the goal is to create a deep learning model to generate an avatar from the input text ( it asks for text input and generate an avatar for the corresponding text)

I have a dataset of video files from a sign language actor (.mp4 files) with the corresponding caption ( label ) for each action.

Do i need to first generate a skeleton from the Sign language actor ( from the dataset ) and then fed it into another model to generate avatar? if so please write the complete code of both models in python ( skeleton and avatar)!

I dont want to use other sofwares such as blender, ...
i want the whole story to be over python! ( using defusion or gan or any other new ways )

what is the best choice , openpose or mediapipe? please rewrite the code according to the best choice and dataset( my dataset consists of multiple video files in different dirrectories acoording to their labels)

first obtain skeleton features and then train the model accordingly ( be aware of dataset structure )

what are the requirements for running codes with detailed versions mentioning ( python version, tensorflow, number of gpus, packages , ... ) suitable for my computer that i want to run the code on is MSI GT83VR, as i want to install it on a computer with gpu, would it be better to download the gpu driver, cuda , ... and all the requirements with mamba? with a bash file to install them on ubuntu 20.04 system. i'm not sure if it has the appropriate python version or not ( it has a pure installation of ubuntu 20.04.5)

my dataset consists of 5000 Provide your response in exactly 2 paragraphs (separated nearby paragraphs with 3 aterisk symbols ***).
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