was designed using Python on Django. I followed the steps of AlpacaTag installation guide When I run the command
python manage.py migrate
(I come to find information, to know this is the Django's command of database migration),
The program threw an exception:

I'm new to AWS and it's services. What I want to achieve is a multi-tenancy SaaS application. What my concept looks like: I use Cognito for user authentication. There all users no matter what tenant they belong to should use one frontend to login. For the tenant-recognition I use a custom attribute "custom:tenant" which I get from the JWT when the login is successful. For the applicantion itself I want to use VPCs and to ensure encapsulation each tenant should have their own VPC.

Example:

• User A of Tenant 1 login and gets back JWT with claim "custom:tenant":"1" should be routed to VPC 1
• User B of Tenant 2 login and gets back JWT with claim "custom:tenant":"2" should be routed to VPC 2

Now my question is: how do I achieve this routing from the success of the login to the appropriate VPC? Do I need further Services for that or where do I find these settings?

I have a folder that contains 200 images. I loaded all these images into an array list of type image called training. I have a problem converting this to a one dimension vector. I need help with this, am writing a PCA based solution for face recognition, Thank You.

I have recently migrated my app to Flutter 2 with null safety and I encountered weird error. I have following function which I use to convert CameraImage (YUV) into RGB image, which worked flawlessly before going from Flutter 1.26 to 2.3 and migrating. Afterwards, it started to complain about RangeError (index): Index out of range, which I do not understand and error description is not helpful.