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ultralytics 8.0.197 save P, R, F1 curves to metrics (#5354)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: erminkev1 <83356055+erminkev1@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Andy <39454881+yermandy@users.noreply.github.com>
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Glenn Jocher 2023-10-13 02:49:31 +02:00 • committed by GitHub
parent 7fd5dcbd86
commit 12e3eef844
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33 changed files with 337 additions and 195 deletions
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6
ultralytics/models/sam/modules/encoders.py
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@ -304,11 +304,11 @@ class PositionEmbeddingRandom(nn.Module):
def _pe_encoding(self, coords: torch.Tensor) -> torch.Tensor:
"""Positionally encode points that are normalized to [0,1]."""
# assuming coords are in [0, 1]^2 square and have d_1 x ... x d_n x 2 shape
# Assuming coords are in [0, 1]^2 square and have d_1 x ... x d_n x 2 shape
coords = 2 * coords - 1
coords = coords @ self.positional_encoding_gaussian_matrix
coords = 2 * np.pi * coords
# outputs d_1 x ... x d_n x C shape
# Outputs d_1 x ... x d_n x C shape
return torch.cat([torch.sin(coords), torch.cos(coords)], dim=-1)
def forward(self, size: Tuple[int, int]) -> torch.Tensor:
@ -429,7 +429,7 @@ class Attention(nn.Module):
self.use_rel_pos = use_rel_pos
if self.use_rel_pos:
assert (input_size is not None), 'Input size must be provided if using relative positional encoding.'
# initialize relative positional embeddings
# Initialize relative positional embeddings
self.rel_pos_h = nn.Parameter(torch.zeros(2 * input_size[0] - 1, head_dim))
self.rel_pos_w = nn.Parameter(torch.zeros(2 * input_size[1] - 1, head_dim))