Project 5a - Object detection I, example #1

Project start: 1 January 2022

Project finish: 3 January 2022

Objective: test a program from Ref. 4 which detects objects using YOLOv4 (using YOLOv3 files) in real time using a USB camera connected to a Jetson Nano.

[Ref 4.] Valentyn Sichkar, "Train YOLO for Object Detection with Custom Data", Udemy, date unknown

The following .zip file contains a Jupyter Notebook program based on a program from the Udemy course and required data files (to run Jupyter Notebook, type jupyter-notebook):

project_5a_USB_V0_with_data.zip

Download ZIP • 230.10MB

The directory structure used is:

/Projects

└── Project_5a

├── project_5a_USB_V0.ipynb

└── yolo-coco-data

├── coco.names

├── yolov3.cfg

└── yolov3.weights

1 )yolov3.cfg: contains structure of convolutional neural network

2)yolov3.weights: contains weights for neural network

3)coco.names: contains the names of the classes of objects for which the neural network was trained

If you have any problems or need clarification please contact me: jscanova@gmail.com