How to train a Faster R-CNN with a Multi-labeled images table?
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I have a 8792x11 table with my dataset labeled with the Image Labeler:
1st column: imageFilename;
from 2nd to 11th column: different labels with the rectangles' dimensions, exactly as how the ground-truth dataset must be for Faster R-CNN training.
But MathWorks' examples show how to train the network with a one-labeled dataset.
How to train the net with a multi-labeled ground-truth table?
Thank you.
回答（1 个）
what does multi-labeled ground-truth mean? the MathWorks' rcnn example is for object detection with mutilple instances but one-labeld ground-truth.
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2021-1-14
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