https://github.com/ankitbko/vision-on-edge

https://github.com/ankitbko/vision-on-edge

Last synced: 2 months ago
JSON representation

• Host: GitHub
• URL: https://github.com/ankitbko/vision-on-edge
• Owner: ankitbko
• License: mit
• Created: 2022-06-22T07:14:28.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-06-24T04:55:06.000Z (over 2 years ago)
• Last Synced: 2023-08-12T14:46:20.951Z (over 1 year ago)
• Language: Python
• Size: 32.5 MB
• Stars: 3
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Object detection Sample Application

The sample provided is an implementation of the above design discussed in blog posts. [TODO: Link to blog posts](http://LINK).

## Running the sample

### Prerequisite

To execute the sample, the developer machine must have either -

* [Visual Studio Code](https://code.visualstudio.com/)

* [Docker](https://docs.docker.com/engine/install/)

OR

* [Python 3.9](https://www.python.org/downloads/release/python-390/)

### Steps

1. Clone the repository.

1. Prepare environment.

    1. If using Docker and Visual Studio Code, open the repository in [Visual Studio Code Remote - Containers](https://code.visualstudio.com/docs/remote/containers) following this [guide](https://code.visualstudio.com/docs/remote/containers#_reopen-folder-in-container)

    1. Or in case of using Python, install the [required packages](../code/requirements.txt) using [pip](https://pip.pypa.io/en/stable/)

1. Run command `python main.py` from *multiprocessing* to start the sample.

1. The video feed will be shown in User Interface, via ULR [http://localhost:7001/](http://localhost:7001/).

1. The time taken by the ML model to process the frame will be shown in the Console.