/TF-Lite-Python-Object-Objection

Object detection examples using pre-trained models on Tensorflow Lite and OpenCV

Primary LanguagePythonMIT LicenseMIT

Object Detection Examples With Tensorflow Lite and OpenCV (Python)

Running pre-trained TF Lite models for object detection. You either have to install Tehsorflow or Tensorflow Lite (tflite_runtime) and OpenCV (opencv-python). These scripts also run a lot faster on a ARM device, for example, a Raspberry Pi 3B or 4B.

There are three models available here (downloaded from Google):

  • SSD-MobileNet V1
  • EfficientDet-Lite0
  • YOLO V5

All three are trained with the COCO dataset (labelmap.txt is the label list). This is mainly a demostration of how to get the possible things as well as their location from the model.

result

TF_Lite_Object_Detection.py can use either SSD or EfficientNet to process a still image, and TF_Lite_Object_Detection_Yolo.py is the YOLO version. TF_Lite_Object_Detection_Live.py use live USB cam images with SSD or EfficientNet (press q).