Prototype for Baby Action Detection and Classification

Sep 07, 2021 2 min read

Baby Action Detection

An attempt to harness the power of Deep Learning to come up with a solution that can let us detect various classes of activities an infant, toddler or a baby is performing in real-time. This POC can then be published as an end-to-end deployable cloud project.

The model does not restrict predictions for babies only, it is applicable to all entities that appears in a human posture. So temporary, this needs to be handled at project level.

Special thanks to nicknochnack/ActionDetectionforSignLanguage repository for putting up such helpful content. Without it this project might have never existed.

Data collection

Data was collected from YouTube video clips. Human pose keypoints were extracted with the help of MediaPipe.

Classes trained

Baby Walking
Baby Still (no movement, can be considered as sleeping)
Baby Crawling

Install

Create a new environment and use below command for installing all required packages

pip install -r- requirements.txt

Run Predictions

Rename your baby video as input.mp4 and place it inside /raw directory.
Open cmd and traverse to the project directory.
To run the prediction script, just do:

python prediction.py

Demo

Full Demo - Drive Link

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GitHub

Detection Computer Vision Deep Learning Machine Learning

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