objectImageIdentifierAI

• imagesToDataset
  • From two directories ('object' and 'noobject'), gets all the images inside the directories and generates the dataset
• nnTrain
  • From the dataset file generated in the previous step, train the Neural Network
• serverPredictor
  • Runs a server API, that with the Neural Network classifies the incoming images
• smartphoneApp
  • Take photo and upload to the server, to get the response (object or no object)

Real steps

• download images
  • for example, can be done with https://github.com/arnaucode/imgDownloader.git
• In /serverPredictor directory

python classifierChooser.py

This will generate the model.pkl. Then, run the serverPredictor.py

python serverPredictor.py