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Human Posture Recognition System

  • The objectives of the project are to -
    • Make a dataset for posture recognition.
    • Use the dataset to create a CNN classifier.
  • The following postures have been considered -
    • Bending
    • Lying
    • Sitting
    • Standing
  • The programs have been written using Python3 in Google Colab.

Dataset

  • The dataset is available as downloadable zip file under Dataset folder.

  • The size of images available are 256 x 256 and 512 x 512.

  • Each of the zip file follow the following directory structure -

    .
|--Training
|  |--Bending
|  |--Sitting
|  |--Lying
|  |--Standing
|
|--Validation
|  |--Bending
|  |--Sitting
|  |--Lying
|  |--Standing

Structure Description

  • Dataset - Contains the dataset.
  • ScratchModel - Contains the program used for training the classifier from scratch. It also contains a script to make prediction using the saved model.
  • TransferLearning - Contains the pre trained weight files and the programs for performing transfer learning.
  • The pre trained model can be downloaded from ./ScratchModel/model/ and executed using ./ScratchModel/model/predict.ipynb