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Quick fix for losses docs (microsoft#333)
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* Fix doc link

* Brute forcing rst syntax

* Adding more docs to ChesapeakeCVPR
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calebrob6 authored Dec 28, 2021
1 parent da0c668 commit 3d8f9f1
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6 changes: 6 additions & 0 deletions torchgeo/datasets/chesapeake.py
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Expand Up @@ -288,6 +288,12 @@ class ChesapeakeCVPR(GeoDataset):
This dataset was organized to accompany the 2019 CVPR paper, "Large Scale
High-Resolution Land Cover Mapping with Multi-Resolution Data".
The paper "Resolving label uncertainty with implicit generative models" added an
additional layer of data to this dataset containing a prior over the Chesapeake Bay
land cover classes generated from the NLCD land cover labels. For more information
about this layer see `the dataset documentation
<https://zenodo.org/record/5652512#.YcuAIZLMIQ8>`_.
If you use this dataset in your research, please cite the following paper:
* https://doi.org/10.1109/cvpr.2019.01301
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8 changes: 4 additions & 4 deletions torchgeo/losses/qr.py
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Expand Up @@ -14,8 +14,8 @@
class QRLoss(Module):
"""The QR (forward) loss between class probabilities and predictions.
This loss is defined in 'Resolving label uncertainty with implicit generative
models' https://openreview.net/forum?id=AEa_UepnMDX.
This loss is defined in `'Resolving label uncertainty with implicit generative
models' <https://openreview.net/forum?id=AEa_UepnMDX>`_.
.. versionadded:: 0.2
"""
Expand Down Expand Up @@ -45,8 +45,8 @@ def forward(self, probs: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
class RQLoss(Module):
"""The RQ (backwards) loss between class probabilities and predictions.
This loss is defined in 'Resolving label uncertainty with implicit generative
models' https://openreview.net/forum?id=AEa_UepnMDX.
This loss is defined in `'Resolving label uncertainty with implicit generative
models' <https://openreview.net/forum?id=AEa_UepnMDX>`_.
.. versionadded:: 0.2
"""
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