Comments (3)
@praeclarumjj3 could you please help
from oneformer.
Hi @rono221, thanks for your interest in our work. To answer your questions:
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DETECTIONS_PER_IMAGE
is the top k queries considered from the total number of queries during the inference stage for the final instance segmentation predictions. Usually, it's fine to set it equal toNUM_QUERIES
.
OneFormer/oneformer/oneformer_model.py
Line 214 in 7611899
OneFormer/oneformer/oneformer_model.py
Line 445 in 7611899
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The right crop size depends on your use case. If, during the inference, you want to input high-resolution or low-resolution images, it's beneficial to train with a comparable resolution. The crop size is only used during training, so training with a larger resolution will take more time.
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It depends on the number of classes in your dataset as well, but since the size is similar to ADE20K, I would recommend training for 160k iterations to establish a baseline.
from oneformer.
Closing this, feel free to re-open.
from oneformer.
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from oneformer.