Comments (2)
Sorry that we do not consider applying RNGDet++/RNGDet on aerial images with different resolutions, and there are no parameters in the code to realize it. You can modify the code by yourself for your own applications. You can
- enlarge the ROI crop size
- modify the size of points in the GT segmentation label
- enlarge the step size of the agent
- retrain the whole model
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thanks for your answer
from rngdetplusplus.
Related Issues (20)
- Segmentation operations during training HOT 4
- about Training label calculation HOT 1
- About RNGDet result HOT 3
- How to Batch Training? HOT 2
- Some issues related to history_map HOT 2
- L1 Loss HOT 2
- Training Label Calculation HOT 4
- CNN backones HOT 1
- Tensorboard Log HOT 3
- aux_loss HOT 1
- About the preparation of the training dataset. HOT 5
- This is a problem about rtree.go HOT 4
- The number of "unexplored_edges" is larger than "num_queries" HOT 2
- About Evaluation Metrics HOT 2
- I am not sure why not try RoadTracer Dataset in RNGDet++ like the experiment conducted in RNGDet HOT 1
- Inference problem on the new trained weights HOT 4
- how long it took for your model, which was trained on 4 RTX4090,and how many epochs it took to achieve the current level of performance. HOT 1
- Intersection Detection HOT 1
- dataset
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