Collections: - Name: bisenetv2 Metadata: Training Data: - Cityscapes Paper: URL: https://arxiv.org/abs/2004.02147 Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation' README: configs/bisenetv2/README.md Code: URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545 Version: v0.18.0 Models: - Name: bisenetv2_fcn_4x4_1024x1024_160k_cityscapes In Collection: bisenetv2 Metadata: backbone: BiSeNetV2 crop size: (1024,1024) lr schd: 160000 inference time (ms/im): - value: 31.48 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (1024,1024) memory (GB): 7.64 Results: - Task: Semantic Segmentation Dataset: Cityscapes Metrics: mIoU: 73.21 mIoU(ms+flip): 75.74 Config: configs/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes_20210902_015551-bcf10f09.pth - Name: bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes In Collection: bisenetv2 Metadata: backbone: BiSeNetV2 crop size: (1024,1024) lr schd: 160000 memory (GB): 7.64 Results: - Task: Semantic Segmentation Dataset: Cityscapes Metrics: mIoU: 73.57 mIoU(ms+flip): 75.8 Config: configs/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes.py Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes_20210902_112947-5f8103b4.pth - Name: bisenetv2_fcn_4x8_1024x1024_160k_cityscapes In Collection: bisenetv2 Metadata: backbone: BiSeNetV2 crop size: (1024,1024) lr schd: 160000 memory (GB): 15.05 Results: - Task: Semantic Segmentation Dataset: Cityscapes Metrics: mIoU: 75.76 mIoU(ms+flip): 77.79 Config: configs/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes.py Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes_20210903_000032-e1a2eed6.pth - Name: bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes In Collection: bisenetv2 Metadata: backbone: BiSeNetV2 crop size: (1024,1024) lr schd: 160000 inference time (ms/im): - value: 27.29 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (1024,1024) memory (GB): 5.77 Results: - Task: Semantic Segmentation Dataset: Cityscapes Metrics: mIoU: 73.07 mIoU(ms+flip): 75.13 Config: configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes_20210902_045942-b979777b.pth