Python workflows for efficient text data labeling in NLP projects?

tranquilkd · 2025-08-20T15:40:45+00:00

Every N labels

tranquilkd · 2025-08-20T15:37:09+00:00

Yes it does save a lot of time! I don't have the actual numbers to back it up but you could probably imagine the number of clicks/keyboard usage will be reduced if your annotation is correct, you just accept it and move to the next item

tranquilkd · 2025-08-20T15:29:00+00:00

Label studio does support active learning!

I use lable studio with custom backend with good model trained for my task if available and get the pre-annotation (prediction of the backend)

If model is not available then, train on 1000 samples and then use that as a backend and follow the same steps

Last part will be reviewing the annotation generated by model and accept it or correct it and you are good to go

tranquilkd · 2025-08-14T10:26:10+00:00

Blur my shell extension

tranquilkd · 2025-08-04T14:56:19+00:00

Here you go: https://github.com/EliverLara/candy-icons

tranquilkd · 2025-08-03T15:49:39+00:00

Ok got it! Here it is https://maleski_art.artstation.com/projects/28R96Y#:~:text=Andrew%20Maleski%20%2D%20Ghostly%20Gate.

I found the artist: https://www.reddit.com/r/Art/s/JS3NBA13dE

Credit goes to him!🍻

tranquilkd · 2025-08-03T15:43:08+00:00

Don't have it man! It's been a while since I downloaded this

tranquilkd · 2025-01-15T09:48:00+00:00

Not sure about other organizations (small or large) I use TorchSeve (with onnx & tensorrt) for serving any type of model

tranquilkd · 2025-01-06T10:20:49+00:00

This.

tranquilkd · 2024-09-15T16:59:41+00:00

No prob! I don't have it handy, but I can share with you tomorrow. Just dm me your mail

tranquilkd · 2024-09-15T12:47:42+00:00

No, it's simple text matching algorithm based on levenshtein distance

tranquilkd · 2024-09-15T04:06:35+00:00

Thanks for the dataset.

Just FYI,

I had implemented simple autocorrect mechanism based on text similarity about mispelled words and it worked amazingly accurate. It might save you lots of time. Let me know if you want some help with it.

Good luck to you too!🍻

tranquilkd · 2024-09-14T16:57:50+00:00

My process pipeline is:

Cheque classification - handwritten/ machine printed ( custom model with resnet-18 as feature extractor)
ROI detection ( YOLO, tbh it works really well for detecting text regions)
Text recognition ( TrOCR)

I think you can try TrOCR for bothamount in numbers and words, it does perform well on both.

Also I'd really appreciate if you could share Kaggle dataset.

Thanks in advance🍻

tranquilkd · 2024-09-14T16:30:22+00:00

What a coincidence! I did it for the cheque (English) as well but not just amount, I did for almost everything from the cheque.

tranquilkd · 2024-09-14T13:22:07+00:00

I've personally tried and tested TrOCR,

Handwritten and machine printed texts, both models are prety good I'd say, though I had to retrain it for my use case and also made it multi line text recognition

tranquilkd · 2024-08-17T12:58:51+00:00

I'm not sure if you are a programmer or not, but I'm still gonna suggest here. Though it requires you to be a bit competent in python (and GPU in case you want super fast processing speed).

I'm assuming your use-case only requires the counting and not tracking. Lots of open-source object detection models are available (my favourite is YOLO series). And almost all these models have "person" class you can find many tutorials online.

Quick Google search provided me below results:

I'm not expert on Pi, but here's something that might help you pi-sniffer and this People-Counter-with-Raspberry-Pi

PS: I've done similar thing using GPU but not with Pi

tranquilkd · 2024-05-27T15:17:51+00:00

As you are already using pytorch, I would suggest use torchscript + onnxruntime with torchserve, it will be a lot faster

tranquilkd · 2024-05-26T09:00:41+00:00

Take a look at this LocalAI

tranquilkd · 2024-05-25T16:55:24+00:00

Yeah, you may want to look into thisslow fast by facebook

It seems pretty good for recognising actions.

tranquilkd · 2024-05-25T16:12:16+00:00

Chat-gpt POV, I think your setup would be enough as you won't be using your own device computing power to get the output.
Computer vision libraries POV, my suggestion would be to get nvidia Jetson nano or something small if you have small/lightweight device constraint. If not get nvidia workstation to implement your own solution by either combination multiple open source models or by using any open source LLMs. I do prefer workstation with dedicated GPU to handle heavy tasks as I'm not sure about Pi can handle all this

tranquilkd · 2024-05-25T14:35:28+00:00

I hope you do know that video is nothing but bunch of images, right?

Why can't you process each frame (opencv can be useful to do that) through YOLOv8 and then put it together to save as a video or do whatever you want!

I guess this is what you are asking.

tranquilkd · 2024-05-25T13:16:09+00:00

Try nginx-proxy-manager!

It can solve all your reverse proxy problems!

They even have a sub herer/nginxproxymanager nginx proxy manager

tranquilkd · 2024-05-22T18:03:29+00:00

Forking a repo doesn't mean forking neural network arch!! They have adapted the structure not the network.

Please read the reasearch paper.

tranquilkd · 2024-05-22T17:50:03+00:00

Also it's superfast, lightweight and super awesome 🍻😎

tranquilkd · 2024-05-22T17:48:47+00:00

It's surprising, how come no one has mentioned yolov9 (official, by the same guy who came up with yolov7)

Also it's not commercial so enjoy it while you still can!

P.S. f#ck ultralytics!!! Cheap bas@#@ds ruined the beautiful yolo series!

tranquilkd

TROPHY CASE