Difference between revisions of "Shared:2023W4G1CV"
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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. | 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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<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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Revision as of 10:26, 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
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]]
