Image Segmentation
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PyTorch
upernet
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test2 / configs /point_rend /pointrend_r50_512x512_160k_ade20k.py
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_base_ = [
'../_base_/models/pointrend_r50.py', '../_base_/datasets/ade20k.py',
'../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
]
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(decode_head=[
dict(
type='FPNHead',
in_channels=[256, 256, 256, 256],
in_index=[0, 1, 2, 3],
feature_strides=[4, 8, 16, 32],
channels=128,
dropout_ratio=-1,
num_classes=150,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
dict(
type='PointHead',
in_channels=[256],
in_index=[0],
channels=256,
num_fcs=3,
coarse_pred_each_layer=True,
dropout_ratio=-1,
num_classes=150,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0))
])
lr_config = dict(warmup='linear', warmup_iters=200)