Image Segmentation
Transformers
PyTorch
upernet
Inference Endpoints
test2 / configs /_base_ /models /lraspp_m-v3-d8.py
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# model settings
norm_cfg = dict(type='SyncBN', eps=0.001, requires_grad=True)
model = dict(
type='EncoderDecoder',
backbone=dict(
type='MobileNetV3',
arch='large',
out_indices=(1, 3, 16),
norm_cfg=norm_cfg),
decode_head=dict(
type='LRASPPHead',
in_channels=(16, 24, 960),
in_index=(0, 1, 2),
channels=128,
input_transform='multiple_select',
dropout_ratio=0.1,
num_classes=19,
norm_cfg=norm_cfg,
act_cfg=dict(type='ReLU'),
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
# model training and testing settings
train_cfg=dict(),
test_cfg=dict(mode='whole'))