IbrahimSobh/Segmentation
In this tutorial, you will perform inference across 10 well-known pre-trained semantic segmentors and fine-tune on a custom dataset. Design and train your own segmentor.
This project helps you classify every pixel in an image, segmenting it into predefined categories. You provide an image, and it outputs a segmented image highlighting different objects or regions. This is ideal for researchers, scientists, or engineers who need to precisely delineate objects in visual data for analysis.
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Use this if you need to automatically identify and outline specific objects or areas within images, such as for medical imaging analysis, autonomous driving, or satellite imagery interpretation.
Not ideal if you only need to classify an entire image or detect bounding boxes around objects without pixel-level precision.
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Jupyter Notebook
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MIT
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Last pushed
Apr 24, 2022
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