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# 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 segment_anything.modeling import ImageEncoderViT, MaskDecoder, PromptEncoder, Sam, TwoWayTransformer
from EdgeSAM.rep_vit import RepViT
prompt_embed_dim = 256
image_size = 1024
vit_patch_size = 16
image_embedding_size = image_size // vit_patch_size
def build_edge_sam(checkpoint=None, upsample_mode="bicubic"):
image_encoder = RepViT(
arch="m1",
img_size=image_size,
upsample_mode=upsample_mode
)
return _build_sam(image_encoder, checkpoint)
sam_model_registry = {
"default": build_edge_sam,
"edge_sam": build_edge_sam,
}
def _build_sam_encoder(
encoder_embed_dim,
encoder_depth,
encoder_num_heads,
encoder_global_attn_indexes,
):
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,
)
return image_encoder
def _build_sam(
image_encoder,
checkpoint=None,
):
sam = Sam(
image_encoder=image_encoder,
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, map_location="cpu")
sam.load_state_dict(state_dict)
return sam |