Skip to content

Latest commit

 

History

History
22 lines (17 loc) · 1.05 KB

README.md

File metadata and controls

22 lines (17 loc) · 1.05 KB

eyeball-sam

What: Real-time object detection, person detection, and face recognition using YOLOv7 in TensorFlow Lite targeted for devices at the edge with Google Coral hardware.

Requirements:

Software

  • 🖥️ Ubuntu 20.04
  • 🐍️ Python 3.8
  • 📦️ See requirements.txt, there are a lot.
  • 📷️ It is recommend to build OpenCV from source for local testing (or just in general). use the requirements.txt version.

Hardware

  • 🌊️ Google Coral. They have low-wattage USB and M.2 TPUs. A must for real-time video processing.

Usage:

  1. Create a virtual environment and pip install -r requirements.txt.
  2. Run the create_tf_lite.ipynb notebook to download use the model weights. This notebook will convert ONNX format to tf-lite.
  3. Run tfl_yolov7_main.py.

Note: by default, openCV will use your wedcam (cv2.VideoCapture(0))

This project was updated on 01/29/2024