Comments (2)
gabrieldemarmiesse
commented on June 1, 2024
The softmax is applied along the channels axis, pixelwise, so in the end, it's similar to do one classification per pixel, and grouping the result to provide one heatmap per class. This approach works well on examples that I've shown on the readme. And can be also think of, as a classification network applied as a sliding window on the input image.
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gabrieldemarmiesse
commented on June 1, 2024
I'll close this issue. Feel free to reopen it if necessary.
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Related Issues (15)
- regarding using a dataset of different domain HOT 6
- AttributeError: 'Model' object has no attribute 'name' HOT 5
- Error using own Model with non-quadratic images HOT 3
- Unexpected Type Error while using a custom model HOT 5
- can it be used to grey-level imageset network? HOT 2
- to_heatmap function error HOT 2
- KeyError: 'Strides' With Custom Model HOT 1
- Example not working: NameError: name 'preprocess_input' is not defined HOT 5
- regarding re-train the VGG19 model HOT 5
- Update to Keras 2 HOT 4
- Usign the code on your own model HOT 32
- sigmoid outputs? HOT 2
- MemoryError on Raspberry Pi HOT 17
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