You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
107 lines
2.9 KiB
107 lines
2.9 KiB
# Copyright (c) Meta Platforms, Inc. and affiliates. |
|
# All rights reserved. |
|
|
|
# This source code is licensed under the license found in the |
|
# LICENSE file in the root directory of this source tree. |
|
|
|
import torch |
|
|
|
from functools import partial |
|
|
|
from .modeling import ImageEncoderViT, MaskDecoder, PromptEncoder, Sam, TwoWayTransformer |
|
|
|
|
|
def build_sam_vit_h(checkpoint=None): |
|
return _build_sam( |
|
encoder_embed_dim=1280, |
|
encoder_depth=32, |
|
encoder_num_heads=16, |
|
encoder_global_attn_indexes=[7, 15, 23, 31], |
|
checkpoint=checkpoint, |
|
) |
|
|
|
|
|
build_sam = build_sam_vit_h |
|
|
|
|
|
def build_sam_vit_l(checkpoint=None): |
|
return _build_sam( |
|
encoder_embed_dim=1024, |
|
encoder_depth=24, |
|
encoder_num_heads=16, |
|
encoder_global_attn_indexes=[5, 11, 17, 23], |
|
checkpoint=checkpoint, |
|
) |
|
|
|
|
|
def build_sam_vit_b(checkpoint=None): |
|
return _build_sam( |
|
encoder_embed_dim=768, |
|
encoder_depth=12, |
|
encoder_num_heads=12, |
|
encoder_global_attn_indexes=[2, 5, 8, 11], |
|
checkpoint=checkpoint, |
|
) |
|
|
|
|
|
sam_model_registry = { |
|
"default": build_sam_vit_h, |
|
"vit_h": build_sam_vit_h, |
|
"vit_l": build_sam_vit_l, |
|
"vit_b": build_sam_vit_b, |
|
} |
|
|
|
|
|
def _build_sam( |
|
encoder_embed_dim, |
|
encoder_depth, |
|
encoder_num_heads, |
|
encoder_global_attn_indexes, |
|
checkpoint=None, |
|
): |
|
prompt_embed_dim = 256 |
|
image_size = 1024 |
|
vit_patch_size = 16 |
|
image_embedding_size = image_size // vit_patch_size |
|
sam = Sam( |
|
image_encoder=ImageEncoderViT( |
|
depth=encoder_depth, |
|
embed_dim=encoder_embed_dim, |
|
img_size=image_size, |
|
mlp_ratio=4, |
|
norm_layer=partial(torch.nn.LayerNorm, eps=1e-6), |
|
num_heads=encoder_num_heads, |
|
patch_size=vit_patch_size, |
|
qkv_bias=True, |
|
use_rel_pos=True, |
|
global_attn_indexes=encoder_global_attn_indexes, |
|
window_size=14, |
|
out_chans=prompt_embed_dim, |
|
), |
|
prompt_encoder=PromptEncoder( |
|
embed_dim=prompt_embed_dim, |
|
image_embedding_size=(image_embedding_size, image_embedding_size), |
|
input_image_size=(image_size, image_size), |
|
mask_in_chans=16, |
|
), |
|
mask_decoder=MaskDecoder( |
|
num_multimask_outputs=3, |
|
transformer=TwoWayTransformer( |
|
depth=2, |
|
embedding_dim=prompt_embed_dim, |
|
mlp_dim=2048, |
|
num_heads=8, |
|
), |
|
transformer_dim=prompt_embed_dim, |
|
iou_head_depth=3, |
|
iou_head_hidden_dim=256, |
|
), |
|
pixel_mean=[123.675, 116.28, 103.53], |
|
pixel_std=[58.395, 57.12, 57.375], |
|
) |
|
sam.eval() |
|
if checkpoint is not None: |
|
with open(checkpoint, "rb") as f: |
|
state_dict = torch.load(f) |
|
sam.load_state_dict(state_dict) |
|
return sam
|
|
|