AI代码解释 _base_='./pspnet_r50-d8_512x1024_40k_cityscapes.py'model=dict(decode_head=dict(loss_decode=dict(type='CrossEntropyLoss',use_sigmoid=False,loss_weight=1.0,# DeepLab 对 cityscapes 使用这种权重 class_weight=[0.8373,0.9180,0.8660,1.0345,1.0166,0.9969,0.9754,1.0489,0.8786,1.0023,0.9539,...
use_sigmoid=False, # 在分割里是否使用 sigmoid 激活。 loss_weight=0.4))) # 辅助头里损失的权重。默认设置为0.4。 train_cfg = dict() # train_cfg 当前仅是一个占位符。 test_cfg = dict(mode='whole') # 测试模式, 选项是 'whole' 和'sliding'. 'whole': 整张图像全卷积(fully-convolutional)...
use_sigmoid=False, # 在分割里是否使用 sigmoid 激活。 loss_weight=0.4))) # 辅助头里损失的权重。默认设置为0.4。 train_cfg = dict() # train_cfg 当前仅是一个占位符。 test_cfg = dict(mode='whole') # 测试模式, 选项是 'whole' 和 'sliding'. 'whole': 整张图像全卷积(fully-convolutional)...
loss_decode=dict( loss_weight=1.0, type='CrossEntropyLoss', use_sigmoid=False), norm_cfg=dict(requires_grad=True, type='BN'), num_classes=6, pool_scales=( 1, 2, 3, 6, ), type='PSPHead'), pretrained='open-mmlab://resnet50_v1c', test_cfg=dict(mode='whole'), train_cfg=dict...
use_sigmoid=False, loss_weight=1.0)), auxiliary_head=dict( type='FCNHead', in_channels=1024, in_index=2, channels=256, num_convs=1, concat_input=False, dropout_ratio=0.1, num_classes=19, norm_cfg=norm_cfg, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid...
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0, # DeepLab 对 cityscapes 使用这种权重 class_weight=[0.8373, 0.9180, 0.8660, 1.0345, 1.0166, 0.9969, 0.9754, 1.0489, 0.8786, 1.0023, 0.9539, 0.9843, 1.1116, 0.9037, 1.0865, 1.0955, 1.0865, 1.1529, 1.0507]))) ...
loss_decode=dict( # 解码头(decode_head)里的损失函数的配置项。type='CrossEntropyLoss', # 在分割里使用的损失函数的类别。use_sigmoid=False, # 在分割里是否使用 sigmoid 激活。loss_weight=1.0)), # 解码头里损失的权重。auxiliary_head=dict(type='FCNHead', # 辅助头(auxiliary head)的种类。可用...
( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), dict( type='STDCHead', in_channels=256, channels=64, num_convs=1, num_classes=num_classes, boundary_threshold=0.1, in_index=0, norm_cfg=norm_cfg, concat_input=False, align_corners=True, loss_decode=[ dict( type='...
use_sigmoid=False, loss_weight=1.0)), auxiliary_head=dict( type='FCNHead', in_channels=384, in_index=2, channels=256, num_convs=1, concat_input=False, dropout_ratio=0.1, num_classes=19, norm_cfg=norm_cfg, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid...
_base_ = './pspnet_r50-d8_512x1024_40k_cityscapes.py'model=dict(decode_head=dict(loss_decode=dict(type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0,# DeepLab 对 cityscapes 使用这种权重class_weight=[0.8373, 0.9180, 0.8660, 1.0345, 1.0166, 0.9969, 0.9754,1.0489, 0.8786, 1.0023, ...