adaptive-led-matrix-highbeams | A project to demonstrate how an adaptive LED high beam
kandi X-RAY | adaptive-led-matrix-highbeams Summary
kandi X-RAY | adaptive-led-matrix-highbeams Summary
This project was created to demonstrate a more sophisticated approach to modern/standard headlight technology used in present cars. In addition to having mandatory low and high beams, this project aims to demonstrate how the flexibility of LEDs can be used to create safer driving environment under low light/dark conditions. The main objective of this technology is to illuminate as much of the road as possible while not dazzling other drivers for both oncoming and preceding traffic. This is made possible in this project with 2 sub-systems in communication. First is the module to control the hardware (LED matrix), second is a camera feed with a trained object detection model to detect vehicles, locate them and determine where to lighten/darken.
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Top functions reviewed by kandi - BETA
- Draws the vehicle s vehicle .
- Draw a single vehicle
- Switch LEDs on the device .
adaptive-led-matrix-highbeams Key Features
adaptive-led-matrix-highbeams Examples and Code Snippets
Community Discussions
Trending Discussions on Internet of Things (IoT)
QUESTION
I have js files Dashboard and Adverts. I managed to get Dashboard to list the information in one json file (advertisers), but when clicking on an advertiser I want it to navigate to a separate page that will display some data (Say title and text) from the second json file (productadverts). I can't get it to work. Below is the code for the Dashboard and next for Adverts. Then the json files
...ANSWER
Answered 2020-May-17 at 23:55The new object to get params in React Navigation 5 is:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install adaptive-led-matrix-highbeams
LEDController folder includes the file for an Arduino microcontroller and is responsible for controlling the LED matrix module based on the input from vehicle detection part (Python).
Python folder includes the Python script vehicleDetect.py for vehicle detection, an inference graph for the pretrained model and a label_map.pbtxt file to map the labels.
Arduino IDE (https://www.arduino.cc/en/main/software)
Python 3.6 or higher (https://www.python.org/downloads/)
Tensorflow Object Detection API included in their models repository (https://github.com/tensorflow/models)
Microsoft Visual Studio (https://visualstudio.microsoft.com/free-developer-offers/)
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