mahdi-darvish/Instance-Segmentation-via-Training-Mask-RCNN-on-Custom-Dataset
Combining Google Open Images with COCO-dataset weights and training a Mask R-CNN model to accurately create a instance mask for pumpkins ;)
This project helps you accurately identify and outline individual objects within an image, creating a precise pixel-level mask for each instance rather than just a bounding box. It takes a collection of images and associated annotations (like those from Google Open Images) and outputs a trained model capable of drawing detailed masks around specific objects. This is ideal for anyone working with visual data who needs to distinguish between multiple occurrences of the same object in an image.
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Use this if you need to precisely locate and differentiate individual objects within images by creating detailed, pixel-level outlines for each one.
Not ideal if you only need to draw a simple box around objects or if your objects frequently overlap significantly, as it may struggle with highly clumped instances.
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Mar 28, 2021
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