sign-language-processing / lexicon-induction

Induce a lexicon from a continuous sign language corpus
MIT License
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How to adequate categorize and collect Signbank / Corpus Videos for preparing dataset #1

Open rem0g opened 1 month ago

rem0g commented 1 month ago

I have run the interference from ASL signs on NGT videos, and i have to say the model has produced some surprising results.

The model recognized dutch signs and produced glosses from similair ASL signs.

Now I want to prepare dataset from Corpus NGT, signCollect (which consist 4K 60FPS quality) and Signbank.

Then i have to run the training script from asl competition.

@AmitMY is the preparation I have in my mind right?

rem0g commented 1 month ago

Oline also has created synthetic dataset of 200 NGT glosses of which consist of videos from avatar that produces signs from different angles.

AmitMY commented 1 month ago

If you would like to train your own identification model, go ahead, that is the process, but it should belong in a different repository - https://github.com/sign-language-processing/recognition for example.

I however don't think it is a great use of your time. Instead, if you want to perform classification, right now, get a vector to represent each sign in your dictionary (using the recognition model before softmax, or CLIP), then you can perform kNN on new videos to find a match. This requires no training, allows you to annotate data on the fly, and will result in visually cluster-able data.

rem0g commented 2 weeks ago

I was sick for a while, but now i'm better.

Can you expand a bit more about how to get vector from a sign? Or all the steps in a more practical way, because I am not really proficient with training model as I am still learning.

Thank you!

AmitMY commented 2 weeks ago
from sign_language_recognition.kaggle_asl_signs import predict
from pose_format import Pose

data_buffer = open("file.pose", "rb").read()
pose = Pose.read(data_buffer)
vector = predict(pose)