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NicolasHug avatar NicolasHug commented on June 17, 2024

Sorry @ABCCASa , I don't understand the question.

So do we still need to use index=0

What does that refer to?

from vision.

ABCCASa avatar ABCCASa commented on June 17, 2024

Hi, @NicolasHug , Thanks for your reply,
I mean, for example, should I use ["background", "apple", "cat", "bottle", "people"] or ["apple", "cat", "bottle", "people"].
The value at index = 0 should always be background in faster rcnn. But in retinanet, it may not. I looked at the source code, and it threatens each class separately as a binary problem. For a box, if the value is close to 1 (e.g. [0.9, 0.1, 0.1]), then it belongs to this class. Otherwise, it's not. If the box does not belong to any of the classes, it will be the background (e.g., [0.001, 0.001, 0.013]). The retinanet uses sigmoid, not softmax, all class scores sum up do not need to be 1.
image

from vision.

NicolasHug avatar NicolasHug commented on June 17, 2024

Does this help: #4106 (comment) ?

the num_classes should include the background which is encoded with 0. During inference the model predicts labels starting from 1.

from vision.

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