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SignLanguageDetection_TenserflowLite

Project to deploy a Machine Learning Model on a Rasberry Pi

Machine learning based on tensorflow and a costum dataset & convert it to Lite model to run on embedded devices as raspberry pi or android

Setup

  • clone this repository with git clone --recurse-submodules -j8 https://github.com/Yeshey/SignLanguageDetection_TenserFlow_RaspberryPi.git
  • follow the SignLanguageDetection.ipynb file to setup, train and run/convert the model

Notes

  • American sign language letters image
  • See Nvidia available memory in linux with watch -n 0.1 nvidia-smi
  • Activate environment `conda activate signLanguageDetector'
  • RasberryPi Credentials:
    • User: pi
    • Passwd: raspberry
  • Wifi Connection:
    • Connect using the hostname: ssh pi@raspberrypi
    • Connecting using ip (connected to yeshey-hotspot): 'ssh [email protected]'
    • Commands:
      • sudo nano /etc/wpa_supplicant/wpa_supplicant.conf - file that says wich networks it will connect to
      • sudo iwlist wlan0 scanning | grep ESSID - show available wlan connections
      • iwconfig | grep wlan0 - show currently active wlan connection

Logical flow of.. steps

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Project to deploy a Machine Learning Model on a Rasberry Pi

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