Difference between revisions of "Shared:2023W4G1CV"

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      The Jupyter notebook embedded below is a Computer Vision script written to aid the robotic hand in identifying our components, locating the appropriate grabbing spots and separating it from the background. The code uses a combination of libraries to achieve this.
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The code was written in a manner that allows it to be used with any image, so feel free to give it a try with your own fragments!
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The Jupyter notebook below contains a Computer Vision script designed to assist a robotic hand in identifying components, locating the appropriate grabbing spots, and separating them from the background. This code uses a combination of Python libraries, including OpenCV and Shapely, to achieve its objectives. The code is designed to be versatile and can be used with any image, making it a valuable tool for anyone working with robotic components.
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Whether you're a researcher or a hobbyist, this script is an excellent resource for automating the process of component identification and removal. Give it a try with your own fragments and see what you can accomplish!
 
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   <iframe src="https://nbviewer.org/github/arnodecorte/IA-Computer-Vision/blob/main/Group1_CV%20%281%29.ipynb" style="width: 100%; height: 100%;"></iframe>
 
   <iframe src="https://nbviewer.org/github/arnodecorte/IA-Computer-Vision/blob/main/Group1_CV%20%281%29.ipynb" style="width: 100%; height: 100%;"></iframe>
 
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[[File:CODEGIF.gif]]
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      '''Sources'''
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      Images Mars, Nasa
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Latest revision as of 10:46, 21 April 2023

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MARS HABITAT



Prototype water research station for the human endeavour of discovering water on Mars.
Group 1 Arno Decorte - Tom Punte - Augusta Fiseryte


CV

HRI






The Jupyter notebook below contains a Computer Vision script designed to assist a robotic hand in identifying components, locating the appropriate grabbing spots, and separating them from the background. This code uses a combination of Python libraries, including OpenCV and Shapely, to achieve its objectives. The code is designed to be versatile and can be used with any image, making it a valuable tool for anyone working with robotic components.

Whether you're a researcher or a hobbyist, this script is an excellent resource for automating the process of component identification and removal. Give it a try with your own fragments and see what you can accomplish!


[[File:CODEGIF.gif]]