https://github.com/bbbmau/selfdrivedataset

A sample of the Berkeley Deep Drive Dataset that shows the how data is organized from video images.
https://github.com/bbbmau/selfdrivedataset

Last synced: 2 days ago
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A sample of the Berkeley Deep Drive Dataset that shows the how data is organized from video images.

• Host: GitHub
• URL: https://github.com/bbbmau/selfdrivedataset
• Owner: BBBmau
• Created: 2020-09-08T18:30:24.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2021-07-02T17:38:40.000Z (over 3 years ago)
• Last Synced: 2024-11-19T12:58:37.249Z (2 months ago)
• Language: Python
• Size: 99.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Deep Drive Data Set Usage

A sample of the Berkeley Deep Drive Dataset that shows the how data is organized from video images.

![Berkeley Logo](logo-v2.png)

PRODUCT NAME: Berkeley S.D Label Reader

USER GUIDE

This program is used with the help of Berkeley Deep Drive Data to given a visual representation of self driving labels and what they look

like in the images that are scanned when the cars are being driven.

VERSION 1.0

- Analyzed the Data with the help of import json

- using Dictionaries to grab and store data

VERSION 1.1

- Sorted the Data based on what the user is wanting

VERSION 1.2

- GUI being implemented

- allows user the ability to see labels based on which one is chosen from the listbox

- listbox still being in development, can only be changed through the code. Only functioning lablels are Box2D Data 

FUTURE PLANS

- have a function listBox where when one is chosen, changes the label that is shown on the image.

- add check boxes that give the user the choice of how many labels appear on the screen.

- add the ability to change from images that are part of the berkeley deep drive database

- give the user ability to add labels on the spot

- give user ability to add an image of their choice to add labels to it

REFERENCE MATERIALS

- Learning how to implement a .JSON file as well as how to work with Dictionaries

- using Tkinter and the PIL Library (Python Image Library) for help in the GUI

	along with making it possible for users to see the labels from the data