_base_ = './htc-without-semantic_r50_fpn_1x_coco.py' | |
model = dict( | |
data_preprocessor=dict(pad_seg=True), | |
roi_head=dict( | |
semantic_roi_extractor=dict( | |
type='SingleRoIExtractor', | |
roi_layer=dict(type='RoIAlign', output_size=14, sampling_ratio=0), | |
out_channels=256, | |
featmap_strides=[8]), | |
semantic_head=dict( | |
type='FusedSemanticHead', | |
num_ins=5, | |
fusion_level=1, | |
seg_scale_factor=1 / 8, | |
num_convs=4, | |
in_channels=256, | |
conv_out_channels=256, | |
num_classes=183, | |
loss_seg=dict( | |
type='CrossEntropyLoss', ignore_index=255, loss_weight=0.2)))) | |
train_pipeline = [ | |
dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}), | |
dict( | |
type='LoadAnnotations', with_bbox=True, with_mask=True, with_seg=True), | |
dict(type='Resize', scale=(1333, 800), keep_ratio=True), | |
dict(type='RandomFlip', prob=0.5), | |
dict(type='PackDetInputs') | |
] | |
train_dataloader = dict( | |
dataset=dict( | |
data_prefix=dict(img='train2017/', seg='stuffthingmaps/train2017/'), | |
pipeline=train_pipeline)) | |