##Notes:
use tf-lite
supervised Learning
Image Segmentation and Object detection
https://www.kaggle.com/datasets/aruchomu/data-for-yolo-v3-kernel?select=office.jpg https://www.kaggle.com/datasets/soumikrakshit/nyu-depth-v2 https://www.kaggle.com/datasets/itsahmad/indoor-scenes-cvpr-2019 https://www.kaggle.com/datasets/balraj98/indoor-training-set-its-residestandard https://www.kaggle.com/datasets/luznoc/indoor-random-track-sample-dataset https://www.kaggle.com/datasets/balraj98/synthetic-objective-testing-set-sots-reside https://www.kaggle.com/datasets/luznoc/indoor-scene-composition https://www.kaggle.com/datasets/stuartjames/lights https://www.kaggle.com/datasets/lehomme/deep-person-detection-on-non-cenital-data https://www.kaggle.com/datasets/datatangai/50-types-of-dynamic-gesture-recognition-data https://www.kaggle.com/datasets/luznoc/synthetic-data-generation-for-messyindoors https://www.kaggle.com/datasets/celsopereira1/visible-light-positioning-dataset
#Steps:
- Detect Object with help of ML_Model
find dataset for supervised learning
- Show result in GUI