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deploy: 8168d837ad161f5d6ab58bf87bf756360d21714e
Browse files- README.md +1 -1
- layout_overlap.py +7 -1
README.md
CHANGED
@@ -1,5 +1,5 @@
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---
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-
title: Layout
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emoji: π
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colorFrom: pink
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colorTo: purple
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---
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title: Layout Overlap
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emoji: π
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colorFrom: pink
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colorTo: purple
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layout_overlap.py
CHANGED
@@ -118,18 +118,21 @@ class LayoutOverlap(evaluate.Metric):
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self,
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score_ac_layout_gan: npt.NDArray[np.float64],
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batch_mask: npt.NDArray[np.bool_],
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):
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# shape: (B, S) -> (B,)
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batch_mask = batch_mask.sum(axis=1)
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# shape: (B,)
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score_normalized = score_ac_layout_gan / batch_mask
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score_normalized[np.isnan(score_normalized)] = 0.0
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return score_normalized
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def _compute_layout_gan(
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self, S: int, B: int, ai: npt.NDArray[np.float64]
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) -> npt.NDArray[np.float64]:
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indices = np.arange(S)
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ii, jj = np.meshgrid(indices, indices, indexing="ij")
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@@ -154,6 +157,9 @@ class LayoutOverlap(evaluate.Metric):
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# shape: (B, model_max_length)
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batch_mask = np.array(batch_mask)
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# S: model_max_length
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B, S, C = batch_bbox.shape
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self,
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score_ac_layout_gan: npt.NDArray[np.float64],
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batch_mask: npt.NDArray[np.bool_],
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) -> npt.NDArray[np.float64]:
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# shape: (B, S) -> (B,)
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batch_mask = batch_mask.sum(axis=1)
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# shape: (B,)
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score_normalized = score_ac_layout_gan / batch_mask
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score_normalized[np.isnan(score_normalized)] = 0.0
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return score_normalized
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def _compute_layout_gan(
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self, S: int, B: int, ai: npt.NDArray[np.float64]
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) -> npt.NDArray[np.float64]:
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indices = np.arange(S)
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ii, jj = np.meshgrid(indices, indices, indexing="ij")
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# shape: (B, model_max_length)
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batch_mask = np.array(batch_mask)
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assert batch_bbox.ndim == 3
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assert batch_mask.ndim == 2
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# S: model_max_length
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B, S, C = batch_bbox.shape
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