| _base_ = './htc_r50_fpn_head-without-semantic_1x_nuim.py' | |
| model = dict( | |
| 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, | |
| num_convs=4, | |
| in_channels=256, | |
| conv_out_channels=256, | |
| num_classes=32, | |
| ignore_label=0, | |
| loss_weight=0.2))) | |
| data_root = 'data/nuimages/' | |
| backend_args = None | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile', backend_args=backend_args), | |
| dict( | |
| type='LoadAnnotations', with_bbox=True, with_mask=True, with_seg=True), | |
| dict( | |
| type='Resize', | |
| img_scale=[(1280, 720), (1920, 1080)], | |
| multiscale_mode='range', | |
| keep_ratio=True), | |
| dict(type='RandomFlip', flip_ratio=0.5), | |
| dict(type='SegRescale', scale_factor=1 / 8), | |
| dict(type='PackDetInputs') | |
| ] | |
| data = dict( | |
| train=dict( | |
| seg_prefix=data_root + 'annotations/semantic_masks/', | |
| pipeline=train_pipeline)) | |