edge's People
edge's Issues
Implement YOLOv8 Lightning Module
Adapt dinov2 as a detectron2's Backbone
Relevant DinoV2 snippet
class DinoVisionTransformer(nn.Module):
....
def forward_features(self, x, masks=None):
if isinstance(x, list):
return self.forward_features_list(x, masks)
x = self.prepare_tokens_with_masks(x, masks)
for blk in self.blocks:
x = blk(x)
x_norm = self.norm(x)
return {
"x_norm_clstoken": x_norm[:, 0],
"x_norm_regtokens": x_norm[:, 1 : self.num_register_tokens + 1],
"x_norm_patchtokens": x_norm[:, self.num_register_tokens + 1 :],
"x_prenorm": x,
"masks": masks,
}
Notes:
x_prenorm
is of shape[1, 1370, 768]
or[B, P*P + 1, D]
Relevant detectron2 snippet
class ViT(Backbone):
...
def forward(self, x):
x = self.patch_embed(x)
if self.pos_embed is not None:
x = x + get_abs_pos(
self.pos_embed, self.pretrain_use_cls_token, (x.shape[1], x.shape[2])
)
for blk in self.blocks:
x = blk(x)
outputs = {self._out_features[0]: x.permute(0, 3, 1, 2)}
return outputs
Implement Cityscapes datamodule
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