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 | 1 | initial version |
using opencv's HOGDescriptor, you can only detect objects of a single class. (it's using a single, binary regression support vector in this case)
but you can also compute your own HOG features, and use those with multi-class SVM for classification.
you simply cannot to both at the same time, with the same setup.
| | 2 | No.2 Revision |
using opencv's HOGDescriptor, you can only detect objects of a single class. (it's using a single, binary regression support vector in this case)
but you can also compute your own HOG features, and use those with multi-class SVM for classification.
if you're using an SVM, you simply cannot to both at the same time, with the same setup. (it's a bit different with rcnn or yolo, where you get both segmentation and identification)
