HongChuang/ultralytics-ascend
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PyCharm Code and Docs Inspect fixes v1 (#18461)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Ultralytics Assistant <135830346+UltralyticsAssistant@users.noreply.github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2025-01-03 01:16:18 +05:00 • committed by GitHub
parent 126867e355
commit 7f1a50e893
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26 changed files with 90 additions and 91 deletions
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ultralytics/models/sam/modules/sam.py
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@ -425,7 +425,7 @@ class SAM2Model(torch.nn.Module):
low_res_masks: Tensor of shape (B, 1, H*4, W*4) with the best low-resolution mask.
high_res_masks: Tensor of shape (B, 1, H*16, W*16) with the best high-resolution mask.
obj_ptr: Tensor of shape (B, C) with object pointer vector for the output mask.
object_score_logits: Tensor of shape (B,) with object score logits.
object_score_logits: Tensor of shape (B) with object score logits.
Where M is 3 if multimask_output=True, and 1 if multimask_output=False.
@ -643,7 +643,7 @@ class SAM2Model(torch.nn.Module):
if not is_init_cond_frame:
# Retrieve the memories encoded with the maskmem backbone
to_cat_memory, to_cat_memory_pos_embed = [], []
# Add conditioning frames's output first (all cond frames have t_pos=0 for
# Add conditioning frame's output first (all cond frames have t_pos=0 for
# when getting temporal positional embedding below)
assert len(output_dict["cond_frame_outputs"]) > 0
# Select a maximum number of temporally closest cond frames for cross attention