ibaiGorordo/ONNX-YOLOv5-Instance-Segmentation
Python scripts performing instance segmentation using the YOLOv5 model in ONNX.
This project helps developers integrate object instance segmentation into their Python applications. It takes images or video streams as input and outputs identified objects with pixel-level masks, distinguishing each instance of an object even if they are of the same class. This is ideal for machine vision engineers, robotics developers, or anyone building systems that need to precisely locate and differentiate individual items in visual data.
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Use this if you are a Python developer needing to add real-time, precise object instance segmentation capabilities to your computer vision applications, especially for tasks like identifying and isolating specific items on a conveyor belt or people in a crowd.
Not ideal if you need a no-code solution or a readily available application with a graphical user interface, as this project provides the underlying code for developers to build upon.
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42
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Language
Python
License
MIT
Category
Last pushed
Dec 21, 2022
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